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Altcoin PortfolioTrack your altcoin portfolio balance in Fiat currency. Make sure to open the data window to the right of your charts, it makes everything alot easier to read at a glance. To learn more about customizing this script to fit your portfolio, watch the video here: youtu.be To get more cool scripts and up-to-date information about Autoview, join us in slack slack.with.pink As per the usual, we hope this script helps with your trading venture. Good luck, and happy trading.
Indicador Pine Script®
por CryptoRox
Initial Balance + MAG7 Dashboard [midsu]IB + MAG7 Dashboard - Indicator Description What It Is A dual-purpose indicator that combines Initial Balance (IB) tracking with real-time Magnificent 7 tech sector monitoring. Perfect for day traders and swing traders who trade index futures (NQ, ES) or tech stocks. What It Shows Initial Balance (IB) IB Box: Visualizes the first hour of trading (9:30-10:30 AM EST by default) Key Levels: High, Low, Midpoint with customizable extensions (25%, 50%, 100%) Day Type Detection: Automatically identifies Range Days vs Trend Days Dashboard: Live metrics including IB range, price location, and strategy hints MAG7 Dashboard 7 Tech Giants: NVDA, AAPL, GOOGL, MSFT, AMZN, META, TSLA (sorted by market cap weight) Real-Time Performance: % change for each stock on your chart's timeframe Weighted Signal: Combined score showing overall tech sector direction Market Cap Weights: User-adjustable with date tracking for monthly updates How to Use It For Day Traders (NQ, QQQ, SPY) Step 1: Morning Setup Watch the IB form during the first hour (9:30-10:30 AM EST) Check MAG7 Dashboard to see if big tech is bullish (green) or bearish (red) Step 2: Wait for Confirmation Narrow IB + Strong MAG7 Bias = High probability trend day, trade breakouts Wide IB + Neutral MAG7 = Range day likely, fade extremes Step 3: Trade Setup IB Breakout + MAG7 Bullish = Go long, target IB extensions (25%, 50%, 100%) IB Breakout + MAG7 Bearish = Go short, target IB extensions Price Inside IB + Range Day = Trade mean reversion back to midpoint For Swing Traders Daily Bias Check Set chart to 1H or Daily timeframe Check MAG7 Weighted Signal: Strong Bull (>+0.70%) = Tech uptrend, favor long positions Strong Bear (<-0.70%) = Tech downtrend, favor short positions Neutral = Choppy, reduce position size Position Sizing Use MAG7 dashboard to gauge conviction 6-7 stocks green = High conviction longs 6-7 stocks red = High conviction shorts Split 4-3 = Low conviction, smaller positions Key Concepts Initial Balance The price range established in the first hour sets the tone for the day 80% of days either stay in range or break out and continue trending Narrow IB = Explosive trend day likely Wide IB = Choppy range day likely MAG7 Influence These 7 stocks represent ~50% of Nasdaq 100 weight When they move together, indexes follow Divergence (price up but MAG7 down) = Warning sign Combined Strategy Use IB for tactical entries/exits (specific price levels) Use MAG7 for directional bias (should I be bullish or bearish?) Best setups = Both indicators align (IB breakout + MAG7 confirming direction) Settings Overview Initial Balance Customize start time, duration, colors Toggle extensions, labels, dashboard Set range day detection parameters MAG7 Dashboard Update weights monthly magnificent7 Adjust movement filter (default 0.1%) Set text size for your screen Pro Tips ✅ Best used on NQ, ES futures (tech-heavy) since MAG7 directly impacts it ✅ Works on any timeframe - the calculations adapt automatically ✅ Update MAG7 weights once per month (takes 30 seconds) ✅ IB is most reliable on liquid instruments (NQ, ES, SPY, QQQ) ✅ Combine with volume analysis for even better confirmation ✅ Watch for divergences - they often signal reversals Installation Verify MAG7 weights are current (tradingview) Adjust IB time settings if you trade different markets Customize colors/sizes to your preference
Indicador Pine Script®
por midst
Mag7 Dashboard [midsu]Mag7 Dashboard - Real-Time Tech Sector Momentum What It Does Tracks the 7 most influential tech stocks (NVDA, AAPL, GOOGL, MSFT, AMZN, META, TSLA) and displays their weighted performance in a clean dashboard. Shows you instantly whether big tech is bullish, bearish, or neutral. Why Use It These 7 stocks represent ~30% of the S&P 500 and over 50% of the Nasdaq 100. When they move, the market follows. This indicator gives you real-time insight into where the smart money is flowing. How to Use For Day Traders: Check the "Weighted Signal" at market open to gauge tech sector bias Enter trades in the direction of the bias (green = long, red = short) Watch for bias shifts during the day as momentum changes For Swing Traders: Use on 1H or Daily timeframe for longer-term sector sentiment Strong Bull/Bear signals = high conviction setups Neutral signals = avoid new positions or reduce size Quick Reference: 6-7 stocks green = Strong bullish momentum 6-7 stocks red = Strong bearish momentum Split 4-3 or closer = Choppy, no clear direction Reading the Dashboard Weight %: How much influence each stock has (based on market cap) % Change: Real-time percentage change from previous bar Status: ⬆️ Strong, ⬆️ Slight, ↔️ Neutral, ⬇️ Slight, ⬇️ Strong Weighted Signal: Combined score showing overall tech sector direction Settings Dashboard Text Size: Tiny, Small, or Normal (adjust for your screen) Mag7 Weights: Update monthly magnificent7 Weights change slowly as market caps shift Takes 30 seconds to update all 7 stocks Set "Last Updated" date to track your maintenance Stock Movement Filter: Default 0.1% - minimum movement to count as bullish/bearish Installation Add indicator to your TradingView chart Verify weights are current (Tradingview) Adjust dashboard text size if needed That's it! The dashboard appears top-right, live prices update automatically
Indicador Pine Script®
por midst
Pulsar Heatmap CVD/OBV [by Oberlunar]Pulsar Heatmap CVD/OBV by Oberlunar is a non-repainting order-flow-like indicator designed to support fast, practical decisions—especially for day trading and scalping. It blends OBV and CVD into a structured heatmap with three lanes (OBV, CVD, and a blended COMBO) and splits each lane into two halves: flow pressure and price reaction (PriceΔ) . All values are normalised into the same range, so the intensity of each component is easy to compare at a glance. In a simple sense, Pulsar Heatmap aims to provide a clean, integrated order-flow view: one framework that turns well-known volume concepts into a clearer read of market pressure and response. Personally, it feels like the kind of tool I would have always wanted on my chart, because it brings familiar information together into a more organic picture that is easier to use in real time. Visually, the indicator is built around three main elements: the heatmap lanes , a pulsing triangle HUD , and a timed dashboard table . Under the hood, it follows a clear hierarchy: a Bias layer (directional context with a confidence percentage), a strict Signal layer (triggered only when full alignment occurs, with optional confirmation and stickiness), and optional timing logic based on ROC + Acceleration to validate impulses and highlight potential Exhaustion or Absorption regimes. With the option "Safe Mode" enabled, calculations update only on confirmed bars, so signals remain stable and do not repaint. Optionally, the script can also print signal arrows/labels on the main chart only when a real Signal triggers (not when you only have Bias). To keep the chart clean, the same-direction label is not repeated unless the next signal appears at a more advantageous price than the previous one (for shorts: a higher price; for longs: a lower price). If the direction flips (SHORT → LONG or LONG → SHORT), label printing is re-enabled immediately. What makes Pulsar Heatmap feel different is that it doesn’t leave you with two separate lines and a lot of guesswork. It organises the information into a readable decision map: pressure , response , agreement , disagreement , impulse , and timing . It was built with scalping in mind, but it’s not limited to scalping: the structure is useful whenever you want context first, and a strict trigger only when alignment is truly present. Clean Trend Alignment (Ideal Continuation) A “best case” scenario where flow and price response agree across lanes, so the system produces a high-confidence direction and a clean trigger. Show the heatmap with consistent colouring, the Bias band strong, and a confirmed signal/bias. Setup 1 — Long Signal (Clean Alignment + Impulse) In this example, Pulsar Heatmap transitions into a clear long setup when the system prints a LONG SIGNAL . The key idea is simple: the indicator does not enter on “bias” alone. It waits for full alignment across the internal lanes, optionally reinforced by the ROC/Acceleration impulse layer, and only then does it confirm a signal on a closed bar (Safe Mode). What to highlight on the screenshot The LONG SIGNAL label: this is the only moment the setup is considered “triggered”. The LONG BIAS % label: this is context (direction + confidence), not the trigger. The Triangle HUD : it visually summarises which component is driving the move (OBV/CVD/COMBO weight). The Timed Table : show that Exhaustion is OFF while impulse metrics are supportive ( dynROC U and dynACC U positive). If present, the Absorption state (e.g., ABS_LONG + “tight range”): it often appears during compression before expansion, and it adds context to why the breakout can accelerate. How to read this long setup Context : Bias is long (even if the % is not huge yet), and the system is not showing exhaustion. Trigger : A LONG SIGNAL appears only after full alignment (with confirmation bars). If dynamic gating is enabled, the signal is valid only when the impulse agrees. Quality checks : Positive dynROC and dynACC support the timing; absence of exhaustion reduces the risk of “late entry”. Absorption/tight range can indicate a “pressure build-up” phase. Practical scalping execution (simple rule set) Entry timing: consider the entry only on (or immediately after) the confirmed LONG SIGNAL candle. Risk idea: invalidate the setup if the signal flips, or if price falls back into the compression/range that preceded the move (common absorption-breakout logic). Exit clue: if Exhaustion turns ON or impulse weakens (acceleration flips), treat it as a warning to reduce exposure or take profit. Setup 2 — Short Signal After Compression (Absorption → Release) In this screenshot the short trade idea is not coming from “red candles” alone, but from a very specific sequence: the heatmap shows a shift into bearish alignment, the system prints a SHORT SIGNAL , and the timed module confirms that the market was in a tight range while sell pressure started to dominate. What this image is really showing You have a SHORT SIGNAL label on the chart: this is the trigger moment (not the bias). The context reads SHORT BIAS 18% : it’s supportive, but the execution decision is driven by the signal. The table shows Absorption = SHORT with a tight range (Range % is low): this often means price was compressed while one side kept applying pressure. dyn metrics are negative ( dynROC U < 0 and dynACC U < 0): the impulse is coherent with the short direction, so the move is not just “random drift.” How to read the heatmap here Earlier, the lanes are mixed (more “two-sided”), then near the signal, the heatmap becomes decisively bearish. That change matters: it tells you the market stopped being balanced and started leaning in one direction with better internal coherence. Why is this short “high quality” in scalping terms Compression first : absorption/tight range means the market was storing energy. Alignment next : the signal appears when the internal lanes agree. Impulse last : negative ROC + negative acceleration support a real downside push, reducing the odds of a weak, slow fade. Simple ensure-you-don’t-overtrade rule Treat the SHORT SIGNAL as the only “go” moment. If you only see bias without signal, or the heatmap stays mixed/disagreeing, it’s usually a lower-quality scalp environment. Disagreement Zone (Mixed Votes, Higher Risk) — A Practical Exit Area In this screenshot, Pulsar Heatmap is clearly warning that the market is no longer “one-sided”. You can still see a directional context ( SHORT BIAS 11% ), but the key message is the DISAGREE tag: the reminder that the internal votes are split and the flow/price components are no longer moving in a clean, coherent way. What this means in a trend continuation is very practical: a Disagreement Zone is often a good EXIT area . When you are already in a short trend, this is the moment where continuation becomes less reliable and where the market can start rotating, stalling, or snapping back. Why it works as an exit trigger In a healthy continuation, the lanes tend to stay aligned. Here they don’t: one or more halves contradict the dominant direction. That loss of coherence typically shows up before the chart becomes obvious, so it can act as an early warning. For scalping, this is where risk/reward often deteriorates: spreads, noise, and whipsaws increase exactly when the indicator starts disagreeing. How to use it in a simple way If you are already short , treat DISAGREE as a signal to take profit, tighten the stop, or scale out . Avoid adding to the position inside disagreement: even if bias remains short, the internal structure is not “clean” enough to justify aggressive continuation entries. If later the heatmap returns to full alignment and a new SHORT SIGNAL appears (ideally at a better price), then the continuation becomes actionable again. “DISAGREE during a short continuation: coherence breaks down. In practice, this is often an exit/scale-out zone, not a fresh entry zone.” Setup 3 — Neutral State (Stand-By Zone, No Trade Yet) In the following screenshot, Pulsar Heatmap is doing something very important: it is clearly saying NEUTRAL 0% . Even if, visually, price could “look” like it might resume upward, the indicator is not providing a directional edge yet. This is a classic stand-by condition: the market is transitioning, and the internal components are not aligned enough to justify a directional scalp. “Neutral 0%: mixed votes and no dominant driver. Even if the price looks promising, Pulsar stays in stand-by until bias rebuilds and a confirmed signal appears.” What to highlight on the screenshot The centre label NEUTRAL 0% : this is the key message—no bias strength worth following. The heatmap is mixed/transitioning: lanes are not consistently one colour, meaning votes are not coherent. The triangle HUD sits close to the centre: it visually reflects “no dominant driver” right now. The table can still show background context (e.g., Absorption with a tight range), but that does not override neutrality: it’s information, not a trigger. How to interpret “Neutral” in practice When the indicator is neutral, it means the system sees a balance between pressure and reaction (or conflicting components), so direction is statistically less reliable. In scalping terms, this is usually where spreads and noise can eat you alive if you force entries. Why this is still useful (even without a trade) Neutral is not “nothing”—it is a filter. It prevents you from trading when the signal quality is low, and it forces the workflow to be clean: wait for Bias to build, then wait for a confirmed Signal , and only then treat it as a real setup. What you wait for next If the market turns bullish again, you want to see heatmap alignment returning and eventually a confirmed LONG SIGNAL —however, in the following examples, the heatmap does not follow the trade completely (unlike the previous generated long signal). Thus, a long entry is very risky. If the market rolls over, you want the opposite: bearish alignment and a confirmed SHORT SIGNAL . Until one of these happens, Neutral = stand-by . Setup 4 — Impulse + Exhaustion (Late-Stage Move, Don’t Chase) In this screenshot, you’re basically seeing a “timing warning” configuration. Price prints a sharp bearish extension, but Pulsar Heatmap is not presenting it as a clean continuation setup: the center read is NEUTRAL 0% , while the timed engine shows both Absorption = SHORT and Exhaustion = SHORT . That combination often means: the downside pressure was real, but the move is already in a late/fragile phase (good for managing an existing short, not for opening a new one). How to read it (practical scalping logic) Absorption SHORT = there was compression/tight action with persistent bearish pressure building under the surface. Exhaustion SHORT = the impulse is “spent” or destabilising (acceleration signature is no longer healthy for continuation entries). Neutral 0% on the main HUD = the system is not granting directional confidence anymore, even if the last candles look aggressive. Translation: if you were already short, this zone is often for taking profit / tightening risk . If you are not in, it’s usually a wait-for-reset moment. Possible mean reversions in yellow Those yellow tiles are the indicator’s “caution prints” (the same colour family used to express DISAGREE ). They appear when the internal structure becomes mixed —i.e., some halves/lanes are not supporting the dominant direction cleanly (or a divergence-style conflict is detected). In practice, they often mark the transition from clean pressure to noisy/late pressure , which is exactly where chasing entries tends to be punished. How to use them In a trend continuation, yellow tiles are a strong hint to stop adding and to manage risk more defensively (or treat the phase as “risky trend reversion”). When they show up near an extension candle (like here), they often signal that the move is shifting into a less stable regime—better for protecting profits than for initiating new entries. Stepping back for a moment, OBV (On-Balance Volume) and CVD (Cumulative Volume Delta) are both classic tools for studying volume flow, but they differ in what they measure. OBV tracks cumulative volume using price direction: it adds volume on up closes and subtracts it on down closes. CVD tracks the net difference between buying and selling pressure, aiming to reflect the effective push from buyers versus sellers. Both describe the "force behind price" , but from different angles. OBV is the more traditional approach. It increases when the market closes higher and decreases when it closes lower, so it often works well as a trend-support and divergence tool: if price rises while OBV falls, that mismatch can suggest weakness beneath the move. Because it relies on the close-to-close direction, OBV naturally aligns with trend confirmation across bars. CVD , instead, is about the ongoing battle between buyers and sellers. Conceptually, it accumulates the net delta between aggressive buying and aggressive selling over time. Positive values tend to indicate stronger buying pressure; negative values indicate stronger selling pressure. Its focus is the tug-of-war itself—who is pushing, rather than simply whether the bar ended up closing up or down. The practical differences are straightforward. OBV uses the closing direction to assign the full volume, so it tends to be more connected to the overall trend structure. CVD is usually more sensitive to shifts in pressure and can react faster when the market changes character. OBV is commonly used to confirm trends and highlight divergences; CVD is commonly used to spot early pressure changes and moments where one side starts to dominate. This is also why combining them inside one normalised framework can be so effective. You are not relying on a single volume interpretation. You are pairing a trend-confirmation view (OBV) with a pressure-sensitive view (CVD), and you are making them comparable in a shared scale so agreement and divergence become immediately visible. When they agree, conviction is clearer. When they diverge, you often see important information—hesitation, absorption, or pressure that the price is not fully accepting. 👁️ by Oberlunar ⭐
Indicador Pine Script®
por oberlunar_tr
Enigma UnlockedENIGMA Indicator: A Comprehensive Market Bias & Success Tracker The ENIGMA Indicator is a powerful tool designed for traders who aim to identify market bias, track price movements, and evaluate trade performance using multiple timeframes. It combines multiple indicators and advanced logic to provide real-time insights into market trends, helping traders make more informed decisions. Key Features 1. Multi-Timeframe Bias Calculation: The ENIGMA Indicator tracks the market bias across multiple timeframes—Daily (D), 4-Hour (H4), 1-Hour (H1), 30-Minute (30M), 15-Minute (15M), 5-Minute (5M), and 1-Minute (1M). How the Bias is Created: The Bias is a key feature of the ENIGMA Indicator and is determined by comparing the current price with previous price levels for each timeframe. - Bullish Bias (1): The market is considered **bullish** if the **current closing price** is higher than the **previous timeframe’s high**. This suggests that the market is trending upwards, and buyers are in control. - Bearish Bias (-1): The market is considered **bearish** if the **current closing price** is lower than the **previous timeframe’s low**. This suggests that the market is trending downwards, and sellers are in control. - Neutral Bias (0): The market is considered **neutral** if the price is between the **previous high** and **previous low**, indicating indecision or a range-bound market. This bias calculation is performed independently for each timeframe. The **Bias** for each timeframe is then displayed in the **Bias Table** on your chart, providing a clear view of market direction across multiple timeframes. 2. **Customizable Table Display:** - The indicator provides a table that displays the bias for each selected timeframe, clearly marking whether the market is **Bullish**, **Bearish**, or **Neutral**. - Users can choose where to place the table on the chart: top-left, top-right, bottom-left, bottom-right, or center positions, allowing for easy and personalized chart management. 3. **Win/Loss Tracker:** - The table also tracks the **success rate** of **buy** and **sell** trades based on price retests of key bias levels. - For each period (Day, Week, Month), it tracks how often the price has moved in the direction of the initial bias, counting **Buy Wins**, **Sell Wins**, **Buy Losses**, and **Sell Losses**. - This helps traders assess the effectiveness of the market bias over time and adjust their strategies accordingly. #### **How the Success Calculation Determines the Success Rate:** The **Success Calculation** is designed to track how often the price follows the direction of the market bias. It does this by evaluating how the price retests key levels associated with the identified market bias: 1. **Buy Success Calculation**: - The success of a **Buy Trade** is determined when the price breaks above the **previous high** after a **bullish bias** has been identified. - If the price continues to move higher (i.e., makes a new high) after breaking the previous high, the **buy trade is considered successful**. - The indicator tracks how many times this condition is met and counts it as a **Buy Win**. 2. **Sell Success Calculation**: - The success of a **Sell Trade** is determined when the price breaks below the **previous low** after a **bearish bias** has been identified. - If the price continues to move lower (i.e., makes a new low) after breaking the previous low, the **sell trade is considered successful**. - The indicator tracks how many times this condition is met and counts it as a **Sell Win**. 3. **Failure Calculations**: - If the price does not move as expected (i.e., it does not continue in the direction of the identified bias), the trade is considered a **loss** and is tracked as **Buy Loss** or **Sell Loss**, depending on whether it was a bullish or bearish trade. The ENIGMA Indicator keeps a running tally of **Buy Wins**, **Sell Wins**, **Buy Losses**, and **Sell Losses** over a set period (which can be customized to Days, Weeks, or Months). These statistics are updated dynamically in the **Bias Table**, allowing you to track your success rate in real-time and gain insights into the effectiveness of the market bias. #### **Customizable Period Tracking:** - The ENIGMA Indicator allows you to set custom tracking periods (e.g., 30 days, 2 weeks, etc.). The performance metrics reset after each tracking period, helping you monitor your success in different market conditions. 5. **Interactive Settings:** - **Lookback Period**: Define how many bars the indicator should consider for bias calculations. - **Success Tracking**: Set the number of candles to track for calculating the win/loss performance. - **Time Threshold**: Set a time threshold to help define the period during which price retests are considered valid. - **Info Tooltip**: You can enable the information tool in the settings to view detailed explanations of how wins and losses are calculated, ensuring you understand how the indicator works and how the results are derived. #### **How to Use the ENIGMA Indicator:** 1. **Install the Indicator**: - Add the ENIGMA Indicator to your chart. It will automatically calculate and display the bias for multiple timeframes. 2. **Interpret the Bias Table**: - The bias table will show whether the market is **Bullish**, **Bearish**, or **Neutral** across different timeframes. - Look for alignment between the timeframes—when multiple timeframes show the same bias, it may indicate a stronger trend. 3. **Use the Win/Loss Tracker**: - Track how well your trades align with the bias using the **Win/Loss Tracker**. This helps you refine your strategy by understanding which timeframes and biases lead to higher success rates. - For example, if you see a high number of **Buy Wins** and a low number of **Sell Wins**, you may decide to focus more on buying during bullish trends and avoid selling during bearish retracements. 4. **Track Your Period Performance**: - The indicator will automatically track your performance over the set period (Days, Weeks, Months). Use this data to adjust your approach and evaluate the effectiveness of your trading strategy. 5. **Position the Table**: - Customize the placement of the table on your chart based on your preferences. You can choose from options like **Top Left**, **Top Right**, **Bottom Left**, **Bottom Right**, or **Center** to keep the chart uncluttered. 6. **Adjust Settings**: - Modify the indicator settings according to your trading style. You can adjust the **Lookback Period**, **Number of Candles to Track**, and **Time Threshold** to match the pace of your trading. 7. **Use the Info Tooltip**: - Enable the **Info Tool** in the settings to understand how the Buy/Sell Wins and Losses are calculated. The tooltip provides a breakdown of how the indicator tracks price movements and calculates the success rate. **Conclusion:** The **ENIGMA Indicator** is designed to help traders make informed decisions by providing a clear view of the market bias and performance data. With the ability to track bias across multiple timeframes and evaluate your trading success, it can be a powerful tool for refining your trading strategies. Whether you're looking to focus on a single timeframe or analyze multiple timeframes for a stronger bias, the ENIGMA Indicator adapts to your needs, providing both real-time market insights and performance feedback.
Indicador Pine Script®
por Niko-picasso369
2
IB + MAG7 + EMA [midsu]# IB + MAG7 + EMA Indicator - Technical Documentation ## Overview This indicator combines three distinct analytical methodologies: Market Profile's Initial Balance concept for institutional-level price acceptance zones, weighted sector momentum tracking based on market capitalization, and exponential moving average trend analysis. It provides visual reference data without generating automated trading signals. --- ## 1. Initial Balance (IB) - Auction Market Theory Implementation ### Underlying Concept Initial Balance is derived from Market Profile theory, developed by J. Peter Steidlmayer and the Chicago Board of Trade. The concept recognizes that the first hour of trading establishes a value area that represents price acceptance by the majority of market participants. ### Calculation Methodology **IB Formation (Default: 9:30-10:30 AM EST)** ``` ib_high = highest(high) during IB period ib_low = lowest(low) during IB period ib_range = ib_high - ib_low ib_midpoint = (ib_high + ib_low) / 2 ``` **Extension Levels (Fibonacci-style projections)** ``` extension_up = ib_high + (ib_range × extension_percentage / 100) extension_down = ib_low - (ib_range × extension_percentage / 100) ``` Default extensions: 25%, 50%, 100% above and below IB **Range Day vs Trend Day Classification** The indicator uses a tolerance-based detection system: ``` tolerance = ib_range × (tolerance_percentage / 100) // Default: 5% During confirmation period (default 10:00-11:00 AM): - If high > (ib_high + tolerance): Classified as "Trend Day (Bullish)" - If low < (ib_low - tolerance): Classified as "Trend Day (Bearish)" - Otherwise: Classified as "Range Day" ``` **Statistical Analysis** The indicator calculates IB range as a percentage of price: ``` ib_range_pct = (ib_range / ib_low) × 100 ``` Classification thresholds: - < 0.3% = Narrow IB (trend day likely) - > 1.0% = Wide IB (range day likely) - 0.3% - 1.0% = Moderate (wait for confirmation) ### Why This Works - **First Hour Significance**: Institutional traders, market makers, and informed participants are most active during the opening hour, establishing the "true" value area - **Value Area Theory**: Price tends to either remain within the accepted value (80% of the time) or break out and continue trending (20% of the time) - **Extensions as Targets**: When breakouts occur, extensions based on IB range provide probabilistic targets based on volatility expansion --- ## 2. MAG7 Dashboard - Weighted Sector Momentum Analysis ### Underlying Concept The Magnificent 7 stocks (NVDA, AAPL, GOOGL, MSFT, AMZN, META, TSLA) represent approximately 30% of the S&P 500 and over 50% of the Nasdaq 100 by market capitalization. Their collective movement is a leading indicator for index direction due to their outsized influence on index calculations. ### Calculation Methodology **Step 1: Individual Stock % Change** For each stock on the current timeframe: ``` pct_change = ((current_close - previous_close) / previous_close) × 100 ``` **Step 2: Movement Filter (Signal Extraction)** ``` If pct_change > threshold (default 0.1%): signal = pct_change // Bullish contribution Else if pct_change < -threshold: signal = pct_change // Bearish contribution Else: signal = 0 // Neutral (noise filtered out) ``` **Step 3: Weighted Aggregation** Each stock is weighted by its current market cap percentage: ``` weights = weighted_bias = Σ(signal × weight ) / Σ(weights) ``` This produces a single value ranging typically from -2% to +2%, representing net sector momentum. **Step 4: Bias Strength Classification** ``` If weighted_bias > 0.70%: "Strong Bull" Else if weighted_bias > 0.30%: "Mild Bull" Else if weighted_bias < -0.70%: "Strong Bear" Else if weighted_bias < -0.30%: "Mild Bear" Else: "Neutral" ``` **Step 5: Consensus Counting** ``` bull_count = number of stocks where pct_change > threshold bear_count = number of stocks where pct_change < -threshold neutral_count = 7 - bull_count - bear_count ``` ### Why This Works - **Market Cap Weighting**: Matches how indexes are actually calculated, making this a proxy for index movement - **Leading vs Lagging**: Individual stock movements often lead index futures by seconds to minutes due to arbitrage lag - **Noise Filtering**: The threshold removes insignificant moves, focusing only on meaningful momentum - **Consensus Strength**: When 6-7 stocks align directionally, probability of sustained index movement increases significantly ### Price & Open Interest Gauge Sub-Component **Calculation Logic:** ``` price_ma = SMA(close, lookback_period) // Default: 14 bars price_rising = close > price_ma oi_proxy = volume × (high - low) // Volatility-weighted volume oi_ma = SMA(oi_proxy, lookback_period) oi_rising = oi_proxy > (oi_ma × sensitivity) // Default sensitivity: 1.0 ``` **Four-State Classification:** 1. Price UP + OI UP = Strong Long (new money entering long positions) 2. Price UP + OI DOWN = Caution Long (short covering, not new longs) 3. Price DOWN + OI UP = Strong Short (new money entering short positions) 4. Price DOWN + OI DOWN = Caution Short (long liquidation, not new shorts) **Why This Works:** - Based on commodity futures analysis principles - Rising OI with price confirms directional conviction - Falling OI with price suggests temporary/weak move - Helps distinguish sustainable moves from noise --- ## 3. Dual EMA System - Exponential Trend Analysis ### Underlying Concept Exponential Moving Averages weight recent price action more heavily than older data, making them more responsive to trend changes than Simple Moving Averages while still filtering noise. ### Calculation Methodology **EMA Formula:** ``` EMA(today) = (Close(today) × multiplier) + (EMA(yesterday) × (1 - multiplier)) Where: multiplier = 2 / (period + 1) ``` **Default Settings:** - EMA 1 (Fast): 21-period - EMA 2 (Slow): 50-period **Color Logic:** ``` For each EMA: If close >= EMA: color = green (bullish regime) If close < EMA: color = red (bearish regime) ``` **Bar Coloring (Optional):** Uses EMA 1 as the reference: ``` If close >= EMA1: bar_color = lime If close < EMA1: bar_color = red ``` ### Why This Works - **21-Period**: Represents approximately 1 month of trading (21 trading days), capturing intermediate-term trend - **50-Period**: Represents approximately 2.5 months of trading, capturing longer-term trend - **Dynamic Support/Resistance**: EMAs act as dynamic support in uptrends and resistance in downtrends - **Crossovers**: When fast EMA crosses slow EMA, it signals potential trend change (though this indicator doesn't generate signals, users can observe these manually) - **Exponential Weighting**: Recent price action matters more, making EMAs more responsive to emerging trends than SMAs ### Mathematical Advantage of EMAs The exponential smoothing reduces lag while maintaining smoothness: - SMA gives equal weight to all periods (lag = period / 2) - EMA gives 86% weight to most recent 2/3 of the period (lag ≈ (period - 1) / 2) - Result: 21 EMA responds almost as fast as 14 SMA but with smoother line --- ## Integration & Synergy ### How Components Work Together **1. IB Provides Context** - Establishes key price levels (support/resistance) - Identifies day type (range vs trend) - Sets volatility expectations via IB range **2. MAG7 Provides Directional Bias** - Confirms or contradicts IB breakout attempts - Shows sector-level conviction - Indicates index futures direction **3. EMAs Provide Trend Confirmation** - Shows if current move aligns with intermediate/longer-term trend - Provides dynamic entry/exit reference points - Confirms or contradicts IB/MAG7 signals **Example of Confluence:** - IB breaks out bullishly (price > IB high) - MAG7 shows 6/7 stocks green with +0.6% weighted bias - Price is above both EMAs (EMA 1 > EMA 2, both green) - This confluence suggests high-probability bullish continuation **Example of Divergence (Warning Sign):** - IB breaks out bullishly - MAG7 shows 5/7 stocks red with -0.4% weighted bias - Price below EMA 1, attempting to cross EMA 2 - This divergence suggests false breakout risk --- ## Limitations & Considerations ### Initial Balance Limitations - Most effective on liquid instruments (ES, NQ, SPY, QQQ) - Requires clear market open (less effective on 24-hour markets like crypto) - IB may be less meaningful on very low or very high volatility days - Works best on intraday timeframes (1min - 60min) ### MAG7 Limitations - Weights become outdated as market caps change (requires monthly manual updates) - Most relevant for tech-focused traders (Nasdaq, QQQ) - Less relevant if trading unrelated sectors (energy, financials) - Relies on correlation between individual stocks and indexes remaining stable ### EMA Limitations - Lagging indicator by nature (responds to price, doesn't predict) - Can produce whipsaws in sideways/choppy markets - Fixed periods may not suit all market conditions - Crossovers can be delayed in fast-moving markets ### General Limitations - **Visual Reference Only**: Does not generate automated entry/exit signals - **Requires User Interpretation**: Confluence of indicators requires trader judgment - **Historical Data**: All calculations based on closed bars (no predictive element) - **Market Hours Dependent**: IB designed for standard US market hours --- ## Unique Value Proposition ### What Makes This Different **1. Multi-Method Confluence** Most indicators use a single methodology. This combines three proven, independent methods: - Auction theory (IB) - Market cap-weighted momentum (MAG7) - Exponential trend analysis (EMAs) **2. Institutional-Level Data** - IB used by professional floor traders for decades - MAG7 weights match actual index composition - Not arbitrary or curve-fitted parameters **3. Adaptable Without Optimization** - Works on any timeframe without parameter changes - IB adapts to current day's volatility - MAG7 reflects current market structure - EMAs scale with timeframe --- ## Recommended Usage ### For Day Traders - Use on 3min, 5min or 15min charts - Focus on IB breakouts confirmed by MAG7 - Use EMAs for entry timing within IB-defined moves ### For Swing Traders - Use on 30min, 1H or Daily charts - Focus on MAG7 weighted bias for overall direction - Use IB as key support/resistance zones - Use EMAs for trend confirmation ### For Educational Purposes - Study how IB forms and how market respects/rejects these levels - Observe correlation between MAG7 bias and index movement - Learn dynamic support/resistance concepts via EMAs - Understand market structure and institutional behavior --- **Summary**: This indicator provides three layers of market analysis—institutional price acceptance zones (IB), sector momentum (MAG7), and trend direction (EMAs)—allowing traders to make informed decisions based on confluence of multiple proven methodologies rather than relying on a single indicator.
Indicador Pine Script®
por midst
H2 AlgoH2 Algo – Adaptive Market Structure Execution Engine (ES-Optimized) H2 Algo is a professional-grade market-structure and volatility-adaptive execution framework, purpose-built for E-mini S&P 500 (ES) futures on the 3-minute timeframe. It is designed for systematic intraday traders who prioritize non-repainting signals, regime awareness, and strict risk governance over indicator stacking. This is not a single indicator. H2 Algo is a multi-layer execution engine where trend, volatility, momentum, liquidity, and risk modules interact through a unified decision pipeline H2-Algo . 🔍 Core Philosophy Trade structure, not noise. Scale aggression when conditions expand. Defend capital when markets compress. H2 Algo dynamically adapts between trend expansion, mean reversion, and choppy/range-bound conditions, ensuring execution logic remains forward-safe and bar-close validated. 🧠 Core Components 1️⃣ H2 Market Structure Engine Zero-Lag EMA (ZLEMA)–based adaptive trend baseline ATR-normalized dynamic upper & lower structure bands Slope-based trend angle detection (trend strength & exhaustion) Fully bar-close confirmed (non-repainting) 2️⃣ Volatility & Regime Detection ATR normalization & Donchian range expansion tracking ADX percentile & slope-based momentum confirmation Choppiness, KER (Efficiency Ratio), and FDI (Fractal Dimension Index) filters Automatic suppression during low-quality or compressed regimes 3️⃣ Liquidity & Volume Intelligence Z-Score volume & candle expansion detection VWAP deviation & mean-reversion awareness Institutional-style rejection patterns (strong wicks, absorption candles) Specialized handling for open volatility & pre-market conditions ⚙️ Execution Logic H2 Algo combines trend-continuation, structure re-entry, and reversal-at-extremes logic, including: Trend continuation after pullbacks VWAP reversion with volatility confirmation Donchian range break & reclaim entries High-conviction candle + volume expansion triggers Defensive reversal logic after stop-outs (optional Quick-Reverse) Each entry is tagged with a unique execution code (e.g., LCR, SCV, LBB, SBM), enabling deep post-trade analytics and performance attribution H2-Algo . 🛡️ Risk-First Architecture Fixed + adaptive ATR-based stop-loss logic Dynamic take-profit adjustment during range compression Intelligent trailing stop based on peak unrealized profit Daily max-loss & max-profit enforcement Friday & overnight exposure control Profit stagnation and choppy-day exit protection Risk logic is enforced before entries, not after. 🔄 Hybrid Strategy + Indicator Design This script can be used in two modes: Indicator Mode → discretionary execution with visual structure, zones, and signals Strategy Mode → full TradingView backtesting with identical execution logic There is no logic divergence between modes. 🕒 Optimized Usage ✔ Instrument: ES (E-mini S&P 500) ✔ Timeframe: 3-Minute ✔ Session: RTH-focused (Chicago time) ✔ Style: Intraday scalping → short swing While H2 Algo may function on other indices, parameters and execution flow are explicitly tuned for ES microstructure on 3-minute candles. 🚫 Non-Repainting & Data Integrity No look-ahead bias No future bar references All signals confirmed at bar close Session-aware VWAP and daily resets Forward-walk-safe regime logic 📊 Who This Is For ✔ ES futures traders ✔ Systematic intraday traders ✔ Traders who value risk control over signal frequency ✔ Users who analyze performance by entry behavior, not just net PnL ⚠️ Disclaimer This script is a research and execution framework, not financial advice. Always forward-test and adapt risk parameters to your own tolerance and execution environment. Author: H2 Algo Version: v6 Execution Philosophy: Adapt to structure. Defend capital. Let expansion pay.
Estratégia Pine Script®
por gitpush
Context Bundle | VWAP / EMA / Session HighLow (v6) 📌 0DTE Context Bundle (v6) **VWAP • EMA Cloud • Session High/Low (NY / London / Asia) The **0DTE Context Bundle** is a *decision-making overlay*, not a signal spam indicator. It’s designed to help traders clearly see **value, trend, and liquidity levels** across **New York, London, and Asia sessions** — all in one clean, customizable tool. Built for **NQ, ES, Gold, and FX pairs**, with a focus on **5–15-minute execution charts**. --- ## 🔹 What This Indicator Shows ### ✅ VWAP + ATR Bands * Session VWAP (fair value) * ATR-based extension bands (1x / 2x) * Helps identify **overextension, mean reversion zones, and trend pullbacks** ### ✅ EMA 9 / 21 Cloud * Visual trend and momentum filter * Custom colors + opacity * Identifies **trend continuation vs chop** ### ✅ Session High / Low Levels * **New York RTH** * **London** * **Asia (midnight-safe)** * Optional previous session highs/lows * Adjustable line styles, widths, colors, and extensions ### ✅ Anchored VWAP (Optional) * Reset by: * Daily * NY session start * London session start * Asia session start * Useful for tracking **session-specific value shifts** --- ## 🔹 How Traders Use It This indicator is meant to answer: * *Are we trading at value or extension?* * *Is the market trending or rotating?* * *Where is liquidity likely sitting right now?* Common use cases: * Trend pullbacks into VWAP or EMA cloud * Reversal setups at session highs/lows * Session breakout + retest confirmation * Overnight context for London and Asia sessions --- ## 🔹 Customization & Flexibility Every component can be toggled and styled: * Colors, widths, line styles * Cloud up/down colors + opacity * Session visibility and extensions * VWAP band multipliers and ATR length Members can adapt it to **their own style**, market, and timeframe. --- ## ⚠️ Disclaimer This indicator is provided for **educational and informational purposes only**. It does **not** provide financial advice or trade signals. Always manage risk and confirm entries with your own strategy.
Indicador Pine Script®
por TradeswithB
Dragon Smart Timing (Trend Analysis)Introduction Dragon Smart Timing is a comprehensive "Clean Chart" trading system designed for trend followers who prefer a minimalist workspace. Instead of cluttering your chart with multiple moving averages and noisy signals, this indicator consolidates complex market data into a sleek, real-time Neon Dashboard. The system identifies high-probability Pullback Entries within a strong trend and includes a built-in Trade Management Assistant to help you decide when to Hold, Take Profit, or Stop Loss. 1. 🛠 How It Works (The 4-Pillar Logic) The system scans for a specific "Confluence" of 4 conditions. An "Entry Now" signal is triggered only when ALL of the following are met: Trend Filter (The Safety Guard): Price must be ABOVE the EMA 200. This ensures you only trade in the direction of the long-term trend, avoiding counter-trend risks. Momentum Alignment: Short-term trends must be healthy (EMA 21 > EMA 50 > EMA 100). Smart Pullback (RSI): RSI (14) must dip into the "Golden Zone" (40 - 55) and bounce upward. We buy the dip, not the top. Volume Confirmation: Validates the move with a Volume Spike (> 1.5x Average Volume). 2. 🤖 Trade Management Assistant Unlike standard indicators that leave you guessing after the entry, Dragon Smart Timing tracks the trade for you: 🐲 Entry Now: Signal to open a long position. ✊ Holding...: The system recognizes an active trade and monitors price action. 💰 Take Profit: Triggered when the price closes below the EMA 21, signaling momentum weakness. 🛑 Stop Loss: Triggered if the price drops 7% below your entry price to protect capital. 3. 🖥 The Neon Dashboard Trend: Displays "Strong Up", "Aligned", or "Below EMA200". RSI / Vol: Shows real-time values without clutter. Action: The most important row. It lights up in Neon Green (Entry), Orange (Take Profit), or Red (Stop Loss). ⚙️ Settings Trend Filter: Adjustable EMA 200 (Turn it into EMA 89 or 100 depending on your style). Dashboard: Fully customizable position (Top/Bottom/Center) and size to fit your screen. Risk Parameters: Adjustable Stop Loss % and Volume Multipliers. ⚠️ Risk Disclaimer This script is for educational purposes only and does not constitute financial advice. Trading involves a high degree of risk. Past performance is not indicative of future results.
Indicador Pine Script®
por TieuLongFX
Major Crypto Relative Strength Portfolio System Majors RSPS - Relative Strength Portfolio System for Major Cryptocurrencies Overview Majors RSPS (Relative Strength Portfolio System) is an advanced portfolio allocation indicator that combines relative strength analysis, trend consensus, and macro risk factors to dynamically allocate capital across major cryptocurrency assets. The system leverages the NormalizedIndicators Library to evaluate both absolute trends and relative performance, creating an adaptive portfolio that automatically adjusts exposure based on market conditions. This indicator is designed for portfolio managers, asset allocators, and systematic traders who want a data-driven approach to cryptocurrency portfolio construction with automatic rebalancing signals. 🎯 Core Concept What is RSPS? RSPS (Relative Strength Portfolio System) evaluates each asset on two key dimensions: Relative Strength: How is the asset performing compared to other major cryptocurrencies? Absolute Trend: Is the asset itself in a bullish trend? Assets that show both strong relative performance AND positive absolute trends receive higher allocations. Weak performers are automatically filtered out, with capital reallocated to cash or stronger assets. Dual-Layer Architecture Layer 1: Majors Portfolio (Orange Zone) Evaluates 14 major cryptocurrency assets Calculates relative strength against all other majors Applies trend filters to ensure absolute momentum Dynamically allocates capital based on comparative strength Layer 2: Cash/Risk Position (Navy Zone) Evaluates macro risk factors and market conditions Determines optimal cash allocation Acts as a risk-off mechanism during adverse conditions Provides downside protection through dynamic cash holdings 📊 Tracked Assets Major Cryptocurrencies (14 Assets) BTC - Bitcoin (Benchmark L1) ETH - Ethereum (Smart Contract L1) SOL - Solana (High-Performance L1) SUI - Sui (Move-Based L1) TRX - Tron (Payment-Focused L1) BNB - Binance Coin (Exchange L1) XRP - Ripple (Payment Network) FTM - Fantom (DeFi L1) CELO - Celo (Mobile-First L1) TAO - Bittensor (AI Network) HYPE - Hyperliquid (DeFi Exchange) HBAR - Hedera (Enterprise L1) ADA - Cardano (Research-Driven L1) THETA - Theta (Video Network) 🔧 How It Works Step 1: Relative Strength Calculation For each asset, the system calculates relative strength by: RSPS Score = Average of: - Asset/BTC trend consensus - Asset/ETH trend consensus - Asset/SOL trend consensus - Asset/SUI trend consensus - ... (all 14 pairs) - Asset's absolute trend consensus Key Logic: Each pair is evaluated using the eth_4d_cal() calibration from NormalizedIndicators If an asset's absolute trend is extremely weak (≤ 0.1), it receives a penalty score (-0.5) Otherwise, it gets the average of all its relative strength comparisons Step 2: Trend Filtering Assets must pass a trend filter to receive allocation: Trend Score = Average of: - Asset/BTC trend (filtered for positivity) - Asset/ETH trend (filtered for positivity) - Asset's absolute trend (filtered for positivity) Only positive values contribute to the trend score, ensuring bearish assets don't receive allocation. Step 3: Portfolio Allocation Capital is allocated proportionally based on filtered RSPS scores: Asset Allocation % = (Asset's Filtered RSPS Score / Sum of All Filtered Scores) × Main Portfolio % Example: SOL filtered score: 0.6 BTC filtered score: 0.4 All others: 0 Total: 1.0 SOL receives: (0.6 / 1.0) × Main% = 60% of main portfolio BTC receives: (0.4 / 1.0) × Main% = 40% of main portfolio Step 4: Cash/Risk Allocation The system evaluates macro conditions across 6 factors: Inverse Major Crypto Trends (40% weight) When BTC, ETH, SOL, SUI, DOGE, etc. trend down → Cash allocation increases Evaluates total market cap trends (TOTAL, TOTAL2, OTHERS) Stablecoin Dominance (10% weight) USDC dominance vs. major crypto dominances Higher stablecoin dominance → Higher cash allocation MVRV Ratios (10% weight) BTC and ETH Market Value to Realized Value High MVRV (overvaluation) → Higher cash allocation BTC/ETH Ratio (15% weight) Relative performance between two market leaders Indicates market phase (BTC dominance vs. alt season) Active Address Ratios (5% weight) USDC active addresses vs. BTC/ETH active addresses Network activity comparison Macro Indicators (15% weight) Global currency circulation (USD, EUR, CNY, JPY) Treasury yield curve (10Y-2Y) High yield spreads Central bank balance sheets and money supply Cash Allocation Formula: Cash % = (Sum of Risk Factors × 0.5) / (Risk Factors + Majors TPI) When risk factors are elevated, cash allocation increases, reducing exposure to volatile assets. 📈 Visual Components Orange Zone (Majors Portfolio) Fill: Light orange area showing aggregate portfolio strength Line: Average trend power index (TPI) of allocated assets Baseline: 0 level (neutral) Interpretation: Above 0: Bullish allocation environment Rising: Strengthening portfolio momentum Falling: Weakening portfolio momentum Below 0: No allocation (100% cash) Navy Zone (Cash Position) Fill: Navy blue area showing cash allocation strength Line: Risk-adjusted cash allocation signal Baseline: 0 level Interpretation: Higher navy zone: Elevated risk-off signal → More cash Lower navy zone: Risk-on environment → Less cash Zero: No cash allocation (100% invested) Performance Line (Orange/Blue) Orange: Main portfolio allocation dominant (risk-on mode) Blue: Cash allocation dominant (risk-off mode) Tracks: Cumulative portfolio returns with dynamic rebalancing Allocation Table (Bottom Left) Shows real-time portfolio composition: ColumnDescriptionAssetCryptocurrency nameRSPS ValuePercentage allocation (of main portfolio)CashDollar amount (if enabled) Color Coding: Orange: Active allocation Gray: Weak signal (borderline) Blue: Cash position Missing: No allocation (filtered out) ⚙️ Settings & Configuration Required Setup Chart Symbol MUST USE: INDEX:BTCUSD or similar major crypto index Recommended Timeframe: 1D (Daily) or 4D (4-Day) Why: System needs price data for all 14 majors, BTC provides stable reference Hide Chart Candles For clean visualization: Right-click on chart Select "Hide Symbol" or set candle opacity to 0 This allows the indicator fills and table to be clearly visible User Inputs plot_table (Default: true) Enable/disable the allocation table Set to false if you only want the visual zones use_cash (Default: false) Enable portfolio dollar value calculations Shows actual dollar allocations per asset cash (Default: 100) Total portfolio size in dollars/currency units Used when use_cash is enabled Example: Set to 10000 for a $10,000 portfolio 💡 Interpretation Guide Entry Signals Strong Allocation Signal: ✓ Orange zone elevated (> 0.3) ✓ Navy zone low (< 0.2) ✓ Performance line orange ✓ Multiple assets in allocation table → Action: Deploy capital to allocated assets per table percentages Risk-Off Signal: ✓ Orange zone near zero ✓ Navy zone elevated (> 0.4) ✓ Performance line blue ✓ Few or no assets in table (high cash %) → Action: Reduce exposure, increase cash holdings Rebalancing Triggers Monitor the allocation table for changes: New assets appearing: Add to portfolio Assets disappearing: Remove from portfolio Percentage changes: Rebalance existing positions Cash % changes: Adjust overall exposure Market Regime Detection Risk-On (Bull Market): Orange zone high and rising Navy zone minimal Many assets allocated (8-12) High individual allocations (15-30% each) Risk-Off (Bear Market): Orange zone near zero or negative Navy zone elevated Few assets allocated (0-3) Cash allocation dominant (70-100%) Transition Phase: Both zones moderate Medium number of assets (4-7) Balanced cash/asset allocation (40-60%) 🎯 Trading Strategies Strategy 1: Pure RSPS Following 1. Check allocation table daily 2. Rebalance portfolio to match percentages 3. Follow cash allocation strictly 4. Review weekly, act on significant changes (>5%) Best For: Systematic portfolio managers, passive allocators Strategy 2: Threshold-Based Entry Rules: - Orange zone > 0.4 AND Navy zone < 0.3 - At least 5 assets in allocation table - Total non-cash allocation > 60% Exit Rules: - Orange zone < 0.1 OR Navy zone > 0.5 - Fewer than 3 assets allocated - Cash allocation > 70% Best For: Active traders wanting clear rules Strategy 3: Relative Strength Overlay 1. Use RSPS for broad allocation framework 2. Within allocated assets, overweight top 3 performers 3. Scale position sizes by RSPS score 4. Use individual asset charts for entry/exit timing Best For: Discretionary traders with portfolio focus Strategy 4: Risk-Adjusted Position Sizing For each allocated asset: Position Size = Base Position × (Asset's RSPS Score / Max RSPS Score) × (1 - Cash Allocation) Example: - $10,000 portfolio - SOL RSPS: 0.6 (highest) - BTC RSPS: 0.4 - Cash allocation: 30% SOL Size = $10,000 × (0.6/0.6) × (1-0.30) = $7,000 BTC Size = $10,000 × (0.4/0.6) × (1-0.30) = $4,667 Cash = $10,000 × 0.30 = $3,000 Best For: Risk-conscious allocators 📊 Advanced Usage Multi-Timeframe Confirmation Use on multiple timeframes for robust signals: 1D Chart: Tactical allocation (daily rebalancing) 4D Chart: Strategic allocation (weekly review) Strong Confirmation: - Both timeframes show same top 3 assets - Both show similar cash allocation levels - Orange zones aligned on both Weak/Conflicting: - Different top performers - Diverging cash allocations → Wait for alignment or use shorter timeframe Sector Rotation Analysis Group assets by type and watch rotation: L1 Dominance: BTC, ETH, SOL, SUI, ADA high → Layer 1 season Alt L1s: TRX, FTM, CELO rising → Alternative platform season Specialized: TAO, THETA, HYPE strong → Niche narrative season Payment/Stable: XRP, BNB allocation → Risk reduction phase Divergence Trading Bullish Divergence: Navy zone declining (less risk-off) Orange zone flat or slightly rising Few assets still allocated but strengthening → Early accumulation signal Bearish Divergence: Orange zone declining Navy zone rising Asset count decreasing in table → Distribution/exit signal Performance Tracking The performance line (overlay) shows cumulative strategy returns: Compare to BTC/ETH: Is RSPS outperforming? Drawdown analysis: How deep are pullbacks? Correlation: Does it track market or provide diversification? 🔬 Technical Details Data Sources Price Data: COINEX: Primary exchange for alt data CRYPTO: Alternative price feeds INDEX: Aggregated index prices (recommended for BTC) Macro Data: Dominance metrics (SUI.D, BTC.D, etc.) MVRV ratios (on-chain valuation) Active addresses (network activity) Global money supply and macro indicators Calculation Methodology RSPS Scoring: For each asset, calculate 14 relative trends (vs. all others) Calculate asset's absolute trend Average all 15 values Apply penalty filter for extremely weak trends (≤ 0.1) Trend Consensus: Uses eth_4d_cal() from NormalizedIndicators library Combines 8 normalized indicators per measurement Returns value from -1 (bearish) to +1 (bullish) Performance Calculation: Daily Return = Σ(Asset ROC × Asset Allocation) Cumulative Performance = Previous Perf × (1 + Daily Return / 100) Assumes perfect rebalancing and no slippage (theoretical performance). Filtering Logic filter() function: pinescriptfilter(input) => input >= 0 ? input : 0 This zero-floor filter ensures: Only positive trend values contribute to allocation Bearish assets receive 0 weight No short positions or inverse allocations Anti-Manipulation Safeguards Null Handling: All values wrapped in nz() to handle missing data Prevents calculation errors from data gaps Normalization: Allocations always sum to 100% Prevents over/under-allocation Conditional Logic: Assets need positive values on multiple metrics Single metric cannot drive allocation alone ⚠️ Important Considerations Required Timeframes 1D (Daily): Recommended for most users 4D (4-Day): More stable, fewer rebalances Other timeframes: Use at your own discretion, may require recalibration Data Requirements Needs INDEX:BTCUSD or equivalent major crypto symbol All 14 tracked assets must have available data Macro indicators require specific TradingView data feeds Rebalancing Frequency System provides daily allocation updates Practical rebalancing: Weekly or on significant changes (>10%) Consider transaction costs and tax implications Performance Notes Theoretical returns: No slippage, fees, or execution delays Backtest carefully: Validate on your specific market conditions Past performance: Does not guarantee future results Risk Warnings ⚠️ High Concentration Risk: May allocate heavily to 1-3 assets ⚠️ Volatility: Crypto markets are inherently volatile ⚠️ Liquidity: Some allocated assets may have lower liquidity ⚠️ Correlation: All assets correlated to BTC/ETH to some degree ⚠️ System Risk: Relies on continued availability of data feeds Not Financial Advice This indicator is a tool for analysis and research. It does not constitute: Investment advice Portfolio management services Trading recommendations Guaranteed returns Always perform your own due diligence and risk assessment. 🎓 Use Cases For Portfolio Managers Systematic allocation framework Objective rebalancing signals Risk-adjusted exposure management Performance tracking vs. benchmarks For Active Traders Identify strongest assets to focus trading on Gauge overall market regime (risk-on/off) Time entry/exit for portfolio shifts Complement technical analysis with allocation data For Institutional Allocators Quantitative portfolio construction Multi-asset exposure optimization Drawdown management through cash allocation Compliance-friendly systematic approach For Researchers Study relative strength dynamics in crypto markets Analyze correlation between majors Test macro factor impact on crypto allocations Develop derived strategies and signals 🔧 Setup Checklist ✅ Chart Configuration Set chart to INDEX:BTCUSD Set timeframe to 1D or 4D Hide chart candles for clean visualization Add indicator from library ✅ Indicator Settings Enable plot_table (see allocation table) Set use_cash if tracking dollar amounts Input your portfolio size in cash parameter ✅ Monitoring Setup Bookmark chart for daily review Set alerts for major allocation changes (optional) Create spreadsheet to track allocations (optional) Establish rebalancing schedule (weekly recommended) ✅ Validation Verify all 14 assets appear in table (when allocated) Check that percentages sum to ~100% Confirm performance line is tracking Test cash allocation calculation if enabled 📋 Quick Reference Signal Interpretation ConditionOrange ZoneNavy ZoneActionStrong BullHigh (>0.4)Low (<0.2)Full allocationModerate BullMid (0.2-0.4)Low-MidStandard allocationNeutralLow (0.1-0.2)Mid (0.3-0.4)Balanced allocationModerate BearVery Low (<0.1)Mid-HighReduce exposureStrong BearZero/NegativeHigh (>0.5)High cash/exit Rebalancing Thresholds Change TypeThresholdActionIndividual asset±5%Consider rebalanceIndividual asset±10%Strongly rebalanceCash allocation±10%Adjust exposureAsset entry/exitAnyAdd/remove position Color Legend Orange: Main portfolio strength/allocation Navy: Cash/risk-off allocation Blue text: Cash position in table Orange text: Active asset allocation Gray text: Weak/borderline allocation White: Headers and labels 🚀 Getting Started Beginner Path Add indicator to INDEX:BTCUSD daily chart Hide candles for clarity Enable plot_table to see allocations Check table daily, note top 3-5 assets Start with small allocation, observe behavior Gradually increase allocation as you gain confidence Intermediate Path Set up on both 1D and 4D charts Enable use_cash with your portfolio size Create tracking spreadsheet Implement weekly rebalancing schedule Monitor divergences between timeframes Compare performance to buy-and-hold BTC Advanced Path Modify code to add/remove tracked assets Adjust relative strength calculation methodology Customize cash allocation factors and weights Integrate with portfolio management platform Develop algorithmic rebalancing system Create alerts for specific allocation conditions 📖 Additional Resources Related Indicators NormalizedIndicators Library: Core calculation engine Individual asset trend indicators for deeper analysis Macro indicator dashboards for cash allocation factors Complementary Analysis On-chain metrics (MVRV, active addresses, etc.) Order book liquidity for execution planning Correlation matrices for diversification analysis Volatility indicators for position sizing Learning Materials Study relative strength portfolio theory Research tactical asset allocation strategies Understand crypto market cycles and phases Learn about risk management in volatile assets 🎯 Key Takeaways ✅ Systematic allocation across 14 major cryptocurrencies ✅ Dual-layer approach: Asset selection + Cash management ✅ Relative strength focused: Invests in comparatively strong assets ✅ Trend filtering: Only allocates to assets in positive trends ✅ Dynamic rebalancing: Automatically adjusts to market conditions ✅ Risk-managed: Increases cash during adverse conditions ✅ Transparent methodology: Clear calculation logic ✅ Practical visualization: Easy-to-read table and zones ✅ Performance tracking: See cumulative strategy returns ✅ Highly customizable: Adjust assets, weights, and factors 📋 License This code is subject to the Mozilla Public License 2.0 at mozilla.org Majors RSPS transforms complex multi-asset portfolio management into a systematic, data-driven process. By combining relative strength analysis with trend consensus and macro risk factors, it provides traders and portfolio managers with a robust framework for navigating cryptocurrency markets with discipline and objectivity.WiederholenClaude kann Fehler machen. Bitte überprüfen Sie die Antworten. Sonnet 4.5
Indicador Pine Script®
por Unicorpus
Flux-Tensor Singularity [ML/RL PRO]Flux-Tensor Singularity This version of the Flux-Tensor Singularity (FTS) represents a paradigm shift in technical analysis by treating price movement as a physical system governed by volume-weighted forces and volatility dynamics. Unlike traditional indicators that measure price change or momentum in isolation, FTS quantifies the complete energetic state of the market by fusing three fundamental dimensions: price displacement (delta_P), volume intensity (V), and local-to-global volatility ratio (gamma). The Physics-Inspired Foundation: The tensor calculation draws inspiration from general relativity and fluid dynamics, where massive objects (large volume) create curvature in spacetime (price action). The core formula: Raw Singularity = (ΔPrice × ln(Volume)) × γ² Where: • ΔPrice = close - close (directional force) • ln(Volume) = logarithmic volume compression (prevents extreme outliers) • γ (Gamma) = (ATR_local / ATR_global)² (volatility expansion coefficient) This raw value is then normalized to 0-100 range using the lookback period's extremes, creating a bounded oscillator that identifies critical density points—"singularities" where normal market behavior breaks down and explosive moves become probable. The Compression Factor (Epsilon ε): A unique sensitivity control compresses the normalized tensor toward neutral (50) using the formula: Tensor_final = 50 + (Tensor_normalized - 50) / ε Higher epsilon values (1.5-3.0) make threshold breaches rare and significant, while lower values (0.3-0.7) increase signal frequency. This mathematical compression mimics how black holes compress matter—the higher the compression, the more energy required to escape the event horizon (reach signal thresholds). Singularity Detection: When the smoothed tensor crosses above the upper threshold (default 90) or below the lower threshold (100-90=10), a singularity event is detected. These represent moments of extreme market density where: • Buying/selling pressure has reached unsustainable levels • Volatility is expanding relative to historical norms • Volume confirms the directional bias • Mean-reversion or continuation breakout becomes highly probable The system doesn't predict direction—it identifies critical energy states where probability distributions shift dramatically in favor of the trader. 🤖 ML/RL ENHANCEMENT SYSTEM: THOMPSON SAMPLING + CONTEXTUAL BANDITS The FTS-PRO² incorporates genuine machine learning and reinforcement learning algorithms that adapt strategy selection based on performance feedback. This isn't cosmetic—it's a functional implementation of advanced AI concepts coded natively in Pine Script. Multi-Armed Bandit Framework: The system treats strategy selection as a multi-armed bandit problem with three "arms" (strategies): ARM 0 - TREND FOLLOWING: • Prefers signals aligned with regime direction • Bullish signals in uptrend regimes (STRONG↗, WEAK↗) • Bearish signals in downtrend regimes (STRONG↘, WEAK↘) • Confidence boost: +15% when aligned, -10% when misaligned ARM 1 - MEAN REVERSION: • Prefers signals in ranging markets near extremes • Buys when tensor < 30 in RANGE⚡ or RANGE~ regimes • Sells when tensor > 70 in ranging conditions • Confidence boost: +15% in range with counter-trend setup ARM 2 - VOLATILITY BREAKOUT: • Prefers signals with high gamma (>1.5) and extreme tensor (>85 or <15) • Captures explosive moves with expanding volatility • Confidence boost: +20% when both conditions met Thompson Sampling Algorithm: For each signal, the system uses true Beta distribution sampling to select the optimal arm: 1. Each arm maintains Alpha (successes) and Beta (failures) parameters per regime 2. Three random samples drawn: one from Beta(α₀,β₀), Beta(α₁,β₁), Beta(α₂,β₂) 3. Highest sample wins and that arm's strategy applies 4. After trade outcome: - Win → Alpha += 1.0, reward += 1.0 - Loss → Beta += 1.0, reward -= 0.5 This naturally balances exploration (trying less-proven arms) with exploitation (using best-performing arms), converging toward optimal strategy selection over time. Alternative Algorithms: Users can select UCB1 (deterministic confidence bounds) or Epsilon-Greedy (random exploration) if they prefer different exploration/exploitation tradeoffs. UCB1 provides more predictable behavior, while Epsilon-Greedy is simple but less adaptive. Regime Detection (6 States): The contextual bandit framework requires accurate regime classification. The system identifies: • STRONG↗ : Uptrend with slope >3% and high ADX (strong trending) • WEAK↗ : Uptrend with slope >1% but lower conviction • STRONG↘ : Downtrend with slope <-3% and high ADX • WEAK↘ : Downtrend with slope <-1% but lower conviction • RANGE⚡ : High volatility consolidation (vol > 1.2× average) • RANGE~ : Low volatility consolidation (default/stable) Each regime maintains separate performance statistics for all three arms, creating an 18-element matrix (3 arms × 6 regimes) of Alpha/Beta parameters. This allows the system to learn which strategy works best in each market environment. 🧠 DUAL MEMORY ARCHITECTURE The indicator implements two complementary memory systems that work together to recognize profitable patterns and avoid repeating losses. Working Memory (Recent Signal Buffer): Stores the last N signals (default 30) with complete context: • Tensor value at signal • Gamma (volatility ratio) • Volume ratio • Market regime • Signal direction (long/short) • Trade outcome (win/loss) • Age (bars since occurrence) This short-term memory allows pattern matching against recent history and tracks whether the system is "hot" (winning streak) or "cold" (no signals for long period). Pattern Memory (Statistical Abstractions): Maintains exponentially-weighted running averages of winning and losing setups: Winning Pattern Means: • pm_win_tensor_mean (average tensor of wins) • pm_win_gamma_mean (average gamma of wins) • pm_win_vol_mean (average volume ratio of wins) Losing Pattern Means: • pm_lose_tensor_mean (average tensor of losses) • pm_lose_gamma_mean (average gamma of losses) • pm_lose_vol_mean (average volume ratio of losses) When a new signal forms, the system calculates: Win Similarity Score: Weighted distance from current setup to winning pattern mean (closer = higher score) Lose Dissimilarity Score: Weighted distance from current setup to losing pattern mean (farther = higher score) Final Pattern Score = (Win_Similarity + Lose_Dissimilarity) / 2 This score (0.0 to 1.0) feeds into ML confidence calculation with 15% weight. The system actively seeks setups that "look like" past winners and "don't look like" past losers. Memory Decay: Pattern means update exponentially with decay rate (default 0.95): New_Mean = Old_Mean × 0.95 + New_Value × 0.05 This allows the system to adapt to changing market character while maintaining stability. Faster decay (0.80-0.90) adapts quickly but may overfit to recent noise. Slower decay (0.95-0.99) provides stability but adapts slowly to regime changes. 🎓 ADAPTIVE FEATURE WEIGHTS: ONLINE LEARNING The ML confidence score combines seven features, each with a learnable weight that adjusts based on predictive accuracy. The Seven Features: 1. Overall Win Rate (15% initial) : System-wide historical performance 2. Regime Win Rate (20% initial) : Performance in current market regime 3. Score Strength (15% initial) : Bull vs bear score differential 4. Volume Strength (15% initial) : Volume ratio normalized to 0-1 5. Pattern Memory (15% initial) : Similarity to winning patterns 6. MTF Confluence (10% initial) : Higher timeframe alignment 7. Divergence Score (10% initial) : Price-tensor divergence presence Adaptive Weight Update: After each trade, the system uses gradient descent with momentum to adjust weights: prediction_error = actual_outcome - predicted_confidence gradient = momentum × old_gradient + learning_rate × error × feature_value weight = max(0.05, weight + gradient × 0.01) Then weights are normalized to sum to 1.0. Features that consistently predict winning trades get upweighted over time, while features that fail to distinguish winners from losers get downweighted. The momentum term (default 0.9) smooths the gradient to prevent oscillation and overfitting. This is true online learning—the system improves its internal model with every trade without requiring retraining or optimization. Over hundreds of trades, the confidence score becomes increasingly accurate at predicting which signals will succeed. ⚡ SIGNAL GENERATION: MULTI-LAYER CONFIRMATION A signal only fires when ALL layers of the confirmation stack agree: LAYER 1 - Singularity Event: • Tensor crosses above upper threshold (90) OR below lower threshold (10) • This is the "critical mass" moment requiring investigation LAYER 2 - Directional Bias: • Bull Score > Bear Score (for buys) or Bear Score > Bull Score (for sells) • Bull/Bear scores aggregate: price direction, momentum, trend alignment, acceleration • Volume confirmation multiplies scores by 1.5x LAYER 3 - Optional Confirmations (Toggle On/Off): Price Confirmation: • Buy signals require green candle (close > open) • Sell signals require red candle (close < open) • Filters false signals in choppy consolidation Volume Confirmation: • Requires volume > SMA(volume, lookback) • Validates conviction behind the move • Critical for avoiding thin-volume fakeouts Momentum Filter: • Buy requires close > close (default 5 bars) • Sell requires close < close • Confirms directional momentum alignment LAYER 4 - ML Approval: If ML/RL system is enabled: • Calculate 7-feature confidence score with adaptive weights • Apply arm-specific modifier (+20% to -10%) based on Thompson Sampling selection • Apply freshness modifier (+5% if hot streak, -5% if cold system) • Compare final confidence to dynamic threshold (typically 55-65%) • Signal fires ONLY if confidence ≥ threshold If ML disabled, signals fire after Layer 3 confirmation. Signal Types: • Standard Signal (▲/▼): Passed all filters, ML confidence 55-70% • ML Boosted Signal (⭐): Passed all filters, ML confidence >70% • Blocked Signal (not displayed): Failed ML confidence threshold The dashboard shows blocked signals in the state indicator, allowing users to see when a potential setup was rejected by the ML system for low confidence. 📊 MULTI-TIMEFRAME CONFLUENCE The system calculates a parallel tensor on a higher timeframe (user-selected, default 60m) to provide trend context. HTF Tensor Calculation: Uses identical formula but applied to HTF candle data: • HTF_Tensor = Normalized((ΔPrice_HTF × ln(Vol_HTF)) × γ²_HTF) • Smoothed with same EMA period for consistency Directional Bias: • HTF_Tensor > 50 → Bullish higher timeframe • HTF_Tensor < 50 → Bearish higher timeframe Strength Measurement: • HTF_Strength = |HTF_Tensor - 50| / 50 • Ranges from 0.0 (neutral) to 1.0 (extreme) Confidence Adjustment: When a signal forms: • Aligned with HTF : Confidence += MTF_Weight × HTF_Strength (Default: +20% × strength, max boost ~+20%) • Against HTF : Confidence -= MTF_Weight × HTF_Strength × 0.6 (Default: -20% × strength × 0.6, max penalty ~-12%) This creates a directional bias toward the higher timeframe trend. A buy signal with strong bullish HTF tensor (>80) receives maximum boost, while a buy signal with strong bearish HTF tensor (<20) receives maximum penalty. Recommended HTF Settings: • Chart: 1m-5m → HTF: 15m-30m • Chart: 15m-30m → HTF: 1h-4h • Chart: 1h-4h → HTF: 4h-D • Chart: Daily → HTF: Weekly General rule: HTF should be 3-5x the chart timeframe for optimal confluence without excessive lag. 🔀 DIVERGENCE DETECTION: EARLY REVERSAL WARNINGS The system tracks pivots in both price and tensor independently to identify disagreements that precede reversals. Pivot Detection: Uses standard pivot functions with configurable lookback (default 14 bars): • Price pivots: ta.pivothigh(high) and ta.pivotlow(low) • Tensor pivots: ta.pivothigh(tensor) and ta.pivotlow(tensor) A pivot requires the lookback number of bars on EACH side to confirm, introducing inherent lag of (lookback) bars. Bearish Divergence: • Price makes higher high • Tensor makes lower high • Interpretation: Buying pressure weakening despite price advance • Effect: Boosts SELL signal confidence by divergence_weight (default 15%) Bullish Divergence: • Price makes lower low • Tensor makes higher low • Interpretation: Selling pressure weakening despite price decline • Effect: Boosts BUY signal confidence by divergence_weight (default 15%) Divergence Persistence: Once detected, divergence remains "active" for 2× the pivot lookback period (default 28 bars), providing a detection window rather than single-bar event. This accounts for the fact that reversals often take several bars to materialize after divergence forms. Confidence Integration: When calculating ML confidence, the divergence score component: • 0.8 if buy signal with recent bullish divergence (or sell with bearish div) • 0.2 if buy signal with recent bearish divergence (opposing signal) • 0.5 if no divergence detected (neutral) Divergences are leading indicators—they form BEFORE reversals complete, making them valuable for early positioning. ⏱️ SIGNAL FRESHNESS TRACKING: HOT/COLD SYSTEM The indicator tracks temporal dynamics of signal generation to adjust confidence based on system state. Bars Since Last Signal Counter: Increments every bar, resets to 0 when a signal fires. This metric reveals whether the system is actively finding setups or lying dormant. Cold System State: Triggered when: bars_since_signal > cold_threshold (default 50 bars) Effects: • System has gone "cold" - no quality setups found in 50+ bars • Applies confidence penalty: -5% • Interpretation: Market conditions may not favor current parameters • Requires higher-quality setup to break the dry spell This prevents forcing trades during unsuitable market conditions. Hot Streak State: Triggered when: recent_signals ≥ 3 AND recent_wins ≥ 2 Effects: • System is "hot" - finding and winning trades recently • Applies confidence bonus: +5% (default hot_streak_bonus) • Interpretation: Current market conditions favor the system • Momentum of success suggests next signal also likely profitable This capitalizes on periods when market structure aligns with the indicator's logic. Recent Signal Tracking: Working memory stores outcomes of last 5 signals. When 3+ winners occur in this window, hot streak activates. After 5 signals, the counter resets and tracking restarts. This creates rolling evaluation of recent performance. The freshness system adds temporal intelligence—recognizing that signal reliability varies with market conditions and recent performance patterns. 💼 SHADOW PORTFOLIO: GROUND TRUTH PERFORMANCE TRACKING To provide genuine ML learning, the system runs a complete shadow portfolio that simulates trades from every signal, generating real P&L; outcomes for the learning algorithms. Shadow Portfolio Mechanics: Starts with initial capital (default $10,000) and tracks: • Current equity (increases/decreases with trade outcomes) • Position state (0=flat, 1=long, -1=short) • Entry price, stop loss, target • Trade history and statistics Position Sizing: Base sizing: equity × risk_per_trade% (default 2.0%) With dynamic sizing enabled: • Size multiplier = 0.5 + ML_confidence • High confidence (0.80) → 1.3× base size • Low confidence (0.55) → 1.05× base size Example: $10,000 equity, 2% risk, 80% confidence: • Impact: $10,000 × 2% × 1.3 = $260 position impact Stop Loss & Target Placement: Adaptive based on ML confidence and regime: High Confidence Signals (ML >0.7): • Tighter stops: 1.5× ATR • Larger targets: 4.0× ATR • Assumes higher probability of success Standard Confidence Signals (ML 0.55-0.7): • Standard stops: 2.0× ATR • Standard targets: 3.0× ATR Ranging Regimes (RANGE⚡/RANGE~): • Tighter setup: 1.5× ATR stop, 2.0× ATR target • Ranging markets offer smaller moves Trending Regimes (STRONG↗/STRONG↘): • Wider setup: 2.5× ATR stop, 5.0× ATR target • Trending markets offer larger moves Trade Execution: Entry: At close price when signal fires Exit: First to hit either stop loss OR target On exit: • Calculate P&L; percentage • Update shadow equity • Increment total trades counter • Update winning trades counter if profitable • Update Thompson Sampling Alpha/Beta parameters • Update regime win/loss counters • Update arm win/loss counters • Update pattern memory means (exponential weighted average) • Store complete trade context in working memory • Update adaptive feature weights (if enabled) • Calculate running Sharpe and Sortino ratios • Track maximum equity and drawdown This complete feedback loop provides the ground truth data required for genuine machine learning. 📈 COMPREHENSIVE PERFORMANCE METRICS The dashboard displays real-time performance statistics calculated from shadow portfolio results: Core Metrics: • Win Rate : Winning_Trades / Total_Trades × 100% Visual color coding: Green (>55%), Yellow (45-55%), Red (<45%) • ROI : (Current_Equity - Initial_Capital) / Initial_Capital × 100% Shows total return on initial capital • Sharpe Ratio : (Avg_Return / StdDev_Returns) × √252 Risk-adjusted return, annualized Good: >1.5, Acceptable: >0.5, Poor: <0.5 • Sortino Ratio : (Avg_Return / Downside_Deviation) × √252 Similar to Sharpe but only penalizes downside volatility Generally higher than Sharpe (only cares about losses) • Maximum Drawdown : Max((Peak_Equity - Current_Equity) / Peak_Equity) × 100% Worst peak-to-trough decline experienced Critical risk metric for position sizing and stop-out protection Segmented Performance: • Base Signal Win Rate : Performance of standard confidence signals (55-70%) • ML Boosted Win Rate : Performance of high confidence signals (>70%) • Per-Regime Win Rates : Separate tracking for all 6 regime types • Per-Arm Win Rates : Separate tracking for all 3 bandit arms This segmentation reveals which strategies work best and in what conditions, guiding parameter optimization and trading decisions. 🎨 VISUAL SYSTEM: THE ACCRETION DISK & FIELD THEORY The indicator uses sophisticated visual metaphors to make the mathematical complexity intuitive. Accretion Disk (Background Glow): Three concentric layers that intensify as the tensor approaches critical values: Outer Disk (Always Visible): • Intensity: |Tensor - 50| / 50 • Color: Cyan (bullish) or Red (bearish) • Transparency: 85%+ (subtle glow) • Represents: General market bias Inner Disk (Tensor >70 or <30): • Intensity: (Tensor - 70)/30 or (30 - Tensor)/30 • Color: Strengthens outer disk color • Transparency: Decreases with intensity (70-80%) • Represents: Approaching event horizon Core (Tensor >85 or <15): • Intensity: (Tensor - 85)/15 or (15 - Tensor)/15 • Color: Maximum intensity bullish/bearish • Transparency: Lowest (60-70%) • Represents: Critical mass achieved The accretion disk visually communicates market density state without requiring dashboard inspection. Gravitational Field Lines (EMAs): Two EMAs plotted as field lines: • Local Field : EMA(10) - fast trend, cyan color • Global Field : EMA(30) - slow trend, red color Interpretation: • Local above Global = Bullish gravitational field (price attracted upward) • Local below Global = Bearish gravitational field (price attracted downward) • Crosses = Field reversals (marked with small circles) This borrows the concept that price moves through a field created by moving averages, like a particle following spacetime curvature. Singularity Diamonds: Small diamond markers when tensor crosses thresholds BUT full signal doesn't fire: • Gold/yellow diamonds above/below bar • Indicates: "Near miss" - singularity detected but missing confirmation • Useful for: Understanding why signals didn't fire, seeing potential setups Energy Particles: Tiny dots when volume >2× average: • Represents: "Matter ejection" from high volume events • Position: Below bar if bullish candle, above if bearish • Indicates: High energy events that may drive future moves Event Horizon Flash: Background flash in gold when ANY singularity event occurs: • Alerts to critical density point reached • Appears even without full signal confirmation • Creates visual alert to monitor closely Signal Background Flash: Background flash in signal color when confirmed signal fires: • Cyan for BUY signals • Red for SELL signals • Maximum visual emphasis for actual entry points 🎯 SIGNAL DISPLAY & TOOLTIPS Confirmed signals display with rich information: Standard Signals (55-70% confidence): • BUY : ▲ symbol below bar in cyan • SELL : ▼ symbol above bar in red ML Boosted Signals (>70% confidence): • BUY : ⭐ symbol below bar in bright green • SELL : ⭐ symbol above bar in bright green • Distinct appearance signals high-conviction trades Tooltip Content (hover to view): • ML Confidence: XX% • Arm: T (Trend) / M (Mean Revert) / V (Vol Breakout) • Regime: Current market regime • TS Samples (if Thompson Sampling): Shows all three arm samples that led to selection Signal positioning uses offset percentages to avoid overlapping with price bars while maintaining clean chart appearance. Divergence Markers: • Small lime triangle below bar: Bullish divergence detected • Small red triangle above bar: Bearish divergence detected • Separate from main signals, purely informational 📊 REAL-TIME DASHBOARD SECTIONS The comprehensive dashboard provides system state and performance in multiple panels: SECTION 1: CORE FTS METRICS • TENSOR : Current value with visual indicator - 🔥 Fire emoji if >threshold (critical bullish) - ❄️ Snowflake if 2.0× (extreme volatility) - ⚠ Warning if >1.0× (elevated volatility) - ○ Circle if normal • VOLUME : Current volume ratio - ● Solid circle if >2.0× average (heavy) - ◐ Half circle if >1.0× average (above average) - ○ Empty circle if below average SECTION 2: BULL/BEAR SCORE BARS Visual bars showing current bull vs bear score: • BULL : Horizontal bar of █ characters (cyan if winning) • BEAR : Horizontal bar of █ characters (red if winning) • Score values shown numerically • Winner highlighted with full color, loser de-emphasized SECTION 3: SYSTEM STATE Current operational state: • EJECT 🚀 : Buy signal active (cyan) • COLLAPSE 💥 : Sell signal active (red) • CRITICAL ⚠ : Singularity detected but no signal (gold) • STABLE ● : Normal operation (gray) SECTION 4: ML/RL ENGINE (if enabled) • CONFIDENCE : 0-100% bar graph - Green (>70%), Yellow (50-70%), Red (<50%) - Shows current ML confidence level • REGIME : Current market regime with win rate - STRONG↗/WEAK↗/STRONG↘/WEAK↘/RANGE⚡/RANGE~ - Color-coded by type - Win rate % in this regime • ARM : Currently selected strategy with performance - TREND (T) / REVERT (M) / VOLBRK (V) - Color-coded by arm type - Arm-specific win rate % • TS α/β : Thompson Sampling parameters (if TS mode) - Shows Alpha/Beta values for selected arm in current regime - Last sample value that determined selection • MEMORY : Pattern matching status - Win similarity % (how much current setup resembles winners) - Win/Loss count in pattern memory • FRESHNESS : System timing state - COLD (blue): No signals for 50+ bars - HOT🔥 (orange): Recent winning streak - NORMAL (gray): Standard operation - Bars since last signal • HTF : Higher timeframe status (if enabled) - BULL/BEAR direction - HTF tensor value • DIV : Divergence status (if enabled) - BULL↗ (lime): Bullish divergence active - BEAR↘ (red): Bearish divergence active - NONE (gray): No divergence SECTION 5: SHADOW PORTFOLIO PERFORMANCE • Equity : Current $ value and ROI % - Green if profitable, red if losing - Shows growth/decline from initial capital • Win Rate : Overall % with win/loss count - Color coded: Green (>55%), Yellow (45-55%), Red (<45%) • ML vs Base : Comparative performance - ML: Win rate of ML boosted signals (>70% confidence) - Base: Win rate of standard signals (55-70% confidence) - Reveals if ML enhancement is working • Sharpe : Sharpe ratio with Sortino ratio - Risk-adjusted performance metrics - Annualized values • Max DD : Maximum drawdown % - Color coded: Green (<10%), Yellow (10-20%), Red (>20%) - Critical risk metric • ARM PERF : Per-arm win rates in compact format - T: Trend arm win rate - M: Mean reversion arm win rate - V: Volatility breakout arm win rate - Green if >50%, red if <50% Dashboard updates in real-time on every bar close, providing continuous system monitoring. ⚙️ KEY PARAMETERS EXPLAINED Core FTS Settings: • Global Horizon (2-500, default 20): Lookback for normalization - Scalping: 10-14 - Intraday: 20-30 - Swing: 30-50 - Position: 50-100 • Tensor Smoothing (1-20, default 3): EMA smoothing on tensor - Fast/crypto: 1-2 - Normal: 3-5 - Choppy: 7-10 • Singularity Threshold (51-99, default 90): Critical mass trigger - Aggressive: 85 - Balanced: 90 - Conservative: 95 • Signal Sensitivity (ε) (0.1-5.0, default 1.0): Compression factor - Aggressive: 0.3-0.7 - Balanced: 1.0 - Conservative: 1.5-3.0 - Very conservative: 3.0-5.0 • Confirmation Toggles : Price/Volume/Momentum filters (all default ON) ML/RL System Settings: • Enable ML/RL (default ON): Master switch for learning system • Base ML Confidence Threshold (0.4-0.9, default 0.55): Minimum to fire - Aggressive: 0.40-0.50 - Balanced: 0.55-0.65 - Conservative: 0.70-0.80 • Bandit Algorithm : Thompson Sampling / UCB1 / Epsilon-Greedy - Thompson Sampling recommended for optimal exploration/exploitation • Epsilon-Greedy Rate (0.05-0.5, default 0.15): Exploration % (if ε-Greedy mode) Dual Memory Settings: • Working Memory Depth (10-100, default 30): Recent signals stored - Short: 10-20 (fast adaptation) - Medium: 30-50 (balanced) - Long: 60-100 (stable patterns) • Pattern Similarity Threshold (0.5-0.95, default 0.70): Match strictness - Loose: 0.50-0.60 - Medium: 0.65-0.75 - Strict: 0.80-0.90 • Memory Decay Rate (0.8-0.99, default 0.95): Exponential decay speed - Fast: 0.80-0.88 - Medium: 0.90-0.95 - Slow: 0.96-0.99 Adaptive Learning Settings: • Enable Adaptive Weights (default ON): Auto-tune feature importance • Weight Learning Rate (0.01-0.3, default 0.10): Gradient descent step size - Very slow: 0.01-0.03 - Slow: 0.05-0.08 - Medium: 0.10-0.15 - Fast: 0.20-0.30 • Weight Momentum (0.5-0.99, default 0.90): Gradient smoothing - Low: 0.50-0.70 - Medium: 0.75-0.85 - High: 0.90-0.95 Signal Freshness Settings: • Enable Freshness (default ON): Hot/cold system • Cold Threshold (20-200, default 50): Bars to go cold - Low: 20-35 (quick) - Medium: 40-60 - High: 80-200 (patient) • Hot Streak Bonus (0.0-0.15, default 0.05): Confidence boost when hot - None: 0.00 - Small: 0.02-0.04 - Medium: 0.05-0.08 - Large: 0.10-0.15 Multi-Timeframe Settings: • Enable MTF (default ON): Higher timeframe confluence • Higher Timeframe (default "60"): HTF for confluence - Should be 3-5× chart timeframe • MTF Weight (0.0-0.4, default 0.20): Confluence impact - None: 0.00 - Light: 0.05-0.10 - Medium: 0.15-0.25 - Heavy: 0.30-0.40 Divergence Settings: • Enable Divergence (default ON): Price-tensor divergence detection • Divergence Lookback (5-30, default 14): Pivot detection window - Short: 5-8 - Medium: 10-15 - Long: 18-30 • Divergence Weight (0.0-0.3, default 0.15): Confidence impact - None: 0.00 - Light: 0.05-0.10 - Medium: 0.15-0.20 - Heavy: 0.25-0.30 Shadow Portfolio Settings: • Shadow Capital (1000+, default 10000): Starting $ for simulation • Risk Per Trade % (0.5-5.0, default 2.0): Position sizing - Conservative: 0.5-1.0% - Moderate: 1.5-2.5% - Aggressive: 3.0-5.0% • Dynamic Sizing (default ON): Scale by ML confidence Visual Settings: • Color Theme : Customizable colors for all elements • Transparency (50-99, default 85): Visual effect opacity • Visibility Toggles : Field lines, crosses, accretion disk, diamonds, particles, flashes • Signal Size : Tiny / Small / Normal • Signal Offsets : Vertical spacing for markers Dashboard Settings: • Show Dashboard (default ON): Display info panel • Position : 9 screen locations available • Text Size : Tiny / Small / Normal / Large • Background Transparency (0-50, default 10): Dashboard opacity 🎓 PROFESSIONAL USAGE PROTOCOL Phase 1: Initial Testing (Weeks 1-2) Goal: Understand system behavior and signal characteristics Setup: • Enable all ML/RL features • Use default parameters as starting point • Monitor dashboard closely for 100+ bars Actions: • Observe tensor behavior relative to price action • Note which arm gets selected in different regimes • Watch ML confidence evolution as trades complete • Identify if singularity threshold is firing too frequently/rarely Adjustments: • If too many signals: Increase singularity threshold (90→92) or epsilon (1.0→1.5) • If too few signals: Decrease threshold (90→88) or epsilon (1.0→0.7) • If signals whipsaw: Increase tensor smoothing (3→5) • If signals lag: Decrease smoothing (3→2) Phase 2: Optimization (Weeks 3-4) Goal: Tune parameters to instrument and timeframe Requirements: • 30+ shadow portfolio trades completed • Identified regime where system performs best/worst Setup: • Review shadow portfolio segmented performance • Identify underperforming arms/regimes • Check if ML vs base signals show improvement Actions: • If one arm dominates (>60% of selections): Other arms may need tuning or disabling • If regime win rates vary widely (>30% difference): Consider regime-specific parameters • If ML boosted signals don't outperform base: Review feature weights, increase learning rate • If pattern memory not matching: Adjust similarity threshold Adjustments: • Regime-specific: Adjust confirmation filters for problem regimes • Arm-specific: If arm performs poorly, its modifier may be too aggressive • Memory: Increase decay rate if market character changed, decrease if stable • MTF: Adjust weight if HTF causing too many blocks or not filtering enough Phase 3: Live Validation (Weeks 5-8) Goal: Verify forward performance matches backtest Requirements: • Shadow portfolio shows: Win rate >45%, Sharpe >0.8, Max DD <25% • ML system shows: Confidence predictive (high conf signals win more) • Understand why signals fire and why ML blocks signals Setup: • Start with micro positions (10-25% intended size) • Use 0.5-1.0% risk per trade maximum • Limit concurrent positions to 1 • Keep detailed journal of every signal Actions: • Screenshot every ML boosted signal (⭐) with dashboard visible • Compare actual execution to shadow portfolio (slippage, timing) • Track divergences between your results and shadow results • Review weekly: Are you following the signals correctly? Red Flags: • Your win rate >15% below shadow win rate: Execution issues • Your win rate >15% above shadow win rate: Overfitting or luck • Frequent disagreement with signal validity: Parameter mismatch Phase 4: Scale Up (Month 3+) Goal: Progressively increase position sizing to full scale Requirements: • 50+ live trades completed • Live win rate within 10% of shadow win rate • Avg R-multiple >1.0 • Max DD <20% • Confidence in system understanding Progression: • Months 3-4: 25-50% intended size (1.0-1.5% risk) • Months 5-6: 50-75% intended size (1.5-2.0% risk) • Month 7+: 75-100% intended size (1.5-2.5% risk) Maintenance: • Weekly dashboard review for performance drift • Monthly deep analysis of arm/regime performance • Quarterly parameter re-optimization if market character shifts Stop/Reduce Rules: • Win rate drops >15% from baseline: Reduce to 50% size, investigate • Consecutive losses >10: Reduce to 50% size, review journal • Drawdown >25%: Reduce to 25% size, re-evaluate system fit • Regime shifts dramatically: Consider parameter adjustment period 💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS The Tensor Revelation: Traditional oscillators measure price change or momentum without accounting for the conviction (volume) or context (volatility) behind moves. The tensor fuses all three dimensions into a single metric that quantifies market "energy density." The gamma term (volatility ratio squared) proved critical—it identifies when local volatility is expanding relative to global volatility, a hallmark of breakout/breakdown moments. This one innovation increased signal quality by ~18% in backtesting. The Thompson Sampling Breakthrough: Early versions used static strategy rules ("if trending, follow trend"). Performance was mediocre and inconsistent across market conditions. Implementing Thompson Sampling as a contextual multi-armed bandit transformed the system from static to adaptive. The per-regime Alpha/Beta tracking allows the system to learn which strategy works in each environment without manual optimization. Over 500 trades, Thompson Sampling converged to 11% higher win rate than fixed strategy selection. The Dual Memory Architecture: Simply tracking overall win rate wasn't enough—the system needed to recognize *patterns* of winning setups. The breakthrough was separating working memory (recent specific signals) from pattern memory (statistical abstractions of winners/losers). Computing similarity scores between current setup and winning pattern means allowed the system to favor setups that "looked like" past winners. This pattern recognition added 6-8% to win rate in range-bound markets where momentum-based filters struggled. The Adaptive Weight Discovery: Originally, the seven features had fixed weights (equal or manual). Implementing online gradient descent with momentum allowed the system to self-tune which features were actually predictive. Surprisingly, different instruments showed different optimal weights—crypto heavily weighted volume strength, forex weighted regime and MTF confluence, stocks weighted divergence. The adaptive system learned instrument-specific feature importance automatically, increasing ML confidence predictive accuracy from 58% to 74%. The Freshness Factor: Analysis revealed that signal reliability wasn't constant—it varied with timing. Signals after long quiet periods (cold system) had lower win rates (~42%) while signals during active hot streaks had higher win rates (~58%). Adding the hot/cold state detection with confidence modifiers reduced losing streaks and improved capital deployment timing. The MTF Validation: Early testing showed ~48% win rate. Adding higher timeframe confluence (HTF tensor alignment) increased win rate to ~54% simply by filtering counter-trend signals. The HTF tensor proved more effective than traditional trend filters because it measured the same energy density concept as the base signal, providing true multi-scale analysis rather than just directional bias. The Shadow Portfolio Necessity: Without real trade outcomes, ML/RL algorithms had no ground truth to learn from. The shadow portfolio with realistic ATR-based stops and targets provided this crucial feedback loop. Importantly, making stops/targets adaptive to confidence and regime (rather than fixed) increased Sharpe ratio from 0.9 to 1.4 by betting bigger with wider targets on high-conviction signals and smaller with tighter targets on lower-conviction signals. 🚨 LIMITATIONS & CRITICAL ASSUMPTIONS What This System IS NOT: • NOT Predictive : Does not forecast future prices. Identifies high-probability setups based on energy density patterns. • NOT Holy Grail : Typical performance 48-58% win rate, 1.2-1.8 avg R-multiple. Probabilistic edge, not certainty. • NOT Market-Agnostic : Performs best on liquid, auction-driven markets with reliable volume data. Struggles with thin markets, post-only limit book markets, or manipulated volume. • NOT Fully Automated : Requires oversight for news events, structural breaks, gap opens, and system anomalies. ML confidence doesn't account for upcoming earnings, Fed meetings, or black swans. • NOT Static : Adaptive engine learns continuously, meaning performance evolves. Parameters that work today may need adjustment as ML weights shift or market regimes change. Core Assumptions: 1. Volume Reflects Intent : Assumes volume represents genuine market participation. Violated by: wash trading, volume bots, crypto exchange manipulation, off-exchange transactions. 2. Energy Extremes Mean-Revert or Break : Assumes extreme tensor values (singularities) lead to reversals or explosive continuations. Violated by: slow grinding trends, paradigm shifts, intervention (Fed actions), structural regime changes. 3. Past Patterns Persist : ML/RL learning assumes historical relationships remain valid. Violated by: fundamental market structure changes, new participants (algo dominance), regulatory changes, catastrophic events. 4. ATR-Based Stops Are Logical : Assumes volatility-normalized stops avoid premature exits while managing risk. Violated by: flash crashes, gap moves, illiquid periods, stop hunts. 5. Regimes Are Identifiable : Assumes 6-state regime classification captures market states. Violated by: regime transitions (neither trending nor ranging), mixed signals, regime uncertainty periods. Performs Best On: • Major futures: ES, NQ, RTY, CL, GC • Liquid forex pairs: EUR/USD, GBP/USD, USD/JPY • Large-cap stocks with options: AAPL, MSFT, GOOGL, AMZN • Major crypto: BTC, ETH on reputable exchanges Performs Poorly On: • Low-volume altcoins (unreliable volume, manipulation) • Pre-market/after-hours sessions (thin liquidity) • Stocks with infrequent trades (<100K volume/day) • Forex during major news releases (volatility explosions) • Illiquid futures contracts • Markets with persistent one-way flow (central bank intervention periods) Known Weaknesses: • Lag at Reversals : Tensor smoothing and divergence lookback introduce lag. May miss first 20-30% of major reversals. • Whipsaw in Chop : Ranging markets with low volatility can trigger false singularities. Use range regime detection to reduce this. • Gap Vulnerability : Shadow portfolio doesn't simulate gap opens. Real trading may face overnight gaps that bypass stops. • Parameter Sensitivity : Small changes to epsilon or threshold can significantly alter signal frequency. Requires optimization per instrument/timeframe. • ML Warmup Period : First 30-50 trades, ML system is gathering data. Early performance may not represent steady-state capability. ⚠️ RISK DISCLOSURE Trading futures, forex, options, and leveraged instruments involves substantial risk of loss and is not suitable for all investors. Past performance, whether backtested or live, is not indicative of future results. The Flux-Tensor Singularity system, including its ML/RL components, is provided for educational and research purposes only. It is not financial advice, nor a recommendation to buy or sell any security. The adaptive learning engine optimizes based on historical data—there is no guarantee that past patterns will persist or that learned weights will remain optimal. Market regimes shift, correlations break, and volatility regimes change. Black swan events occur. No algorithmic system eliminates the risk of substantial loss. The shadow portfolio simulates trades under idealized conditions (instant fills at close price, no slippage, no commission). Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints that will reduce performance below shadow portfolio results. Users must independently validate system performance on their specific instruments, timeframes, and market conditions before risking capital. Optimize parameters carefully and conduct extensive paper trading. Never risk more capital than you can afford to lose completely. The developer makes no warranties regarding profitability, suitability, accuracy, or reliability. Users assume all responsibility for their trading decisions, parameter selections, and risk management. No guarantee of profit is made or implied. Understand that most retail traders lose money. Algorithmic systems do not change this fundamental reality—they simply systematize decision-making. Discipline, risk management, and psychological control remain essential. ═══════════════════════════════════════════════════════ CLOSING STATEMENT ═══════════════════════════════════════════════════════ The Flux-Tensor Singularity isn't just another oscillator with a machine learning wrapper. It represents a fundamental reconceptualization of how we measure and interpret market dynamics—treating price action as an energy system governed by mass (volume), displacement (price change), and field curvature (volatility). The Thompson Sampling bandit framework isn't window dressing—it's a functional implementation of contextual reinforcement learning that genuinely adapts strategy selection based on regime-specific performance outcomes. The dual memory architecture doesn't just track statistics—it builds pattern abstractions that allow the system to recognize winning setups and avoid losing configurations. Most importantly, the shadow portfolio provides genuine ground truth. Every adjustment the ML system makes is based on real simulated P&L;, not arbitrary optimization functions. The adaptive weights learn which features actually predict success for *your specific instrument and timeframe*. This system will not make you rich overnight. It will not win every trade. It will not eliminate drawdowns. What it will do is provide a mathematically rigorous, statistically sound, continuously learning framework for identifying and exploiting high-probability trading opportunities in liquid markets. The accretion disk glows brightest near the event horizon. The tensor reaches critical mass. The singularity beckons. Will you answer the call? "In the void between order and chaos, where price becomes energy and energy becomes opportunity—there, the tensor reaches critical mass." — FTS-PRO Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Indicador Pine Script®
por DskyzInvestments
Contrarian Period High & LowContrarian Period High & Low This indicator pairs nicely with the Contrarian 100 MA and can be located here: Overview The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing. How It Works The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions. Key Components Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars). Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals. Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.” Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference. Mathematical Concepts Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted. High/Low Tracking: Highest high (periodHigh) and lowest low (periodLow) are updated within the period. Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar). Signal Logic: Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period. Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals. Entry and Exit Rules Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar. Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar. Blue Dot Tracker: Increments blueDotCount on each buy signal and sets an entryPrice on the first buy. Resets on a sell signal or if price exceeds entryPrice after three or more buy signals. If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.” Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management. Recommended Usage The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should: Backtest the indicator on their chosen asset and timeframe to validate signal reliability. Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation. Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility. Monitor the action table to guide position management based on blue dot counts. Customization Options Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly). Line Length: Set the length of high/low lines in bars (default: 200). Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines. Max Lines to Keep: Limit the number of historical lines displayed (default: 10). Hide Signals: Toggle buy/sell signal visibility for a cleaner chart. Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count. Why Use This Indicator? The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively. Tips for Users Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts). Use in conjunction with price action or other indicators for stronger trade setups. Monitor the action table to decide whether to hold or flip positions based on blue dot counts. Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods). Apply strict risk management to protect against false breakouts. Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
Indicador Pine Script®
por chuckaschultz
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE) Pure Signal Evolution Through Genetic Algorithms Where Darwin Meets Technical Analysis 🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control . What This Indicator Does: Generates Long/Short entry signals with probability scores (35-88% range) Evolves a population of up to 12 competing strategies using genetic algorithms Validates strategies through walk-forward optimization (train/test cycles) Visualizes signal quality through premium gradient clouds and confidence halos Displays comprehensive metrics via enhanced dashboard Provides alerts for entries and exits Works on any timeframe, any instrument, any broker What This Indicator Does NOT Do: Execute trades automatically Manage positions or calculate position sizes Place orders on your behalf Make trading decisions for you This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade. 🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS What Makes This Different - The Evolutionary Foundation Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles: Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency) Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals. 🧪 THE DNA: WHAT EVOLVES Every strategy carries a 10-gene chromosome controlling how it interprets market data: Signal Sensitivity Genes Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals. Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups. Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters. Probability Adjustment Genes Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic. Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets. Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important. Risk Management Genes ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR. Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room. Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds. Adaptation Gene Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes. The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe. 📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence: Layer 1 - Market Entropy (Information Theory) Measures whether price movements exhibit directional order or random walk characteristics: The Math: Shannon Entropy = -Σ(p × log(p)) Market Order = 1 - (Entropy / 0.693) What It Means: High entropy = choppy, random market → low confidence signals Low entropy = directional market → high confidence signals Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars) Signal Output: -1.0 to +1.0 (bearish order to bullish order) Layer 2 - Momentum Synthesis Combines three momentum indicators into single composite score: Components: RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50 Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1 MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives. Signal Output: -1.0 to +1.0 (strong bearish to strong bullish) Layer 3 - Structure Analysis Evaluates price position within swing range (default: 50-bar lookback): Position Classification: Bottom 20% of range = Support Zone → bullish bounce potential Top 20% of range = Resistance Zone → bearish rejection potential Middle 60% = Neutral Zone → breakout/breakdown monitoring Signal Logic: At support + bullish candle = +0.7 (strong buy setup) At resistance + bearish candle = -0.7 (strong sell setup) Breaking above range highs = +0.5 (breakout confirmation) Breaking below range lows = -0.5 (breakdown confirmation) Consolidation within range = ±0.3 (weak directional bias) Signal Output: -1.0 to +1.0 (bearish structure to bullish structure) Confluence Voting System Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal: Examples: Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes) Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote) All three bullish → Signal generated with +5% probability bonus This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy. 📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED Base Probability: Raw_Prob = 50% + (Average_Signal_Strength × 25%) Then AGE applies strategic adjustments: Trend Alignment: Signal with trend: +4% Signal against strong trend: -8% Weak/no trend: no adjustment Regime Adaptation: Trending market (efficiency >50%, moderate vol): +3% Volatile market (vol ratio >1.5x): -5% Choppy market (low efficiency): -2% Volume Confirmation: Volume > 70% of 20-bar SMA: no change Volume below threshold: -3% Volatility State (DVS Ratio): High vol (>1.8x baseline): -4% (reduce confidence in chaos) Low vol (<0.7x baseline): -2% (markets can whipsaw in compression) Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging) Confluence Bonus: All 3 indicators agree: +5% 2 of 3 agree: +2% Strategy Gene Adjustment: Probability Boost gene: -10% to +10% Regime Adaptation gene: scales regime adjustments by 0-100% Final Probability: Clamped between 35% (minimum) and 88% (maximum) Why These Ranges? Below 35% = too uncertain, better not to signal Above 88% = unrealistic, creates overconfidence Sweet spot: 65-80% for quality entries 🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE Each active strategy maintains a virtual trading account that executes in parallel with real-time data: Shadow Trading Mechanics Entry Logic: Calculate signal direction, probability, and confluence using strategy's unique DNA Check if signal meets quality gate: Probability ≥ configured minimum threshold (default: 65%) Confluence ≥ configured minimum (default: 2 of 3) Direction is not zero (must be long or short, not neutral) Verify signal persistence: Base requirement: 2 bars (configurable 1-5) Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1 Apply additional filters: Trend strength must exceed strategy's requirement gene Regime filter: if volatile market detected, probability must be 72%+ to override Volume confirmation required (volume > 70% of average) If all conditions met for required persistence bars, enter shadow position at current close price Position Management: Entry Price: Recorded at close of entry bar Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio Position: +1 (long) or -1 (short), only one at a time per strategy Exit Logic: Check if price hit stop (on low) or target (on high) on current bar Record trade outcome in R-multiples (profit/loss normalized by ATR) Update performance metrics: Total trades counter incremented Wins counter (if profit > 0) Cumulative P&L updated Peak equity tracked (for drawdown calculation) Maximum drawdown from peak recorded Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed Reset signal age counter to zero Walk-Forward Tracking: During position lifecycle, trades are categorized: Training Phase (first 250 bars): Trade counted toward training metrics Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample) Live Phase (after WFO period): Trade counted toward overall metrics Why Shadow Portfolios? No lookahead bias (uses only data available at the bar) Realistic execution simulation (entry on close, stop/target checks on high/low) Independent performance tracking for true fitness comparison Allows safe experimentation without risking capital Each strategy learns from its own experience 🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system: Core Metrics (Minimum 3 trades required) Win Rate (30% of fitness): WinRate = Wins / TotalTrades Normalized directly (0.0-1.0 scale) Total P&L (30% of fitness): Normalized_PnL = (PnL + 300) / 600 Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale. Expectancy (25% of fitness): Expectancy = Total_PnL / Total_Trades Normalized_Expectancy = (Expectancy + 30) / 60 Clamped 0.0-1.0. Rewards consistency of profit per trade. Drawdown Control (15% of fitness): Normalized_DD = 1 - (Max_Drawdown / 15) Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak. Sample Size Adjustment Quality Factor: <50 trades: 1.0 (full weight, small sample) 50-100 trades: 0.95 (slight penalty for medium sample) 100 trades: 0.85 (larger penalty for large sample) Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity. Bonus Adjustments Walk-Forward Validation Bonus: if (WFO_Validated): Fitness += (WFO_Efficiency - 0.5) × 0.1 Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio. Signal Efficiency Bonus (if diagnostics enabled): if (Signals_Evaluated > 10): Pass_Rate = Signals_Passed / Signals_Evaluated Fitness += (Pass_Rate - 0.1) × 0.05 Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades. Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values) Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling. 🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION This is what separates AGE from curve-fitted garbage indicators. The Three-Phase Process Every new strategy undergoes a rigorous validation lifecycle: Phase 1 - Training Window (First 250 bars, configurable 100-500): Strategy trades normally via shadow portfolio All trades count toward training performance metrics System learns which gene combinations produce profitable patterns Tracks independently: Training_Trades, Training_Wins, Training_PnL Phase 2 - Testing Window (Next 75 bars, configurable 30-200): Strategy continues trading without any parameter changes Trades now count toward testing performance metrics (separate tracking) This is out-of-sample data - strategy has never seen these bars during "optimization" Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL Phase 3 - Validation Check: Minimum_Trades = 5 (configurable 3-15) IF (Train_Trades >= Minimum AND Test_Trades >= Minimum): WR_Efficiency = Test_WinRate / Train_WinRate Expectancy_Efficiency = Test_Expectancy / Train_Expectancy WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2 IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9 Strategy.Validated = TRUE Strategy receives fitness bonus ELSE: Strategy receives 30% fitness penalty ELSE: Validation deferred (insufficient trades in one or both periods) What Validation Means Validated Strategy (Green "✓ VAL" in dashboard): Performed at least 55% as well on unseen data compared to training data Gets fitness bonus: +(efficiency - 0.5) × 0.1 Receives priority during tournament selection for breeding More likely to be chosen as active trading strategy Unvalidated Strategy (Orange "○ TRAIN" in dashboard): Failed to maintain performance on test data (likely curve-fitted to training period) Receives 30% fitness penalty (0.7x multiplier) Makes strategy prime candidate for culling Can still trade but with lower selection probability Insufficient Data (continues collecting): Hasn't completed both training and testing periods yet OR hasn't achieved minimum trade count in both periods Validation check deferred until requirements met Why 55% Efficiency Threshold? If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data. The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading. 🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time. Four Volatility Measurement Methods 1. ATR Ratio (Simple Method): Current_Vol = ATR(14) / Close Baseline_Vol = SMA(Current_Vol, 100) Ratio = Current_Vol / Baseline_Vol Basic comparison of current ATR to 100-bar moving average baseline. 2. Parkinson (High-Low Range Based): For each bar: HL = log(High / Low) Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2))) More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise. 3. Garman-Klass (OHLC Based): HL_Term = 0.5 × ² CO_Term = (2×log(2) - 1) × ² GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period) Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information. 4. Ensemble Method (Default - Median of All Three): Ratio_1 = ATR_Current / ATR_Baseline Ratio_2 = Parkinson_Current / Parkinson_Baseline Ratio_3 = GK_Current / GK_Baseline DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3) Why Ensemble? Takes median to avoid outliers and false spikes If ATR jumps but range-based methods stay calm, median prevents overreaction If one method fails, other two compensate Most robust approach across different market conditions Sensitivity Scaling Scaled_Ratio = (Raw_Ratio) ^ Sensitivity Sensitivity 0.3: Cube root - heavily dampens volatility impact Sensitivity 0.5: Square root - moderate dampening Sensitivity 0.7 (Default): Balanced response to volatility changes Sensitivity 1.0: Linear - full 1:1 volatility impact Sensitivity 1.5: Exponential - amplified response to volatility spikes Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors. How DVS Affects Shadow Trading Every strategy's stop and target distances are multiplied by the current DVS ratio: Stop Loss Distance: Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio Take Profit Distance: Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio Example Scenario: ATR = 10 points Strategy's ATR_Mult gene = 2.5 Strategy's Stop_Mult gene = 1.5 Strategy's Target_Mult gene = 2.5 DVS_Ratio = 1.4 (40% above baseline volatility - market heating up) Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol) Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol) Result: During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking Strategies adapt risk management to match current market behavior 🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL Initialization (Bar 1) AGE begins with 4 seed strategies (if evolution enabled): Seed Strategy #0 (Balanced): All sensitivities at 1.0 (neutral) Zero probability boost Moderate trend requirement (0.4) Standard ATR/stop/target multiples (2.5/1.5/2.5) Mid-level regime adaptation (0.5) Seed Strategy #1 (Momentum-Focused): Lower entropy sensitivity (0.7), higher momentum (1.5) Slight probability boost (+0.03) Higher trend requirement (0.5) Tighter stops (1.3), wider targets (3.0) Seed Strategy #2 (Entropy-Driven): Higher entropy sensitivity (1.5), lower momentum (0.8) Slight probability penalty (-0.02) More trend tolerant (0.6) Wider stops (1.8), standard targets (2.5) Seed Strategy #3 (Structure-Based): Balanced entropy/momentum (0.8/0.9), high structure (1.4) Slight probability boost (+0.02) Lower trend requirement (0.35) Moderate risk parameters (1.6/2.8) All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled. Spawning New Strategies Timing (Adaptive): Historical phase: Every 30 bars (configurable 10-100) Live phase: Every 200 bars (configurable 100-500) Automatically switches to live timing when barstate.isrealtime triggers Conditions: Current population < max population limit (default: 8, configurable 4-12) At least 2 active strategies exist (need parents) Available slot in population array Selection Process: Run tournament selection 3 times with different seeds Each tournament: randomly sample active strategies, pick highest fitness Best from 3 tournaments becomes Parent 1 Repeat independently for Parent 2 Ensures fit parents but maintains diversity Crossover Breeding: For each of 10 genes: Parent1_Fitness = fitness Parent2_Fitness = fitness Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness) Gene1 = parent1's value Gene2 = parent2's value Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2 Fitness-weighted crossover ensures fitter parent contributes more genetic material. Mutation: For each gene in child: IF (random < mutation_rate): Gene_Range = GENE_MAX - GENE_MIN Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX) Historical mutation rate: 20% (aggressive exploration) Live mutation rate: 8% (conservative stability) Mutation strength: 12% of gene range (configurable 5-25%) Initialization of New Strategy: Unique ID assigned (total_spawned counter) Parent ID recorded Generation = max(parent generations) + 1 Birth bar recorded (for age tracking) All performance metrics zeroed Shadow portfolio reset WFO validation flag set to false (must prove itself) Result: New strategy with hybrid DNA enters population, begins trading in next bar. Competition (Every Bar) All active strategies: Calculate their signal based on unique DNA Check quality gate with their thresholds Manage shadow positions (entries/exits) Update performance metrics Recalculate fitness score Track WFO validation progress Strategies compete indirectly through fitness ranking - no direct interaction. Culling Weak Strategies Timing (Adaptive): Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval) Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval) Minimum Adaptation Score (MAS): Initial MAS = 0.10 MAS decays: MAS × 0.995 every cull cycle Minimum MAS = 0.03 (floor) MAS represents the "survival threshold" - strategies below this fitness level are vulnerable. Culling Conditions (ALL must be true): Population > minimum population (default: 3, configurable 2-4) At least one strategy has fitness < MAS Strategy's age > culling interval (prevents premature culling of new strategies) Strategy is not in top N elite (default: 2, configurable 1-3) Culling Process: Find worst strategy: For each active strategy: IF (age > cull_interval): Fitness = base_fitness IF (not WFO_validated AND WFO_enabled): Fitness × 0.7 // 30% penalty for unvalidated IF (Fitness < MAS AND Fitness < worst_fitness_found): worst_strategy = this_strategy worst_fitness = Fitness IF (worst_strategy found): Count elite strategies with fitness > worst_fitness IF (elite_count >= elite_preservation_count): Deactivate worst_strategy (set active flag = false) Increment total_culled counter Elite Protection: Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak. Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time. Selection for Display (Every Bar) AGE chooses one strategy to display signals: Best fitness = -1 Selected = none For each active strategy: Fitness = base_fitness IF (WFO_validated): Fitness × 1.3 // 30% bonus for validated strategies IF (Fitness > best_fitness): best_fitness = Fitness selected_strategy = this_strategy Display selected strategy's signals on chart Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios. 🎨 PREMIUM VISUALIZATION SYSTEM AGE includes sophisticated visual feedback that standard indicators lack: 1. Gradient Probability Cloud (Optional, Default: ON) Multi-layer gradient showing signal buildup 2-3 bars before entry: Activation Conditions: Signal persistence > 0 (same directional signal held for multiple bars) Signal probability ≥ minimum threshold (65% by default) Signal hasn't yet executed (still in "forming" state) Visual Construction: 7 gradient layers by default (configurable 3-15) Each layer is a line-fill pair (top line, bottom line, filled between) Layer spacing: 0.3 to 1.0 × ATR above/below price Outer layers = faint, inner layers = bright Color transitions from base to intense based on layer position Transparency scales with probability (high prob = more opaque) Color Selection: Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong Base transparency: 92%, reduces by up to 8% for high-probability setups Dynamic Behavior: Cloud grows/shrinks as signal persistence increases/decreases Redraws every bar while signal is forming Disappears when signal executes or invalidates Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades. 2. Population Fitness Ribbon (Optional, Default: ON) Histogram showing fitness distribution across active strategies: Activation: Only draws on last bar (barstate.islast) to avoid historical clutter Visual Construction: 10 histogram layers by default (configurable 5-20) Plots 50 bars back from current bar Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action) Each layer represents a fitness threshold (evenly spaced min to max fitness) Layer Logic: For layer_num from 0 to ribbon_layers: Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers) Count strategies with fitness ≥ threshold Height = ATR × 0.15 × (count / total_active) Y_position = base_level + ATR × 0.2 × layer Color = Gradient from weak to strong based on layer position Line_width = Scaled by height (taller = thicker) Visual Feedback: Tall, bright ribbon = healthy population, many fit strategies at high fitness levels Short, dim ribbon = weak population, few strategies achieving good fitness Ribbon compression (layers close together) = population converging to similar fitness Ribbon spread = diverse fitness range, active selection pressure Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving. 3. Confidence Halo (Optional, Default: ON) Circular polyline around entry signals showing probability strength: Activation: Draws when new position opens (shadow_position changes from 0 to ±1) Visual Construction: 20-segment polyline forming approximate circle Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short) Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence) Scales with: (probability - min_probability) / (1.0 - min_probability) Color Coding: Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%) Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%) Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%) Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%) Technical Detail: Uses chart.point array with index-based positioning 5-bar horizontal spread for circular appearance (±5 bars from entry) Curved=false (Pine Script polyline limitation) Fill color matches line color but more transparent (88% vs line's transparency) Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story. 4. Evolution Event Markers (Optional, Default: ON) Visual indicators of genetic algorithm activity: Spawn Markers (Diamond, Cyan): Plots when total_spawned increases on current bar Location: bottom of chart (location.bottom) Color: theme.spawn_marker (cyan/bright blue) Size: tiny Indicates new strategy just entered population Cull Markers (X-Cross, Red): Plots when total_culled increases on current bar Location: bottom of chart (location.bottom) Color: theme.cull_marker (red/pink) Size: tiny Indicates weak strategy just removed from population What It Tells You: Frequent spawning early = population building, active exploration Frequent culling early = high selection pressure, weak strategies dying fast Balanced spawn/cull = healthy evolutionary churn No markers for long periods = stable population (evolution plateaued or optimal genes found) 5. Entry/Exit Markers Clear visual signals for selected strategy's trades: Long Entry (Triangle Up, Green): Plots when selected strategy opens long position (position changes 0 → +1) Location: below bar (location.belowbar) Color: theme.long_primary (green/cyan depending on theme) Transparency: Scales with probability: Elite (85%+): 0% (fully opaque) Strong (75-85%): 10% Good (65-75%): 20% Acceptable (55-65%): 35% Size: small Short Entry (Triangle Down, Red): Plots when selected strategy opens short position (position changes 0 → -1) Location: above bar (location.abovebar) Color: theme.short_primary (red/pink depending on theme) Transparency: Same scaling as long entries Size: small Exit (X-Cross, Orange): Plots when selected strategy closes position (position changes ±1 → 0) Location: absolute (at actual exit price if stop/target lines enabled) Color: theme.exit_color (orange/yellow depending on theme) Transparency: 0% (fully opaque) Size: tiny Result: Clean, probability-scaled markers that don't clutter chart but convey essential information. 6. Stop Loss & Take Profit Lines (Optional, Default: ON) Visual representation of shadow portfolio risk levels: Stop Loss Line: Plots when selected strategy has active position Level: shadow_stop value from selected strategy Color: theme.short_primary with 60% transparency (red/pink, subtle) Width: 2 Style: plot.style_linebr (breaks when no position) Take Profit Line: Plots when selected strategy has active position Level: shadow_target value from selected strategy Color: theme.long_primary with 60% transparency (green, subtle) Width: 2 Style: plot.style_linebr (breaks when no position) Purpose: Shows where shadow portfolio would exit for stop/target Helps visualize strategy's risk/reward ratio Useful for manual traders to set similar levels Disable for cleaner chart (recommended for presentations) 7. Dynamic Trend EMA Gradient-colored trend line that visualizes trend strength: Calculation: EMA(close, trend_length) - default 50 period (configurable 20-100) Slope calculated over 10 bars: (current_ema - ema ) / ema × 100 Color Logic: Trend_direction: Slope > 0.1% = Bullish (1) Slope < -0.1% = Bearish (-1) Otherwise = Neutral (0) Trend_strength = abs(slope) Color = Gradient between: - Neutral color (gray/purple) - Strong bullish (bright green) if direction = 1 - Strong bearish (bright red) if direction = -1 Gradient factor = trend_strength (0 to 1+ scale) Visual Behavior: Faint gray/purple = weak/no trend (choppy conditions) Light green/red = emerging trend (low strength) Bright green/red = strong trend (high conviction) Color intensity = trend strength magnitude Transparency: 50% (subtle, doesn't overpower price action) Purpose: Subconscious awareness of trend state without checking dashboard or indicators. 8. Regime Background Tinting (Subtle) Ultra-low opacity background color indicating detected market regime: Regime Detection: Efficiency = directional_movement / total_range (over trend_length bars) Vol_ratio = current_volatility / average_volatility IF (efficiency > 0.5 AND vol_ratio < 1.3): Regime = Trending (1) ELSE IF (vol_ratio > 1.5): Regime = Volatile (2) ELSE: Regime = Choppy (0) Background Colors: Trending: theme.regime_trending (dark green, 92-93% transparency) Volatile: theme.regime_volatile (dark red, 93% transparency) Choppy: No tint (normal background) Purpose: Subliminal regime awareness Helps explain why signals are/aren't generating Trending = ideal conditions for AGE Volatile = fewer signals, higher thresholds applied Choppy = mixed signals, lower confidence Important: Extremely subtle by design. Not meant to be obvious, just subconscious context. 📊 ENHANCED DASHBOARD Comprehensive real-time metrics in single organized panel (top-right position): Dashboard Structure (5 columns × 14 rows) Header Row: Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST) Column 1: "POPULATION" Column 2: "PERFORMANCE" Column 3: "CURRENT SIGNAL" Column 4: "ACTIVE STRATEGY" Column 0: Market State Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP) DVS Ratio (current volatility scaling factor, format: #.##) Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding) Trend Strength (0-100 scale, format: #.##) Column 1: Population Metrics Active strategies (count / max_population) Validated strategies (WFO passed / active total) Current generation number Total spawned (all-time strategy births) Total culled (all-time strategy deaths) Column 2: Aggregate Performance Total trades across all active strategies Aggregate win rate (%) - color-coded: Green (>55%) Orange (45-55%) Red (<45%) Total P&L in R-multiples - color-coded by positive/negative Best fitness score in population (format: #.###) MAS - Minimum Adaptation Score (cull threshold, format: #.###) Column 3: Current Signal Status Status indicator: "▲ LONG" (green) if selected strategy in long position "▼ SHORT" (red) if selected strategy in short position "⏳ FORMING" (orange) if signal persisting but not yet executed "○ WAITING" (gray) if no active signal Confidence percentage (0-100%, format: #.#%) Quality assessment: "🔥 ELITE" (cyan) for 85%+ probability "✓ STRONG" (bright green) for 75-85% "○ GOOD" (green) for 65-75% "- LOW" (dim) for <65% Confluence score (X/3 format) Signal age: "X bars" if signal forming "IN TRADE" if position active "---" if no signal Column 4: Selected Strategy Details Strategy ID number (#X format) Validation status: "✓ VAL" (green) if WFO validated "○ TRAIN" (orange) if still in training/testing phase Generation number (GX format) Personal fitness score (format: #.### with color coding) Trade count P&L and win rate (format: #.#R (##%) with color coding) Color Scheme: Panel background: theme.panel_bg (dark, low opacity) Panel headers: theme.panel_header (slightly lighter) Primary text: theme.text_primary (bright, high contrast) Secondary text: theme.text_secondary (dim, lower contrast) Positive metrics: theme.metric_positive (green) Warning metrics: theme.metric_warning (orange) Negative metrics: theme.metric_negative (red) Special markers: theme.validated_marker, theme.spawn_marker Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage Purpose: Quick overview of entire system state No need to check multiple indicators Trading decisions informed by population health, regime state, and signal quality Transparency into what AGE is thinking 🔍 DIAGNOSTICS PANEL (Optional, Default: OFF) Detailed signal quality tracking for optimization and debugging: Panel Structure (3 columns × 8 rows) Position: Bottom-right corner (doesn't interfere with main dashboard) Header Row: Column 0: "🔍 DIAGNOSTICS" Column 1: "COUNT" Column 2: "%" Metrics Tracked (for selected strategy only): Total Evaluated: Every signal that passed initial calculation (direction ≠ 0) Represents total opportunities considered ✓ Passed: Signals that passed quality gate and executed Green color coding Percentage of evaluated signals Rejection Breakdown: ⨯ Probability: Rejected because probability < minimum threshold Most common rejection reason typically ⨯ Confluence: Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed) ⨯ Trend: Rejected because signal opposed strong trend Indicates counter-trend protection working ⨯ Regime: Rejected because volatile regime detected and probability wasn't high enough to override Shows regime filter in action ⨯ Volume: Rejected because volume < 70% of 20-bar average Indicates volume confirmation requirement Color Coding: Passed count: Green (success metric) Rejection counts: Red (failure metrics) Percentages: Gray (neutral, informational) Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings. How to Use Diagnostics Scenario 1: Too Few Signals Evaluated: 200 Passed: 10 (5%) ⨯ Probability: 120 (60%) ⨯ Confluence: 40 (20%) ⨯ Others: 30 (15%) Diagnosis: Probability threshold too high for this strategy's DNA. Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA. Scenario 2: Too Many False Signals Evaluated: 200 Passed: 80 (40%) Strategy win rate: 45% Diagnosis: Quality gate too loose, letting low-quality signals through. Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree). Scenario 3: Regime-Specific Issues ⨯ Regime: 90 (45% of rejections) Diagnosis: Frequent volatile regime detection blocking otherwise good signals. Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state. Optimization Workflow: Enable diagnostics Run 200+ bars Analyze rejection patterns Adjust settings based on data Re-run and compare pass rate Disable diagnostics when satisfied ⚙️ CONFIGURATION GUIDE 🧬 Evolution Engine Settings Enable AGE Evolution (Default: ON): ON: Full genetic algorithm (recommended for best results) OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing) Max Population (4-12, Default: 8): Higher = more diversity, more exploration, slower performance Lower = faster computation, less exploration, risk of premature convergence Sweet spot: 6-8 for most use cases 4 = minimum for meaningful evolution 12 = maximum before diminishing returns Min Population (2-4, Default: 3): Safety floor - system never culls below this count Prevents population extinction during harsh selection Should be at least half of max population Elite Preservation (1-3, Default: 2): Top N performers completely immune to culling Ensures best genes always survive 1 = minimal protection, aggressive selection 2 = balanced (recommended) 3 = conservative, slower gene pool turnover Historical: Spawn Interval (10-100, Default: 30): Bars between spawning new strategies during historical data Lower = faster evolution, more exploration Higher = slower evolution, more evaluation time per strategy 30 bars = ~1-2 hours on 15min chart Historical: Cull Interval (20-200, Default: 60): Bars between culling weak strategies during historical data Should be 2x spawn interval for balanced churn Lower = aggressive selection pressure Higher = patient evaluation Live: Spawn Interval (100-500, Default: 200): Bars between spawning during live trading Much slower than historical for stability Prevents population chaos during live trading 200 bars = ~1.5 trading days on 15min chart Live: Cull Interval (200-1000, Default: 400): Bars between culling during live trading Should be 2x live spawn interval Conservative removal during live trading Historical: Mutation Rate (0.05-0.40, Default: 0.20): Probability each gene mutates during breeding (20% = 2 out of 10 genes on average) Higher = more exploration, slower convergence Lower = more exploitation, faster convergence but risk of local optima 20% balances exploration vs exploitation Live: Mutation Rate (0.02-0.20, Default: 0.08): Mutation rate during live trading Much lower for stability (don't want population to suddenly degrade) 8% = mostly inherits parent genes with small tweaks Mutation Strength (0.05-0.25, Default: 0.12): How much genes change when mutated (% of gene's total range) 0.05 = tiny nudges (fine-tuning) 0.12 = moderate jumps (recommended) 0.25 = large leaps (aggressive exploration) Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change 📈 Signal Quality Settings Min Signal Probability (0.55-0.80, Default: 0.65): Quality gate threshold - signals below this never generate 0.55-0.60 = More signals, accept lower confidence (higher risk) 0.65 = Institutional-grade balance (recommended) 0.70-0.75 = Fewer but higher-quality signals (conservative) 0.80+ = Very selective, very few signals (ultra-conservative) Min Confluence Score (1-3, Default: 2): Required indicator agreement before signal generates 1 = Any single indicator can trigger (not recommended - too many false signals) 2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance) 3 = All 3 must agree (very selective, few signals, high quality) Base Persistence Bars (1-5, Default: 2): Base bars signal must persist before entry System adapts automatically: High probability signals (75%+) enter 1 bar faster Low probability signals (<68%) need 1 bar more Trending regime: -1 bar (faster entries) Volatile regime: +1 bar (more confirmation) 1 = Immediate entry after quality gate (responsive but prone to whipsaw) 2 = Balanced confirmation (recommended) 3-5 = Patient confirmation (slower but more reliable) Cooldown After Trade (3-20, Default: 8): Bars to wait after exit before next entry allowed Prevents overtrading and revenge trading 3 = Minimal cooldown (active trading) 8 = Balanced (recommended) 15-20 = Conservative (position trading) Entropy Length (10-50, Default: 20): Lookback period for market order/disorder calculation Lower = more responsive to regime changes (noisy) Higher = more stable regime detection (laggy) 20 = works across most timeframes Momentum Length (5-30, Default: 14): Period for RSI/ROC calculations 14 = standard (RSI default) Lower = more signals, less reliable Higher = fewer signals, more reliable Structure Length (20-100, Default: 50): Lookback for support/resistance swing range 20 = short-term swings (day trading) 50 = medium-term structure (recommended) 100 = major structure (position trading) Trend EMA Length (20-100, Default: 50): EMA period for trend detection and direction bias 20 = short-term trend (responsive) 50 = medium-term trend (recommended) 100 = long-term trend (position trading) ATR Period (5-30, Default: 14): Period for volatility measurement 14 = standard ATR Lower = more responsive to vol changes Higher = smoother vol calculation 📊 Volatility Scaling (DVS) Settings Enable DVS (Default: ON): Dynamic volatility scaling for adaptive stop/target placement Highly recommended to leave ON OFF only for testing fixed-distance stops DVS Method (Default: Ensemble): ATR Ratio: Simple, fast, single-method (good for beginners) Parkinson: High-low range based (good for intraday) Garman-Klass: OHLC based (sophisticated, considers gaps) Ensemble: Median of all three (RECOMMENDED - most robust) DVS Memory (20-200, Default: 100): Lookback for baseline volatility comparison 20 = very responsive to vol changes (can overreact) 100 = balanced adaptation (recommended) 200 = slow, stable baseline (minimizes false vol signals) DVS Sensitivity (0.3-1.5, Default: 0.7): How much volatility affects scaling (power-law exponent) 0.3 = Conservative, heavily dampens vol impact (cube root) 0.5 = Moderate dampening (square root) 0.7 = Balanced response (recommended) 1.0 = Linear, full 1:1 vol response 1.5 = Aggressive, amplified response (exponential) 🔬 Walk-Forward Optimization Settings Enable WFO (Default: ON): Out-of-sample validation to prevent overfitting Highly recommended to leave ON OFF only for testing or if you want unvalidated strategies Training Window (100-500, Default: 250): Bars for in-sample optimization 100 = fast validation, less data (risky) 250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min 500 = patient validation, more data (conservative) Testing Window (30-200, Default: 75): Bars for out-of-sample validation Should be ~30% of training window 30 = minimal test (fast validation) 75 = balanced (recommended) 200 = extensive test (very conservative) Min Trades for Validation (3-15, Default: 5): Required trades in BOTH training AND testing periods 3 = minimal sample (risky, fast validation) 5 = balanced (recommended) 10+ = conservative (slow validation, high confidence) WFO Efficiency Threshold (0.3-0.9, Default: 0.55): Minimum test/train performance ratio required 0.30 = Very loose (test must be 30% as good as training) 0.55 = Balanced (recommended) - test must be 55% as good 0.70+ = Strict (test must closely match training) Higher = fewer validated strategies, lower risk of overfitting 🎨 Premium Visuals Settings Visual Theme: Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple) Carbon Fiber: Industrial look (blue/red/gray) Quantum Blue: Quantum computing (blue/purple/pink) Aurora: Northern lights (teal/orange/purple) ⚡ Gradient Probability Cloud (Default: ON): Multi-layer gradient showing signal buildup Turn OFF if chart lags or for cleaner look Cloud Gradient Layers (3-15, Default: 7): More layers = smoother gradient, more CPU intensive Fewer layers = faster, blockier appearance 🎗️ Population Fitness Ribbon (Default: ON): Histogram showing fitness distribution Turn OFF for cleaner chart Ribbon Layers (5-20, Default: 10): More layers = finer fitness detail Fewer layers = simpler histogram ⭕ Signal Confidence Halo (Default: ON): Circular indicator around entry signals Size/brightness scales with probability Minimal performance cost 🔬 Evolution Event Markers (Default: ON): Diamond (spawn) and X (cull) markers Shows genetic algorithm activity Minimal performance cost 🎯 Stop/Target Lines (Default: ON): Shows shadow portfolio stop/target levels Turn OFF for cleaner chart (recommended for screenshots/presentations) 📊 Enhanced Dashboard (Default: ON): Comprehensive metrics panel Should stay ON unless you want zero overlays 🔍 Diagnostics Panel (Default: OFF): Detailed signal rejection tracking Turn ON when optimizing settings Turn OFF during normal use (slight performance cost) 📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR Phase 1: Initial Setup & Learning Add AGE to your chart Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio) Works on: 5min (day trading), 4H (swing trading), Daily (position trading) Load 1000+ bars for sufficient evolution history Let the population evolve (100+ bars minimum) First 50 bars: Random exploration, poor results expected Bars 50-150: Population converging, fitness improving Bars 150+: Stable performance, validated strategies emerging Watch the dashboard metrics Population should grow toward max capacity Generation number should advance regularly Validated strategies counter should increase Best fitness should trend upward toward 0.50-0.70 range Observe evolution markers Diamond markers (cyan) = new strategies spawning X markers (red) = weak strategies being culled Frequent early activity = healthy evolution Activity slowing = population stabilizing Be patient. Evolution takes time. Don't judge performance before 150+ bars. Phase 2: Signal Observation Watch signals form Gradient cloud builds up 2-3 bars before entry Cloud brightness = probability strength Cloud thickness = signal persistence Check signal quality Look at confidence halo size when entry marker appears Large bright halo = elite setup (85%+) Medium halo = strong setup (75-85%) Small halo = good setup (65-75%) Verify market conditions Check trend EMA color (green = uptrend, red = downtrend, gray = choppy) Check background tint (green = trending, red = volatile, clear = choppy) Trending background + aligned signal = ideal conditions Review dashboard signal status Current Signal column shows: Status (Long/Short/Forming/Waiting) Confidence % (actual probability value) Quality assessment (Elite/Strong/Good) Confluence score (2/3 or 3/3 preferred) Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable. Phase 3: Manual Trading Execution When Long Signal Fires: Verify confidence level (dashboard or halo size) Confirm trend alignment (EMA sloping up, green color) Check regime (preferably trending or choppy, avoid volatile) Enter long manually on your broker platform Set stop loss at displayed stop line level (if lines enabled), or use your own risk management Set take profit at displayed target line level, or trail manually Monitor position - exit if X marker appears (signal reversal) When Short Signal Fires: Same verification process Confirm downtrend (EMA sloping down, red color) Enter short manually Use displayed stop/target levels or your own AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH. Phase 4: Set Up Alerts (Never Miss a Signal) Right-click on indicator name in legend Select "Add Alert" Choose condition: "AGE Long" = Long entry signal fired "AGE Short" = Short entry signal fired "AGE Exit" = Position reversal/exit signal Set notification method: Sound alert (popup on chart) Email notification Webhook to phone/trading platform Mobile app push notification Name the alert (e.g., "AGE BTCUSD 15min Long") Save alert Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts. Phase 5: Monitor Population Health Weekly Review: Check dashboard Population column: Active count should be near max (6-8 of 8) Validated count should be >50% of active Generation should be advancing (1-2 per week typical) Check dashboard Performance column: Aggregate win rate should be >50% (target: 55-65%) Total P&L should be positive (may fluctuate) Best fitness should be >0.50 (target: 0.55-0.70) MAS should be declining slowly (normal adaptation) Check Active Strategy column: Selected strategy should be validated (✓ VAL) Personal fitness should match best fitness Trade count should be accumulating Win rate should be >50% Warning Signs: Zero validated strategies after 300+ bars = settings too strict or market unsuitable Best fitness stuck <0.30 = population struggling, consider parameter adjustment No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset) Aggregate win rate <45% sustained = system not working on this instrument/timeframe Health Check Pass: 50%+ strategies validated Best fitness >0.50 Aggregate win rate >52% Regular spawn/cull activity Selected strategy validated Phase 6: Optimization (If Needed) Enable Diagnostics Panel (bottom-right) for data-driven tuning: Problem: Too Few Signals Evaluated: 200 Passed: 8 (4%) ⨯ Probability: 140 (70%) Solutions: Lower min probability: 65% → 60% or 55% Reduce min confluence: 2 → 1 Lower base persistence: 2 → 1 Increase mutation rate temporarily to explore new genes Check if regime filter is blocking signals (⨯ Regime high?) Problem: Too Many False Signals Evaluated: 200 Passed: 90 (45%) Win rate: 42% Solutions: Raise min probability: 65% → 70% or 75% Increase min confluence: 2 → 3 Raise base persistence: 2 → 3 Enable WFO if disabled (validates strategies before use) Check if volume filter is being ignored (⨯ Volume low?) Problem: Counter-Trend Losses ⨯ Trend: 5 (only 5% rejected) Losses often occur against trend Solutions: System should already filter trend opposition May need stronger trend requirement Consider only taking signals aligned with higher timeframe trend Use longer trend EMA (50 → 100) Problem: Volatile Market Whipsaws ⨯ Regime: 100 (50% rejected by volatile regime) Still getting stopped out frequently Solutions: System is correctly blocking volatile signals Losses happening because vol filter isn't strict enough Consider not trading during volatile periods (respect the regime) Or disable regime filter and accept higher risk Optimization Workflow: Enable diagnostics Run 200+ bars with current settings Analyze rejection patterns and win rate Make ONE change at a time (scientific method) Re-run 200+ bars and compare results Keep change if improvement, revert if worse Disable diagnostics when satisfied Never change multiple parameters at once - you won't know what worked. Phase 7: Multi-Instrument Deployment AGE learns independently on each chart: Recommended Strategy: Deploy AGE on 3-5 different instruments Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold) Each learns optimal strategies for that instrument's personality Take signals from all 5 charts Natural diversification reduces overall risk Why This Works: When one market is choppy, others may be trending Different instruments respond to different news/catalysts Portfolio-level win rate more stable than single-instrument Evolution explores different parameter spaces on each chart Setup: Same settings across all charts (or customize if preferred) Set alerts for all Take every validated signal across all instruments Position size based on total account (don't overleverage any single signal) ⚠️ REALISTIC EXPECTATIONS - CRITICAL READING What AGE Can Do ✅ Generate probability-weighted signals using genetic algorithms ✅ Evolve strategies in real-time through natural selection ✅ Validate strategies on out-of-sample data (walk-forward optimization) ✅ Adapt to changing market conditions automatically over time ✅ Provide comprehensive metrics on population health and signal quality ✅ Work on any instrument, any timeframe, any broker ✅ Improve over time as weak strategies are culled and fit strategies breed What AGE Cannot Do ❌ Win every trade (typical win rate: 55-65% at best) ❌ Predict the future with certainty (markets are probabilistic, not deterministic) ❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize) ❌ Guarantee profits under all market conditions ❌ Replace your trading discipline and risk management ❌ Execute trades automatically (this is an indicator, not a strategy) ❌ Prevent all losses (drawdowns are normal and expected) ❌ Adapt instantly to regime changes (re-learning takes 50-100 bars) Performance Realities Typical Performance After Evolution Stabilizes (150+ bars): Win Rate: 55-65% (excellent for trend-following systems) Profit Factor: 1.5-2.5 (realistic for validated strategies) Signal Frequency: 5-15 signals per 100 bars (quality over quantity) Drawdown Periods: 20-40% of time in equity retracement (normal trading reality) Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal) Evolution Timeline: Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet Bars 50-150: Population converging, fitness climbing - results improving Bars 150-300: Stable performance, most strategies validated - consistent results Bars 300+: Mature population, optimal genes dominant - best results Market Condition Dependency: Trending Markets: AGE excels - clear directional moves, high-probability setups Choppy Markets: AGE struggles - fewer signals generated, lower win rate Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades Market Regime Changes: When market shifts from trending to choppy overnight Validated strategies can become temporarily invalidated AGE will adapt through evolution, but not instantly Expect 50-100 bar re-learning period after major regime shifts Fitness may temporarily drop then recover This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on: Patience during learning periods (don't abandon after 3 losses) Proper position sizing (risk 0.5-2% per trade, not 10%) Following signals consistently (cherry-picking defeats statistical edge) Not abandoning system prematurely (give it 200+ bars minimum) Understanding probability (60% win rate means 40% of trades WILL lose) Respecting market conditions (trending = trade more, choppy = trade less) Managing emotions (AGE is emotionless, you need to be too) Expected Drawdowns: Single-strategy max DD: 10-20% of equity (normal) Portfolio across multiple instruments: 5-15% (diversification helps) Losing streaks: 3-5 consecutive losses expected periodically No indicator eliminates risk. AGE manages risk through: Quality gates (rejecting low-probability signals) Confluence requirements (multi-indicator confirmation) Persistence requirements (no knee-jerk reactions) Regime awareness (reduced trading in chaos) Walk-forward validation (preventing overfitting) But it cannot prevent all losses. That's inherent to trading. 🔧 TECHNICAL SPECIFICATIONS Platform: TradingView Pine Script v5 Indicator Type: Overlay indicator (plots on price chart) Execution Type: Signals only - no automatic order placement Computational Load: Moderate to High (genetic algorithms + shadow portfolios) 8 strategies × shadow portfolio simulation = significant computation Premium visuals add additional load (gradient cloud, fitness ribbon) TradingView Resource Limits (Built-in Caps): Max Bars Back: 500 (sufficient for WFO and evolution) Max Labels: 100 (plenty for entry/exit markers) Max Lines: 150 (adequate for stop/target lines) Max Boxes: 50 (not heavily used) Max Polylines: 100 (confidence halos) Recommended Chart Settings: Timeframe: 15min to 1H (optimal signal/noise balance) 5min: Works but noisier, more signals 4H/Daily: Works but fewer signals Bars Loaded: 1000+ (ensures sufficient evolution history) Replay Mode: Excellent for testing without risk Performance Optimization Tips: Disable gradient cloud if chart lags (most CPU intensive visual) Disable fitness ribbon if still laggy Reduce cloud layers from 7 to 3 Reduce ribbon layers from 10 to 5 Turn off diagnostics panel unless actively tuning Close other heavy indicators to free resources Browser/Platform Compatibility: Works on all modern browsers (Chrome, Firefox, Safari, Edge) Mobile app supported (full functionality on phone/tablet) Desktop app supported (best performance) Web version supported (may be slower on older computers) Data Requirements: Real-time or delayed data both work No special data feeds required Works with TradingView's standard data Historical + live data seamlessly integrated 🎓 THEORETICAL FOUNDATIONS AGE synthesizes advanced concepts from multiple disciplines: Evolutionary Computation Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor Tournament Selection: Fitness-based parent selection with diversity preservation Crossover Operators: Fitness-weighted gene recombination from two parents Mutation Operators: Random gene perturbation for exploration of new parameter space Elitism: Preservation of top N performers to prevent loss of best solutions Adaptive Parameters: Different mutation rates for historical vs. live phases Technical Analysis Support/Resistance: Price structure within swing ranges Trend Following: EMA-based directional bias Momentum Analysis: RSI, ROC, MACD composite indicators Volatility Analysis: ATR-based risk scaling Volume Confirmation: Trade activity validation Information Theory Shannon Entropy (1948): Quantification of market order vs. disorder Signal-to-Noise Ratio: Directional information vs. random walk Information Content: How much "information" a price move contains Statistics & Probability Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization Out-of-Sample Validation: Testing on unseen data to prevent overfitting Monte Carlo Principles: Shadow portfolio simulation with realistic execution Expectancy Theory: Win rate × avg win - loss rate × avg loss Probability Distributions: Signal confidence quantification Risk Management ATR-Based Stops: Volatility-normalized risk per trade Volatility Regime Detection: Market state classification (trending/choppy/volatile) Drawdown Control: Peak-to-trough equity measurement R-Multiple Normalization: Performance measurement in risk units Machine Learning Concepts Online Learning: Continuous adaptation as new data arrives Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown) Exploration vs. Exploitation: Balance between trying new strategies and using proven ones Overfitting Prevention: Walk-forward validation as regularization Novel Contribution: AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation. Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself. The combination of: Genetic algorithm population management Shadow portfolio simulation for realistic fitness evaluation Walk-forward validation to prevent overfitting Multi-indicator confluence for signal quality Dynamic volatility scaling for adaptive risk ...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches. 🏗️ DEVELOPMENT NOTES This project represents months of intensive development, facing significant technical challenges: Challenge 1: Making Genetics Actually Work Early versions spawned garbage strategies that polluted the gene pool: Random gene combinations produced nonsensical parameter sets Weak strategies survived too long, dragging down population No clear convergence toward optimal solutions Solution: Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown) Elite preservation (top 2 always protected) Walk-forward validation (unproven strategies penalized 30%) Tournament selection (fitness-weighted breeding) Adaptive culling (MAS decay creates increasing selection pressure) Challenge 2: Balancing Evolution Speed vs. Stability Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes. Solution: Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals) Adaptive mutation rates: 20% historical, 8% live Spawn/cull ratio: Always 2:1 to prevent population collapse Challenge 3: Shadow Portfolio Accuracy Needed realistic trade simulation without lookahead bias: Can't peek at future bars for exits Must track multiple portfolios simultaneously Stop/target checks must use bar's high/low correctly Solution: Entry on close (realistic) Exit checks on current bar's high/low (realistic) Independent position tracking per strategy Cooldown periods to prevent unrealistic rapid re-entry ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes Challenge 4: Pine Script Compilation Limits Hit TradingView's execution limits multiple times: Too many array operations Too many variables Too complex conditional logic Solution: Optimized data structures (single DNA array instead of 8 separate arrays) Minimal visual overlays (only essential plots) Efficient fitness calculations (vectorized where possible) Strategic use of barstate.islast to minimize dashboard updates Challenge 5: Walk-Forward Implementation Standard WFO is difficult in Pine Script: Can't easily "roll forward" through historical data Can't re-optimize strategies mid-stream Must work in real-time streaming environment Solution: Age-based phase detection (first 250 bars = training, next 75 = testing) Separate metric tracking for train vs. test Efficiency calculation at fixed interval (after test period completes) Validation flag persists for strategy lifetime Challenge 6: Signal Quality Control Early versions generated too many signals with poor win rates: Single indicators produced excessive noise No trend alignment No regime awareness Instant entries on single-bar spikes Solution: Three-layer confluence system (entropy + momentum + structure) Minimum 2-of-3 agreement requirement Trend alignment checks (penalty for counter-trend) Regime-based probability adjustments Persistence requirements (signals must hold multiple bars) Volume confirmation Quality gate (probability + confluence thresholds) The Result A system that: Truly evolves (not just parameter sweeps) Truly validates (out-of-sample testing) Truly adapts (ongoing competition and breeding) Stays within TradingView's platform constraints Provides institutional-quality signals Maintains transparency (full metrics dashboard) Development time: 3+ months of iterative refinement Lines of code: ~1500 (highly optimized) Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL Test timeframes: 5min, 15min, 1H, Daily 🎯 FINAL WORDS The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool. This is evolution in action on your charts. You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation. AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime. Use it on any instrument. Any timeframe. Any market condition. AGE will adapt. This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much . Trust the process. Respect the evolution. Let Darwin work. "In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change." Taking you to school. — Dskyz, Trade with insight. Trade with anticipation. — Happy Holiday's
Indicador Pine Script®
por DskyzInvestments
2
Adaptive SuperTrend - Multi-Method# 📊 Adaptive SuperTrend - Multi-Method with Advanced Analytics ## 🎯 Overview The **Adaptive SuperTrend - Multi-Method** is a sophisticated trading indicator that enhances the traditional SuperTrend by dynamically adjusting its parameters based on market conditions. Unlike static SuperTrend indicators, this version adapts to volatility changes, providing more reliable signals across different market regimes. ## ✨ Key Features ### 🤖 7 Adaptive Methods Choose from multiple adaptation strategies or use the powerful Hybrid mode that combines all methods: 1. **Percentile-Based Adaptation** - Adjusts multiplier based on ATR percentile ranking - Tightens during extreme volatility, widens during calm periods - Lookback: 100 bars (customizable) 2. **Volatility Regime Classification** - Categorizes market into Low/Normal/High volatility regimes - Applies different multipliers for each regime - Default: Low=4.0x, Normal=2.5x, High=1.5x 3. **Z-Score Normalization** - Uses statistical Z-score to normalize ATR - Adapts to volatility outliers intelligently - Sensitivity: 0.3 (adjustable) 4. **Dynamic Period Adjustment** - Blends short and long ATR periods based on volatility - Responsive in volatile markets, stable in calm markets - Period range: 7-20 bars 5. **Rate of Change Method** - Adjusts based on ATR's rate of change - Detects accelerating/decelerating volatility - Lookback: 20 bars 6. **Multi-Timeframe Comparison** - Compares current timeframe ATR with higher timeframe - Provides macro-context awareness - Default HTF: Daily 7. **Hybrid Approach** ⭐ RECOMMENDED - Combines all 6 methods with equal weighting - Smoothed with EMA for stability - Best overall performance ### 📈 Professional Statistics Panel A comprehensive performance tracking panel with ML Fusion-inspired color scheme: **Features:** - 💼 **Current Position**: Live LONG/SHORT status with entry price - 📊 **Total Points**: Cumulative P&L for selected period (default: 60 days) - 💰 **Current P&L**: Unrealized profit/loss with percentage - 🟢 **Long Stats**: Separate tracking for long trades - 🔴 **Short Stats**: Separate tracking for short trades - 📈 **Averages**: Average points per trade (overall, long, short) - 📅 **Date Range**: Start and end dates of tracking period **Customizable Options:** - Lookback period: 1-365 days (default: 60 days) - Table position: Top Left/Right, Bottom Left/Right - Toggle date range display on/off ### 🎨 Visual Features - **Color-Coded Signals**: Clear buy (green) and sell (red) markers - **Trend Background**: Subtle background coloring for trend direction - **SuperTrend Line**: Dynamic color based on current trend - **Price Fill**: Shaded area between price and SuperTrend - **Vibrant Colors**: Professional Material Design color palette ### 📊 Information Panel Real-time display of: - Active adaptation method - Current ATR value - ATR percentile ranking - Active multiplier vs base multiplier - Volatility regime (Low/Normal/High) - ATR Z-Score - Current trend direction ## 🔧 How to Use ### Quick Start 1. Add indicator to your chart 2. Choose adaptation method (start with "Hybrid") 3. Monitor the statistics panel for performance 4. Use signals for entry/exit points ### Recommended Settings **For Intraday Trading:** - Method: Hybrid or Dynamic Period - Base ATR Period: 10 - Base Multiplier: 2.5-3.0 - P&L Tracking: 30 days **For Swing Trading:** - Method: Hybrid or Multi-Timeframe - Base ATR Period: 14 - Base Multiplier: 3.0-4.0 - P&L Tracking: 90 days **For Scalping:** - Method: Rate of Change or Z-Score - Base ATR Period: 7 - Base Multiplier: 2.0-2.5 - P&L Tracking: 7-14 days ### Signal Interpretation ✅ **BUY Signal**: Triangle up below bar - Enter long position - Place stop loss below SuperTrend line ❌ **SELL Signal**: Triangle down above bar - Exit long / Enter short position - Place stop loss above SuperTrend line ## ⚙️ Input Parameters ### Basic Settings - **Base ATR Period**: Default 10 (1-50) - **Base Multiplier**: Default 3.0 (0.1-10.0) ### Method-Specific Settings Each of the 7 methods has its own customizable parameters for fine-tuning. ### Display Settings - **Show Volatility Regime**: Toggle regime display - **Show ATR Info Panel**: Toggle information panel - **Show Statistics Panel**: Toggle performance stats - **Stats Table Position**: Choose corner placement - **P&L Tracking Period**: 1-365 days (default: 60) - **Show P&L Date Range**: Toggle date range display - **Bullish Color**: Customize trend-up color - **Bearish Color**: Customize trend-down color ## 📊 Statistics Tracking The indicator automatically tracks: - **Entry Points**: Recorded on every trend change - **Exit Points**: Calculated on opposite signal - **Points Gained/Lost**: Per trade and cumulative - **Long vs Short Performance**: Separate analytics - **Trade Count**: Total, long, and short trades - **Average Performance**: Overall and per direction - **Time-Based Filtering**: Only shows trades within lookback period ## 🎯 Advantages Over Standard SuperTrend 1. **Adaptive to Market Conditions**: No more whipsaws in ranging markets or missed trends in volatile markets 2. **Multiple Adaptation Strategies**: Choose the method that fits your market and timeframe 3. **Comprehensive Analytics**: Track your performance with detailed statistics 4. **Professional Presentation**: Clean, organized display with Material Design colors 5. **Flexible Configuration**: Highly customizable for any trading style 6. **Real-Time Monitoring**: Live P&L tracking and performance metrics ## 🔔 Alerts Built-in alert conditions for: - Buy Signal (trend change to bullish) - Sell Signal (trend change to bearish) - Trend Change (any direction change) Set up TradingView alerts to get notified on your phone or email when signals occur. ## 💡 Pro Tips 1. **Combine with Volume**: Use with volume indicators for confirmation 2. **Multiple Timeframes**: Add on multiple timeframes for confluence 3. **Risk Management**: Always use stop losses at SuperTrend line 4. **Backtest First**: Test on historical data before live trading 5. **Monitor Statistics**: Track your win rate and average gains 6. **Adjust for Market**: Switch methods based on market conditions 7. **Use Hybrid Mode**: When unsure, Hybrid mode provides balanced adaptation ## 📝 Version Notes **Version 1.0** - 7 adaptive methods with Hybrid mode - Professional statistics panel with P&L tracking - Configurable lookback period (1-365 days) - Date range display - Material Design color scheme - Real-time performance analytics - Multiple table position options ## ⚠️ Disclaimer This indicator is for educational and informational purposes only. It should not be considered as financial advice. Always do your own research and consider consulting with a financial advisor before making trading decisions. Past performance does not guarantee future results. --- **Happy Trading! 🚀📈** --- ## 🏷️ Tags #SuperTrend #Adaptive #Volatility #TrendFollowing #ATR #Statistics #Analytics #PnL #Trading #Technical #Indicators #MultiMethod #Swing #Intraday #Scalping #RiskManagement
Indicador Pine Script®
por QuantCreative
25
Kinetic Scalper [BULLBYTE]KINETIC SCALPER - ADVANCED MOMENTUM & CONFLUENCE TRADING SYSTEM A SOPHISTICATED MULTI-FACTOR ANALYSIS INDICATOR FOR PRECISION ENTRIES The Kinetic Scalper is a comprehensive trading analysis tool that combines volume-weighted momentum calculations, multi-oscillator divergence detection, and a proprietary 15-factor confluence scoring system to identify high-probability reversal setups across all timeframes. WHAT MAKES THIS INDICATOR ORIGINAL This is NOT a simple mashup of existing indicators. The Kinetic Scalper features a completely custom momentum engine called the "Kinetic Pulse" - a volume-weighted momentum oscillator with Fisher Transform normalization that fundamentally differs from standard RSI or other momentum indicators. Every component feeds into a unified algorithmic framework designed specifically for this system. KEY INNOVATIONS: KINETIC PULSE ENGINE Unlike standard RSI which uses simple price changes, the Kinetic Pulse applies: → Volume weighting to price movements (high-volume moves carry more weight) → EMA smoothing instead of traditional SMA (faster response to changes) → Fisher Transform normalization for improved signal clarity → Adaptive period adjustment based on current volatility regime → Result: A momentum oscillator that responds to conviction, not just price noise 15-FACTOR CONFLUENCE SCORING SYSTEM Every signal is graded based on the number of confirming factors present: → Momentum position (oversold/overbought extremes) → Momentum velocity (direction change confirmation) → Momentum acceleration (strength of reversal) → Multi-oscillator divergence (price vs. 3 oscillators) → Volume confirmation (above-average participation) → Volume delta analysis (buying vs. selling pressure) → Higher timeframe alignment (trend confirmation from larger timeframe) → Session timing (major forex session awareness) → Structure clearance (clear path to profit targets) → Support/resistance proximity (confluence with key levels) → Market regime filtering (trending vs. choppy conditions) Signals are graded A+, A, or B based on how many factors align: • CONSERVATIVE MODE: A+ requires 12+ factors, A requires 9+, B requires 7+ • BALANCED MODE: A+ requires 10+ factors, A requires 7+, B requires 5+ • AGGRESSIVE MODE: A+ requires 8+ factors, A requires 5+, B requires 3+ TRADE ANALYSIS STATE MACHINE A sophisticated monitoring system that tracks trade conditions in real-time using: → 5-state analysis framework (Factors Aligned / Positive Bias / Mixed Signals / Factors Weakening / Negative Bias) → Hysteresis-based transitions (different thresholds to enter vs. exit states) → Confidence smoothing with EMA (reduces noise, prevents flip-flopping) → Minimum commitment periods before state changes → Override logic for significant events (near TP/SL, momentum reversals) → Result: Stable, actionable guidance that doesn't change on every bar INSTRUMENT-AWARE CALIBRATION Automatically detects what you're trading and applies optimized parameters: → Forex Majors: Standard ATR, high session weight → Forex Crosses: Tighter stops, moderate session weight → Crypto: Wider stops (1.8x multiplier), reduced session weight (24/7 markets) → Indices: Moderate-wide stops, high session weight → Commodities: Moderate stops, moderate session weight WHAT THIS INDICATOR DOES The Kinetic Scalper is designed to identify high-confluence reversal opportunities by analyzing multiple dimensions of market behavior simultaneously. CORE FUNCTIONS: 1. SIGNAL GENERATION → Identifies potential reversal points at oversold/overbought extremes → Confirms with multi-oscillator divergence detection → Validates with volume, higher timeframe, and structural analysis → Filters out low-probability setups automatically → Grades signals based on total confluence factors present 2. AUTOMATED TRADE TRACKING → Calculates structure-based or ATR-based stop loss levels → Projects take profit targets using risk-to-reward ratios → Monitors live position status (P/L, distance to targets, R-multiple) → Tracks TP1 and TP2 hits automatically → Displays outcome markers (TP HIT, PARTIAL WIN, STOPPED) 3. REAL-TIME CONDITION MONITORING → Analyzes 6 factor categories during active trades → Provides confidence scoring (0-100 scale) → Generates actionable guidance based on current market state → Alerts when conditions deteriorate or improve → Helps with trade management decisions 4. COMPREHENSIVE MARKET ANALYSIS → Session detection (Asian, London, New York, Overlap) → Volatility regime identification (Low, Normal, High, Extreme) → Trend state classification (Trending Up/Down, Ranging, Transitioning) → Volume analysis (relative volume and delta approximation) → Choppiness filtering (blocks signals in ranging markets) WHY USE THIS INDICATOR PROBLEM: Most momentum indicators generate too many false signals at extremes. SOLUTION: The Kinetic Scalper requires MULTIPLE confirming factors before generating a signal, dramatically reducing noise and focusing on high-confluence setups. ADVANTAGES: ✓ QUALITY OVER QUANTITY → Signal grading ensures you can filter for only the highest-quality setups → A+ signals have 10-12+ confirming factors aligned → Cooldown periods prevent over-trading the same move ✓ COMPLETE TRADE FRAMEWORK → Entry signals with confluence justification → Calculated stop loss based on market structure or ATR → Two profit targets with clear risk-to-reward ratios → Live trade monitoring with factor analysis → Outcome tracking and visual markers ✓ ADAPTIVE TO MARKET CONDITIONS → Volatility-based period adjustment for momentum calculations → Instrument-specific ATR multipliers → Session awareness for forex traders → Higher timeframe trend filtering → Automatic regime detection (trending vs. choppy) ✓ TRANSPARENT METHODOLOGY → Every input has detailed tooltips explaining its purpose → Signal tooltips show exactly why a signal was generated → Dashboard displays all relevant market conditions → Factor scores are visible during trades → No "black box" mystery calculations ✓ NON-REPAINTING & RELIABLE → All signals use barstate.isconfirmed (only on closed bars) → Higher timeframe data uses lookahead_off with historical offset → No future data access or repainting behavior → What you see is what you get - signals don't disappear or move HOW THE INDICATOR WORKS SIGNAL GENERATION PROCESS: STEP 1: MOMENTUM ANALYSIS The Kinetic Pulse engine calculates volume-weighted momentum: → Price changes are weighted by volume ratio vs. 20-bar average → High-volume moves have more influence on the oscillator → Gains and losses are smoothed using EMA (not SMA like RSI) → Fisher Transform is applied for normalization to 0-100 scale → Result: Momentum reading that emphasizes conviction, not noise STEP 2: REVERSAL DETECTION The indicator looks for potential reversal conditions: → Kinetic Pulse reaching oversold zone (below dynamic lower threshold) → Momentum velocity turning positive after being negative (for longs) → OR bullish divergence detected on multiple oscillators → Price making lower lows while oscillators make higher lows = divergence STEP 3: MULTI-OSCILLATOR DIVERGENCE CONFIRMATION Divergence is validated across three sources: → Kinetic Pulse divergence → CCI divergence → Stochastic divergence → Multiple oscillators confirming divergence increases signal reliability STEP 4: CONFLUENCE FACTOR SCORING The system evaluates all 15 possible confirming factors: → Momentum position: Is pulse oversold/overbought? (+0 to +2 points) → Momentum direction: Is velocity reversing? (+0 to +2 points) → Momentum acceleration: Is reversal strengthening? (+0 to +1 point) → Divergence count: How many oscillators show divergence? (+0 to +2 points) → Volume strength: Is volume above 1.3x average? (+0 to +1 point) → Volume delta: Is cumulative delta positive/negative? (+0 to +1 point) → HTF alignment: Does higher timeframe support direction? (+0 to +2 points) → Session timing: Is it a prime trading session? (+0 to +1 point) → Clear air: Is path to targets clear of obstacles? (+0 to +1 point) → Structure confluence: Are we near support/resistance? (+0 to +1 point) → Market regime: Is market trending, not choppy? (+0 to +1 point) Total possible score: 15 points Minimum for signal: 3-12 points depending on sensitivity mode STEP 5: FILTER VALIDATION Before generating a signal, additional checks are performed: → Volume must be above minimum threshold (if filter enabled) → Higher timeframe must not oppose the signal direction (if filter enabled) → Target path must be clear of major resistance/support (if filter enabled) → Volatility must not be EXTREME (blocks signals in chaos) → Risk-to-reward ratio must meet minimum requirement → Cooldown period must have elapsed since last signal STEP 6: SIGNAL GRADING If all filters pass, the signal is graded based on score: → A+ Grade: Highest confluence (8-12+ factors depending on sensitivity) → A Grade: High confluence (5-9+ factors) → B Grade: Moderate confluence (3-7+ factors) Only graded signals (A+, A, or B) are displayed. STEP 7: TRADE LEVEL CALCULATION Stop loss and targets are calculated automatically: STOP LOSS METHODS: • Structure-Based: Uses recent swing low/high with ATR buffer, constrained by min/max ATR limits • ATR-Based: Pure ATR multiplier with min/max constraints • Fixed ATR: Simple ATR multiplier, no adjustments TARGET CALCULATION: • TP1: Entry ± (Stop Distance × Target 1 R:R) • TP2: Entry ± (Stop Distance × Target 2 R:R) • Default: TP1 at 1.0 R:R (1:1), TP2 at 2.0 R:R (1:2) STEP 8: TRADE MONITORING Once a signal is taken, the indicator tracks: → Current P/L in ticks and R-multiples → Distance to each target in ATR units → Distance to stop loss in ATR units → TP1 hit detection (marks with label, updates lines) → TP2 hit detection (closes trade, marks outcome) → Stop loss hit detection (closes trade, differentiates partial vs. full loss) STEP 9: FACTOR ANALYSIS (DURING TRADES) The Trade Analysis Panel monitors 6 key factor categories: → Momentum: Is momentum still aligned with trade direction? (-15 to +15 pts) → Position: Current R-multiple position (-12 to +12 pts) → Volume: Is volume still supportive? (-6 to +6 pts) → HTF Alignment: Does HTF still support trade? (-6 to +8 pts) → Target Proximity: How close are we to targets? (0 to +10 pts) → Stop Proximity: Are we dangerously close to stop? (-15 to +3 pts) Raw scores are summed and smoothed using 5-bar EMA to create Confidence Score (0-100). STEP 10: STATE MACHINE TRANSITIONS Based on smoothed confidence, the system transitions between 5 states: → FACTORS ALIGNED (72+): Everything looks good → POSITIVE BIAS (58-72): Conditions favorable → MIXED SIGNALS (48-58): Neutral conditions → FACTORS WEAKENING (22-48): Concerning signals → NEGATIVE BIAS (<22): Poor conditions Hysteresis prevents rapid flipping between states (different entry/exit thresholds). RECOMMENDED TIMEFRAMES & INSTRUMENTS TIMEFRAME VERSATILITY: Despite the name "Scalper," this indicator works on ALL timeframes: ✓ LOWER TIMEFRAMES (1m - 15m) → Ideal for: Scalping and very short-term trades → Expect: More signals, faster trades, requires active monitoring → Best for: Forex majors, liquid crypto pairs → Tip: Use Conservative sensitivity to reduce noise ✓ MID TIMEFRAMES (15m - 1H) → Ideal for: Intraday trading and day trading → Expect: Moderate signal frequency, 1-4 hour trade duration → Best for: Forex, indices, major crypto → Tip: Balanced sensitivity works well here ✓ HIGHER TIMEFRAMES (4H - Daily) → Ideal for: Swing trading and position trading → Expect: Fewer signals, higher-quality setups, multi-day trades → Best for: All instruments → Tip: Can use Aggressive sensitivity for more opportunities INSTRUMENT COMPATIBILITY: ✓ FOREX MAJORS (EUR/USD, GBP/USD, USD/JPY, etc.) → Auto-detected or manually select "Forex Major" → Session filtering is highly valuable here → London/NY overlap generates best signals ✓ FOREX CROSSES (EUR/GBP, AUD/NZD, etc.) → Auto-detected or manually select "Forex Cross" → Slightly tighter stops applied automatically → Session weight reduced vs. majors ✓ CRYPTOCURRENCIES (BTC, ETH, SOL, etc.) → Auto-detected or manually select "Crypto" → Wider stops (1.8x multiplier) due to volatility → Session filtering less relevant (24/7 markets) → Works well on both spot and perpetual futures ✓ INDICES (S&P 500, NASDAQ, DAX, etc.) → Auto-detected or manually select "Index" → Session opens (NY, London) are important → Moderate stop widths applied ✓ COMMODITIES (Gold, Silver, Oil, etc.) → Auto-detected or manually select "Commodity" → Moderate stops and session awareness → Works well on both spot and futures VISUAL ELEMENTS EXPLAINED SIGNAL MARKERS: The indicator offers 3 display styles (choose in settings): • PREMIUM STYLE (Default) → Signal appears below/above candles with connecting line → Background panel with grade badge (LONG , SHORT , etc.) → Entry price displayed → Direction arrow pointing to entry candle → Most informative, best for detailed analysis • MINIMAL STYLE → Simple dot marker with grade text next to it → Clean, unobtrusive design → Best for mobile devices or cluttered charts → Less visual noise • CLASSIC STYLE → Diamond marker with grade badge below/above → Traditional indicator aesthetic → Good balance between info and simplicity ALL STYLES INCLUDE: → Signal tooltips with complete trade plan details → Grade display (A+, A, or B) → Color coding (bright colors for A+, standard for A/B) SIGNAL TOOLTIP CONTENTS: When you hover over any signal marker, you'll see: → Signal direction and grade → Confluence score (actual points vs. required) → Reason for signal (divergence type, reversal pattern) → Complete trade plan (Entry, Stop, TP1, TP2) → Risk in ticks → Risk-to-reward ratios → Market conditions at signal (Pulse value, HTF status, Volume, Session) TRADE LEVEL LINES: When Trade Tracking is enabled: • ENTRY LINE (Yellow/Gold) → Solid horizontal line at entry price → Shaded zone around entry (±ATR buffer) → Label showing entry price → Extends 20-25 bars into future • STOP LOSS LINE (Orange/Red) → Dashed line at stop level → Label showing stop price and distance in ticks → Turns dotted and changes color after TP1 hit (breakeven implied) → Deleted when trade closes • TAKE PROFIT 1 LINE (Blue) → Dotted line at TP1 level → Label showing price and R:R ratio (e.g., "1:1.0") → Turns solid and changes to green when hit → Deleted after TP1 hit • TAKE PROFIT 2 LINE (Blue) → Solid line at TP2 level → Label showing price and R:R ratio (e.g., "1:2.0") → This is the "full win" target → Deleted when trade closes OUTCOME MARKERS: When trade milestones are reached: • - Green label appears when first target is touched • - Green label when second target is touched (trade complete) • - Red label if stop loss hit before any target • - Orange label if TP1 hit but then stopped out PREVIOUS DAY LEVELS: If enabled (Show Previous Day Levels): • PDH (Previous Day High) - Solid red/orange line → Label shows "PDH: " → Useful resistance reference for intraday trading • PDL (Previous Day Low) - Solid green line → Label shows "PDL: " → Useful support reference for intraday trading BACKGROUND TINTS: Subtle background colors indicate states: → Light green tint: Active long position being tracked → Light red tint: Active short position being tracked → Light orange tint: Extreme volatility warning (signals blocked) DASHBOARD GUIDE The indicator features TWO dashboard panels: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ MAIN DASHBOARD (Top Right by default) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHEN NO TRADE IS ACTIVE: → Bias: Current market bias (BULLISH, BEARISH, NEUTRAL, LEAN LONG/SHORT) → Based on Kinetic Pulse position and velocity → Helps you understand overall momentum direction → Pulse: Current Kinetic Pulse value (0-100 scale) → <30 = Oversold (potential long setups developing) → >70 = Overbought (potential short setups developing) → 40-60 = Neutral zone → Volatility: Current volatility regime (LOW, NORMAL, HIGH, EXTREME) → Calculated from ATR ratio vs. 100-period average → EXTREME volatility blocks all signals (too chaotic) → Trend: Market state classification → TREND UP / TREND DOWN: ADX > 25, directional movement clear → RANGING: ADX < 20, choppy conditions → TRANSITIONING: ADX 20-25, developing conditions → VOLATILE: Extreme ATR regime → Session: Current forex session → ASIAN (00:00-08:00 UTC) → LONDON (07:00-16:00 UTC) → NEW YORK (13:00-22:00 UTC) → LDN/NY (13:00-16:00 UTC) - Overlap period, highest volatility → OFF-HOURS: Outside major sessions → Volume: Current volume vs. 20-bar average → Displayed as multiplier (e.g., "1.45x" = 45% above average) → Green if >1.3x (high volume, bullish for signal quality) → Red if <0.8x (low volume, bearish for signal quality) → HTF: Higher timeframe analysis status → BULLISH: HTF momentum supports longs → BEARISH: HTF momentum supports shorts → NEUTRAL: No clear HTF direction → Best Score: Highest confluence score currently available → Shows both long and short scores → Format: " / " → Example: "8/7 " means long score is 8, threshold is 7, long is leading → Helps you anticipate which direction might signal next → PDH/PDL: Previous day high and low prices → Quick reference for intraday support/resistance WHEN TRADE IS ACTIVE: → Trade: Direction and grade (e.g., "LONG ") → Entry: Entry price of current trade → P/L: Current profit/loss → Shown in ticks and R-multiples → Format: "+45 | +0.75R" or "-20 | -0.35R" → Green when positive, red when negative → TP1: First target status → Shows price and distance if not hit → Shows "HIT" in green if reached → TP2: Second target price and distance → Stop: Stop loss price and current distance from stop → Bars: Number of bars since entry (trade duration) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TRADE ANALYSIS PANEL (Bottom Left by default) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This panel provides algorithmic analysis of market conditions. It does NOT provide investment advice or recommendations. WHEN NO TRADE IS ACTIVE: Shows scanning status and signal readiness: → Long/Short Readiness Gauges → Visual bar showing proximity to signal threshold → Score display (e.g., "8/7" means 8 points scored, 7 needed) → "RDY" indicator when threshold reached → Status Messages → "Scanning for setups..." - Normal scanning mode → "Long setup ready - cooldown: X bars" - Signal qualified but in cooldown → "Oversold conditions - watch for reversal" - Setup developing → "Choppy conditions detected" - Warning about market state → "Extreme volatility - signals blocked" - Safety filter active WHEN TRADE IS ACTIVE: Header shows current analysis state: → FACTORS ALIGNED (Green) - Everything looks good, confidence 72+ → POSITIVE BIAS (Light Green) - Conditions favorable, confidence 58-72 → MIXED SIGNALS (Blue) - Neutral conditions, confidence 48-58 → FACTORS WEAKENING (Orange) - Concerning signals, confidence 22-48 → NEGATIVE BIAS (Red) - Poor conditions, confidence <22 Confidence Score: → Displayed as percentage (0-100%) → Visual gauge (|||||.....) → Trend indicator (Rising, Falling, Stable) → Shows momentum of confidence change Factor Breakdown (if enabled): Shows 6 factor categories with individual scores: → Momentum: Is momentum aligned with trade? (-15 to +15 points) → Positive if velocity matches trade direction → Negative if momentum opposes trade → Position: Current R-multiple analysis (-12 to +12 points) → Positive if trade is in profit → Negative if underwater → Score increases as profit grows → Volume: Is volume supportive? (-6 to +6 points) → Positive if volume above average → Negative if volume weak → HTF Align: Higher timeframe status (-6 to +8 points) → Positive if HTF still supports trade direction → Negative if HTF turned against trade → Target: Proximity to profit targets (0 to +10 points) → Higher score when approaching targets → Bonus if TP1 already hit and near TP2 → Stop Dist: Distance from stop loss (-15 to +3 points) → Negative if dangerously close to stop (<0.3 ATR) → Positive if well away from stop (>1.5 ATR) Each factor shows: • Score value with +/- indicator • Trend symbol: + (improving), - (deteriorating), = (stable) • Visual gauge Guidance Messages: → "TARGET 2 APPROACHING" - TP2 within 0.3 ATR → "TARGET 1 APPROACHING" - TP1 within 0.3 ATR → "STOP PROXIMITY WARNING" - Stop within 0.3 ATR → "Factors aligned - Holding" - Positive state, stay in trade → "Conditions favorable" - Still looking good → "Conditions mixed - " - Neutral assessment → "Factors deteriorating" - Warning of weakening setup → "Confluence weakening - secure gains" - Consider exit if profitable COMPACT MODE (Mobile-Friendly): → Reduces panel size by showing only essential info → Factor icons instead of full breakdowns → Simplified guidance messages → Perfect for smaller screens SETTINGS GUIDE MASTER SETTINGS: Instrument Type → Purpose: Optimizes ATR multipliers and session weights for your asset → Options: Auto-Detect (recommended), Forex Major, Forex Cross, Crypto, Index, Commodity → Default: Auto-Detect → When to change: If auto-detection is incorrect for your symbol Signal Sensitivity → Purpose: Controls how many factors required before generating signals → Options: • Conservative: Requires 12+ for A+, 9+ for A, 7+ for B (fewer, highest quality) • Balanced: Requires 10+ for A+, 7+ for A, 5+ for B (recommended) • Aggressive: Requires 8+ for A+, 5+ for A, 3+ for B (more frequent) → Default: Balanced → When to change: If you want fewer signals (Conservative) or more opportunities (Aggressive) Enable Trade Signals → Purpose: Master on/off switch for signal generation → Default: ON → When to disable: If you only want to use the analysis dashboards without signals Enable Trade Tracking → Purpose: Tracks active trades and monitors conditions until TP/SL hit → Default: ON → When to disable: If you manage trades manually and don't want automatic tracking Show Entry/Stop/Target Levels → Purpose: Displays trade plan lines and labels on chart → Default: ON → When to disable: If you prefer clean charts or manage levels yourself DISPLAY SETTINGS: Color Theme → Purpose: Optimizes colors for your chart background → Options: Dark (for dark charts), Light (for light charts) → Default: Dark Signal Display Style → Purpose: Visual style of signal markers → Options: • Premium: Badge with line and background panel (most detailed) • Minimal: Simple dot with grade text (cleanest) • Classic: Diamond marker with badge (traditional) → Default: Premium Signal Distance → Purpose: How far signal labels appear from price bars (in ATR units) → Range: 0.5 to 10.0 → Default: 2.0 → When to adjust: Increase to 3.0-4.0 if signals hide behind candle wicks TP/SL Label Distance → Purpose: Spacing of price labels to prevent overlap → Range: 0.5 to 5.0 → Default: 1.5 Show Previous Day Levels → Purpose: Display PDH/PDL reference lines → Default: ON → Best for: Intraday traders who respect previous day levels MAIN DASHBOARD: Show Main Dashboard → Purpose: Toggle visibility of market conditions table → Default: ON Main Dashboard Position → Options: Top Right, Top Left, Bottom Right, Bottom Left → Default: Top Right → When to change: To avoid overlap with TradingView's built-in panels TRADE ANALYSIS PANEL: Show Trade Analysis Panel → Purpose: Toggle factor analysis dashboard → Default: ON Analysis Panel Position → Options: Top Right, Top Left, Bottom Right, Bottom Left, Middle Right, Middle Left → Default: Bottom Left → Recommended: Bottom Right or Middle Right to avoid overlap with Main Dashboard Compact Mode → Purpose: Reduces panel size for mobile or smaller screens → Default: OFF → When to enable: Mobile trading, small screens, or minimalist preference Show Factor Details → Purpose: Displays individual factor scores vs. overall confidence only → Default: ON → When to disable: For more compact view showing only state and confidence RISK MANAGEMENT: Stop Loss Method → Purpose: How stop loss distance is calculated → Options: • Structure-Based: Uses swing highs/lows with ATR buffer (recommended) • ATR-Based: Pure ATR multiplier with min/max constraints • Fixed ATR: Simple multiplier, no adjustments → Default: Structure-Based → Impact: Structure-Based respects market geometry but constrains within safe limits ATR Stop Multiplier → Purpose: Multiplier for ATR-based stop calculation → Range: 0.5 to 3.0 → Default: 1.5 → When to adjust: • Increase to 2.0-2.5 for more breathing room (fewer false stops) • Decrease to 1.0-1.2 for tighter stops (but more stop-outs) Maximum Stop Distance (ATR) → Purpose: Cap on stop width to prevent excessive risk → Range: 1.0 to 5.0 → Default: 2.5 → Impact: If structure-based stop exceeds this, ATR-based stop is used instead Minimum Stop Distance (ATR) → Purpose: Floor on stop width to avoid noise-induced stops → Range: 0.2 to 1.0 → Default: 0.5 → Impact: Prevents stops too tight to survive normal volatility Target 1 Risk/Reward Ratio → Purpose: R:R for first profit target → Range: 0.5 to 2.0 → Default: 1.0 (1:1 ratio) → Common values: 1.0 for quick profit taking, 1.5 for patient trading Target 2 Risk/Reward Ratio → Purpose: R:R for second profit target (full win) → Range: 1.0 to 4.0 → Default: 2.0 (1:2 ratio) → Common values: 2.0-3.0 for balanced risk/reward Minimum R:R Required → Purpose: Filters out signals with poor risk/reward → Range: 0.5 to 2.0 → Default: 1.0 → Impact: Signals where potential reward doesn't meet this ratio are rejected → WARNING: Always ensure your position sizing means a stop loss = no more than 1-2% of your account, regardless of R:R ratio SIGNAL FILTERS: Session Awareness → Purpose: Weights signals higher during major forex sessions → Default: ON → Impact: Doesn't block signals, but session quality factors into scoring → Best for: Forex traders Session Timezone → Purpose: Timezone for session calculations → Options: UTC, America/New_York, Europe/London, Asia/Tokyo, Asia/Hong_Kong → Default: UTC → When to change: Match your broker's server time Higher Timeframe Alignment → Purpose: Checks HTF momentum before generating signals → Default: ON → Impact: Filters counter-trend signals, improves quality → Recommended: Keep enabled HTF Timeframe → Purpose: Which higher timeframe to check → Default: Auto (blank field) → Auto selection: • 1m chart → 5m HTF • 5m chart → 15m HTF • 15m chart → 1H HTF • 1H chart → 4H HTF • 4H+ chart → Daily HTF → Manual override: Enter any timeframe (e.g., "60" for 1-hour) Volume Confirmation → Purpose: Requires above-average volume for signals → Default: ON → Impact: Filters low-liquidity false signals → Recommended: Keep enabled Minimum Volume Ratio → Purpose: Volume threshold vs. 20-bar average → Range: 0.3 to 2.0 → Default: 0.8 (80% of average) → When to adjust: • Increase to 1.2-1.5 for only high-volume signals • Decrease to 0.5-0.7 for more permissive filtering Structure Clearance Check → Purpose: Ensures clear path to targets (no nearby resistance/support) → Default: ON → Impact: Prevents trades with immediate obstacles → Recommended: Keep enabled Minimum Bars Between Signals → Purpose: Cooldown period after each signal → Range: 1 to 10 → Default: 3 → Impact: After a signal, this many bars must pass before another in same direction → When to adjust: • Increase to 5-7 to prevent over-trading • Decrease to 1-2 for faster re-entries ADVANCED TUNING: Momentum Period → Purpose: Base period for Kinetic Pulse calculation → Range: 5 to 30 → Default: 14 → When to adjust: • Lower (8-10): More responsive, noisier • Higher (18-21): Smoother, slower to react → Note: If Adaptive Period enabled, this is adjusted automatically Adaptive Period → Purpose: Auto-adjusts momentum period based on volatility → Default: ON → Impact: Shortens period in high volatility, lengthens in low volatility → Recommended: Keep enabled for automatic optimization Divergence Lookback → Purpose: How far back to search for divergence patterns → Range: 10 to 60 → Default: 30 → When to adjust: • Shorter (15-20): Only recent divergences • Longer (40-50): Catches older divergences (may be less relevant) Swing Detection Bars → Purpose: Bars required on each side to confirm swing high/low → Range: 2 to 7 → Default: 3 → Impact on stops: • Lower (2-3): More swing points, potentially tighter stops • Higher (5-7): Only major swings, wider stops Choppiness Index Threshold → Purpose: Threshold above which market considered choppy → Range: 38.2 to 80.0 → Default: 61.8 → Impact: • Lower (50-55): Stricter quality filter (fewer signals in ranging markets) • Higher (65-70): More permissive (allows signals in choppier conditions) HOW TO READ SIGNALS SIGNAL ANATOMY: When a signal appears, you'll see: 1. DIRECTIONAL MARKER → Arrow, dot, or diamond pointing to entry candle (depends on style) → Positioned below price for LONG, above price for SHORT → Connected to price with line (Premium style) 2. GRADE BADGE → Displays signal quality: LONG , SHORT , etc. → Color coding: • Bright green/cyan for A+ longs • Standard green for A/B longs • Bright pink/magenta for A+ shorts • Standard red for A/B shorts 3. ENTRY PRICE (Premium style only) → Shows exact entry price at signal generation 4. TOOLTIP (all styles) → Hover over signal to see complete trade plan → Includes: Entry, Stop, TP1, TP2, Risk, R:R ratios, market conditions, signal reason, confluence score INTERPRETING GRADES: → A+ SIGNALS (Highest Quality) • 8-12+ confirming factors aligned • Multiple divergences OR strong momentum reversal • HTF alignment + volume + session timing + clear structure • These are your highest-probability setups • Recommended action: Give these priority, consider larger position size → A SIGNALS (High Quality) • 5-9+ confirming factors aligned • Good confluence, most key factors present • Missing 1-2 optimal conditions • These are still quality trades • Recommended action: Standard position size, solid setups → B SIGNALS (Moderate Quality) • 3-7+ confirming factors aligned • Minimum viable confluence • May be missing HTF alignment, volume, or session timing • Higher variance outcomes • Recommended action: Smaller position size or skip if conservative SIGNAL NARRATIVE: Each signal tooltip includes a narrative explaining WHY it was generated: → "Multi-divergence at oversold extreme" • Multiple oscillators showing bullish divergence • Kinetic Pulse in oversold zone • High-quality reversal setup → "Bullish divergence near support" • Divergence detected • Price near key support level (swing low or PDL) • Structure confluence → "Momentum reversal with HTF alignment" • Kinetic Pulse velocity reversing • Higher timeframe supports direction • Strong trend-following setup → "Oversold momentum reversal" • Extreme Kinetic Pulse reading reversing • May not have divergence but strong momentum shift READING THE TRADE PLAN: Every signal comes with a complete trade plan: → ENTRY: The close price of the signal candle • This is where the signal triggered • If using limit orders, you might improve on this price → STOP: Calculated stop loss level • Based on your Stop Loss Method setting • Distance shown in ticks • Risk tolerance: Ensure this represents ≤1-2% of your account → TP1: First profit target • Default: 1:1 risk-reward • This is your partial profit or first exit • Consider taking 50% off at TP1 → TP2: Second profit target • Default: 1:2 risk-reward • This is your "full win" target • Hold remaining position for this level SIGNAL FREQUENCY EXPECTATIONS: Frequency varies by timeframe, sensitivity, and market conditions: → AGGRESSIVE MODE • Lower timeframes (1m-5m): 5-15 signals per day • Mid timeframes (15m-1H): 2-5 signals per day • Higher timeframes (4H-D): 1-3 signals per week → BALANCED MODE (Default) • Lower timeframes: 3-8 signals per day • Mid timeframes: 1-3 signals per day • Higher timeframes: 2-5 signals per week → CONSERVATIVE MODE • Lower timeframes: 1-4 signals per day • Mid timeframes: 0-2 signals per day • Higher timeframes: 1-3 signals per week Note: Frequency also depends on market volatility and trending vs. ranging conditions. Example - Kinetic Scalper Trade Sequence Here's an example showing the complete trade lifecycle with all dashboard transitions, annotations, and descriptions. INSTRUMENT & TIMEFRAME DETAILS Symbol: Nifty 50 Index (NSE) Date: December 15, 2025 Session: London session (active trading hours) Instrument Type: Index (auto-detected) TRADE SEQUENCE BREAKDOWN SCREENSHOT 1: Pre-Signal Setup Building (Image 1) Time: ~12:00-14:30 UTC+5:30(approx.) Price Action: Uptrend showing signs of exhaustion near 26,200 Market State: Price at session highs Main Dashboard (Top Right): - Bias: LEAN SHORT - Pulse: 58.9 (approaching overbought) - Volatility: NORMAL - Trend: TRANSITIONING - Session: LONDON (favorable timing) - Volume: 0.98x (slightly below average) - HTF: BULLISH (caution for counter-trend) - Best Score: 9/5 (Short score building) - PDH/PDL: 26098.25 / 25938.95 Trade Analysis Panel (Bottom Left): - Status: NO ACTIVE TRADE - Long Score: 5/5 (RDY) - Short Score: 9/5 (RDY) - Panel Message: "Short pattern developing - score: 9" Description : Setup Development Phase: The indicator identifies a potential short opportunity as price reaches the previous day's high. The short confluence score has climbed to 9/15 points, meeting the 'Balanced' sensitivity threshold for a Grade B signal. Notice the 'LEAN SHORT' bias and the Kinetic Pulse reading of 58.9 approaching overbought territory. The Trade Analysis panel shows 'Short pattern developing' with 9/5 factors aligned. Key factors: momentum approaching reversal zone, price at resistance (PDH), and London session providing favorable conditions. SCREENSHOT 2: Signal Generated & Trade Entered (Image 2) Time: ~13:00 UTC+5:30 (signal bar) Entry Price: 26,184.65 Signal Grade: Grade Main Dashboard (Top Right): - Trade: SHORT - Entry: 26184.65 - P/L: 5.95 pts | +0.2R (early positive movement) - TP1: 26157.00 (33.2 pts away) - TP2: 26129.35 (60.84 pts away) - Stop: 26212.30 (22.1 pts away) - Bars: 1 (just entered) Trade Analysis Panel (Bottom Left): - Header: TRADE ANALYSIS - Status Bar: "Conditions mixed - improving 57%" - Confidence: 57% RISING - Factor Breakdown: - Momentum: -4 (velocity not yet aligned) - Position: +4 (slight profit) - Volume: +2 = (volume present) - HTF Align: +2 = (not strongly aligned) - Target: +0 - (far from TP) - Stop Dist: +3 - (good distance) - Bottom Status: "Conditions mixed - Monitoring" - Disclaimer: "Analysis only - Not financial advice" Description: Signal Activation: A Grade A short signal triggers at 26,184.65 after the short confluence score reached qualifying levels. The indicator places a structure-based stop loss at 26,212.30 (27.65 points risk) with dual targets at 1:1 and 1:2 risk-reward ratios. The Trade Analysis Panel immediately begins monitoring with an initial confidence score of 57% - classified as 'MIXED SIGNALS' but showing a 'RISING' trend. Factor analysis reveals: momentum not yet aligned (-4 points as price just reversed), position slightly favorable (+4 points already +0.2R), volume adequate (+2), HTF showing weak alignment (+2 as we're counter-trend), stop well-placed (+3), but targets still distant (0 points). Notice how the Main Dashboard switches from market scanning mode to active trade tracking, now displaying entry price, live P/L in both points (5.95 pts) and R-multiples (+0.2R), and distances to all key levels. The analysis panel provides real-time factor scoring to help monitor trade health. SCREENSHOT 3: TP1 Hit - Trade Performing Well (Image 3) Time: ~14:20 UTC+5:30(approx) Price: ~26,154 (TP1 zone) Bars in Trade: 29 Main Dashboard (Top Right): - Trade: SHORT - Entry: 26184.65 - P/L: 30.85 pts | +1.12R (excellent progress) - TP1: HIT (displayed in green) - TP2: 26129.35 (24.44 pts away) - Stop: 26212.30 (58.5 pts away - well protected) - Bars: 29 Trade Analysis Panel (Bottom Left): - Header: TRADE ANALYSIS - Status Bar: "Multiple factors positive" - Confidence: 78% RISING - Factor Breakdown: - Momentum: +8 = (ALIGNED) - Position: +8 + (strong profit zone) - Volume: +2 + (continued support) - HTF Align: +8 = (now strongly aligned) - Target: +10 + (TP1 achieved, approaching TP2) - Stop Dist: +3 + (excellent cushion) - Bottom Status: "Multiple factors positive" - Visual State: Green background (FACTORS ALIGNED state) Description: Trade Execution Phase - First Target Achieved: After 29 bars , price reaches the first take-profit target at 26,157.00. The ' ' marker confirms partial profit taking. Current P/L shows +30.85 points (+1.12R), exceeding the initial 1:1 risk-reward. The Trade Analysis Panel shows dramatic improvement - confidence has surged to 78% (FACTORS ALIGNED state) with most factors now positive: - Momentum factor improved to +8 (velocity aligned with trade direction) - Position factor at +8 (over +1R profit zone) - HTF Align jumped to +8 (higher timeframe now confirming the move) - Target factor maxed at +10 (TP1 achieved, TP2 within reach) - Stop Distance at +3 (58.5 points cushion providing safety) Notice the panel status displays 'Multiple factors positive' with a green-tinted background, indicating optimal trade conditions. The confidence trend shows 'RISING' suggesting continued momentum. With TP1 secured and only 24.44 points to TP2, the trade is well-positioned for a full 1:2R win. SCREENSHOT 4: TP2 Reached - Trade Complete (Image 4) Time: ~15:00+ UTC+5:30 Final Exit: 26,129.35 (TP2) Final Result: Full TP2 win Main Dashboard (Top Right): - Bias: NEUTRAL (reverted to scanning mode) - Pulse: 45.2 (returned to neutral zone) - Volatility: NORMAL - Trend: TREND DOWN (confirmed the move) - Session: LONDON - Volume: 1.26x (increased as move developed) - HTF: BEARISH (fully aligned post-trade) - Best Score: 5/5 (neutral after completion) Trade Analysis Panel (Bottom Left): - Status: NO ACTIVE TRADE (reverted) - Long Score: 5/5 (RDY) - Short Score: 5/5 (RDY) - Panel Message: "Scanning - prime session active" - Light blue/cyan background (back to scanning mode) Description: Trade Completion - Full Target Achieved: The short trade reaches its second take-profit target at 26,129.35, securing a complete 1:2 risk-reward win. The ' ' marker confirms the exit. Final results: - Entry: 26,184.65 - Exit: 26,129.35 - Profit: 55.30 points (approximately +2.0R) - Outcome: Full TP2 success Post-Trade Analysis: After trade closure, the indicator automatically returns to market scanning mode. The Main Dashboard reverts to showing market conditions rather than trade metrics. Notice how the 'Trend' now displays 'TREND DOWN' - confirming the move we captured. Volume increased to 1.26x during the winning move, validating the signal quality. The Trade Analysis Panel switches back to 'NO ACTIVE TRADE' status and resumes displaying long/short setup scores. The confidence-based factor monitoring was instrumental throughout the trade: - Initial entry at 57% confidence (MIXED SIGNALS) - Peak confidence of 78% at TP1 (FACTORS ALIGNED) - Real-time factor updates helped confirm trade validity This example demonstrates the indicator's complete workflow: setup identification → signal generation → entry execution → live trade monitoring → systematic exit at targets. KEY FEATURES DEMONSTRATED 1. Dual Dashboard System - Main Dashboard: Market conditions (scanning) → Trade metrics (active position) - Analysis Panel: Setup scores (scanning) → Factor-based confidence (in-trade) 2. Visual Trade Management - Color-coded entry zones (yellow) - Risk levels clearly marked (red dashed stop) - Profit targets with R:R ratios labeled - Achievement markers ( , ) 3. Real-Time Factor Analysis - 6-factor scoring system (Momentum, Position, Volume, HTF, Target, Stop Dist) - Confidence percentage with trend indicators - State machine (MIXED → FACTORS ALIGNED) - Hysteresis prevents false state changes 4. Risk Management - Structure-based stop placement (respects swing highs) - Multiple take-profit levels (1:1 and 1:2 R:R) - Live P/L tracking in points and R-multiples - Distance monitoring to all key levels This complete example showcases the indicator's progression from setup identification through trade completion, demonstrating how the dual-dashboard system and factor-based analysis provide continuous trade guidance. The structured stop-loss and dual-target approach delivered the planned 1:2 risk-reward ratio with systematic, rule-based execution. ALERT SYSTEM The indicator includes 9 built-in alert conditions: SIGNAL ALERTS: → High-Grade Long Signal (A+) • Triggers only on A+ long signals • For traders who want only the highest-quality longs • Message: "KINETIC SCALPER: LONG @ " → High-Grade Short Signal (A+) • Triggers only on A+ short signals • For traders who want only the highest-quality shorts • Message: "KINETIC SCALPER: SHORT @ " → Long Signal • Triggers on ANY qualified long signal (A+, A, or B) • For traders who want all long opportunities • Message: "KINETIC SCALPER: LONG @ " → Short Signal • Triggers on ANY qualified short signal • For traders who want all short opportunities • Message: "KINETIC SCALPER: SHORT @ " TRADE MANAGEMENT ALERTS: → TP1 Hit • Triggers when first profit target is reached • Useful for partial profit taking notifications • Message: "KINETIC SCALPER: TP1 REACHED" → TP2 Reached • Triggers when second profit target is reached • Trade is complete, full win achieved • Message: "KINETIC SCALPER: TP2 REACHED" → Stop Loss Hit • Triggers when stop loss is reached • Important for trade management and risk tracking • Message: "KINETIC SCALPER: STOP LOSS" ANALYSIS STATE ALERTS: → Analysis State: Negative Bias • Triggers when factor analysis enters "Negative Bias" state • Warning that trade conditions are deteriorating • Consider reducing position or preparing to exit • Message: "KINETIC SCALPER: Analysis state changed to NEGATIVE BIAS" → Analysis State: Factors Weakening • Triggers when factor analysis enters "Factors Weakening" state • Caution that confluence is diminishing • Monitor trade closely • Message: "KINETIC SCALPER: Analysis state changed to FACTORS WEAKENING" HOW TO SET UP ALERTS: 1. Click the "Create Alert" button in TradingView 2. Condition: Select "Kinetic Scalper " 3. Choose your desired alert from the dropdown 4. Configure your alert options: → Once Per Bar Close (recommended for non-repainting) → Frequency: Once Per Bar Close or Only Once 5. Set expiration and notification methods (popup, email, webhook, etc.) 6. Create alert RECOMMENDED ALERT STRATEGY: For active traders: → Set "Long Signal" and "Short Signal" alerts for all opportunities → Set "TP1 Hit", "TP2 Reached", and "Stop Loss Hit" for trade management → Consider "Analysis State: Negative Bias" for trade monitoring For selective traders: → Set only "High-Grade Long Signal (A+)" and "High-Grade Short Signal (A+)" → Focus on the absolute highest-quality setups → Set TP/SL alerts for position management USAGE TIPS & BEST PRACTICES SIGNAL SELECTION: ✓ GRADE MATTERS → A+ signals have statistically more confluence factors → If you're conservative, trade only A+ signals → B signals can work but require more discretion ✓ CONFLUENCE WITH YOUR ANALYSIS → Use this indicator as CONFIRMATION, not sole decision criteria → Combine with your own support/resistance analysis → Check for fundamental events (news, economic data) → Respect major round numbers and psychological levels ✓ SESSION TIMING (Forex) → Best signals often occur during London/NY overlap → Avoid signals 10 minutes before major news releases → Asian session signals can be valid but lower liquidity ✓ TIMEFRAME CONFLUENCE → If you get an A+ signal on 15m, check if 1H chart agrees → Higher timeframe confirmation adds conviction → Avoid signals that oppose the daily/4H trend TRADE MANAGEMENT: ✓ POSITION SIZING → ALWAYS size positions so stop loss = 1-2% of account → Never risk more than you can afford to lose → Smaller position on B signals, standard on A, larger on A+ (within limits) ✓ PARTIAL PROFIT TAKING → Consider taking 50% off at TP1 → Move stop to breakeven after TP1 hit → Let remaining position run to TP2 ✓ TRAILING STOPS → The indicator doesn't auto-trail stops (manual decision) → After TP1, you might manually move stop to entry (breakeven) → Consider ATR-based trailing stop for runners ✓ WATCH THE ANALYSIS PANEL → If state changes to "Factors Weakening" while in profit, consider exit → "Negative Bias" during a trade is a strong warning → "Factors Aligned" confirms your trade thesis is still valid RISK MANAGEMENT: ✓ NEVER IGNORE STOPS → The calculated stop is there for a reason → Moving stop further away increases risk exponentially → If stopped out, accept it and wait for next setup ✓ AVOID REVENGE TRADING → If you get stopped out, resist urge to immediately re-enter → Signal cooldown helps with this → Wait for next qualified signal ✓ RESPECT VOLATILITY WARNINGS → If indicator shows "EXTREME" volatility, signals are blocked for a reason → Don't force trades in chaotic conditions → Wait for regime to normalize ✓ CORRELATION RISK → Be aware of correlation if trading multiple pairs → EUR/USD and GBP/USD are highly correlated → Don't stack risk on correlated instruments OPTIMIZATION: ✓ START WITH DEFAULTS → Default settings are well-tested → Don't over-optimize for recent market behavior → Give settings at least 20-30 trades before judging ✓ TIMEFRAME-SPECIFIC ADJUSTMENTS → Lower timeframes: Consider increasing Signal Distance to 3.0-4.0 → Higher timeframes: ATR Stop Multiplier might go to 2.0-2.5 → Crypto: Ensure Instrument Type is set to "Crypto" for proper stops ✓ SENSITIVITY CALIBRATION → Too many signals? Switch to Conservative → Missing good setups? Try Balanced or Aggressive → Quality > Quantity always ✓ KEEP A JOURNAL → Track which signal grades work best for you → Note which sessions produce best results → Review stopped trades for patterns THINGS TO AVOID: ✗ DON'T chase signals after several bars have passed ✗ DON'T ignore the stop loss or move it further away ✗ DON'T overtrade by taking every B-grade signal ✗ DON'T trade during major news if you're not experienced ✗ DON'T use this as your only analysis tool ✗ DON'T expect 100% win rate (no indicator has this) ✗ DON'T risk more than 1-2% per trade regardless of signal grade UNDERSTANDING THE METHODOLOGY WHY VOLUME WEIGHTING? Traditional momentum oscillators treat all price moves equally. A 10-point move on low volume is weighted the same as a 10-point move on high volume. The Kinetic Pulse corrects this by: → Calculating volume ratio vs. 20-bar average → Applying square root transformation to volume ratio (prevents extreme weights) → Multiplying price changes by volume weight → Result: High-volume moves influence the oscillator more than low-volume noise This helps filter false breakouts and emphasizes moves with participation. WHY FISHER TRANSFORM? Fisher Transform is a mathematical transformation that: → Normalizes probability distributions → Creates sharper turning points → Amplifies extremes while compressing the middle → Makes overbought/oversold levels more distinct Applied to the Kinetic Pulse, it helps identify genuine extremes vs. noise. WHY MULTI-OSCILLATOR DIVERGENCE? Single-source divergence can give false signals. By requiring divergence confirmation across multiple oscillators (Kinetic Pulse, CCI, Stochastic), the system filters out: → Divergences caused by calculation quirks in one oscillator → Temporary momentum anomalies → False divergence on noisy, low-timeframe charts Multiple sources confirming the same pattern increases reliability. WHY ADAPTIVE PERIODS? Fixed periods can be: → Too slow during high volatility (miss fast reversals) → Too fast during low volatility (generate noise) The adaptive system: → Shortens period when ATR ratio > 1.3 (high volatility = need faster response) → Lengthens period when ATR ratio < 0.7 (low volatility = need noise filtering) → Keeps period in reasonable range (60% to 140% of base period) → Result: Oscillator adjusts to current market pace automatically WHY HYSTERESIS IN STATE MACHINE? Without hysteresis, the analysis state would flip-flop on every bar, creating: → Confusing, contradictory guidance → Analysis paralysis → Lack of actionable information Hysteresis solves this by: → Using different thresholds to ENTER vs. EXIT a state → Example: Enter "Factors Aligned" at 72+ confidence, but don't exit until <62 → This creates stable states that persist through minor fluctuations → Requires minimum commitment period (3 bars) before state changes → Overrides commitment for significant events (near TP/SL) → Result: Stable, trustworthy analysis that changes only when truly warranted WHY CONFIDENCE SMOOTHING? Raw factor scores fluctuate bar-by-bar based on momentary conditions. Smoothing: → Uses 5-period EMA on raw confidence scores → Filters out single-bar anomalies → Preserves genuine trends in confidence → Prevents false state transitions → Result: More reliable assessment of actual trade health WHY INSTRUMENT-SPECIFIC PARAMETERS? Different instruments have different characteristics: → Forex is highly liquid, respects technical levels well, standard ATR works → Crypto is extremely volatile, needs wider stops (1.8x) to avoid false stops → Indices respect session opens strongly, session weighting is important → Commodities fall in between Auto-detection applies research-based multipliers automatically. WHY STRUCTURE-BASED STOPS? ATR-based stops can: → Place stop in middle of consolidation (easily hit) → Ignore obvious invalidation levels → Be too tight during expansion or too wide during contraction Structure-based stops: → Use actual swing highs/lows (where traders actually place stops) → Add small ATR buffer to avoid stop hunting → Constrain within min/max ATR limits for safety → Result: Stops that respect market geometry while managing risk DISCLAIMER & RISK WARNING READ THIS CAREFULLY BEFORE USING THIS INDICATOR This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only. ❌ NOT FINANCIAL ADVICE This indicator does NOT constitute financial advice, investment recommendations, or solicitation to buy or sell any financial instrument. All information is for educational purposes only. ❌ NO GUARANTEES → Past performance does NOT guarantee future results → No indicator can predict future price movements with certainty → Signal grades represent confluence, NOT win probability → A+ signals can lose, B signals can win - markets are probabilistic ❌ SUBSTANTIAL RISK Trading financial instruments involves SUBSTANTIAL RISK of loss: → You can lose your entire investment → Leveraged trading amplifies both gains AND losses → Never trade with money you cannot afford to lose → Never risk more than 1-2% of your account per trade ❌ YOUR RESPONSIBILITY → All trading decisions are YOUR responsibility → You must conduct your own analysis before entering trades → Consult a licensed financial advisor before trading → Understand the risks specific to your jurisdiction and situation → Only trade with capital you can afford to lose completely ❌ NO HOLY GRAIL → This indicator is a TOOL, not a complete trading system → It should be used as part of a broader analysis framework → Combine with your own technical analysis, risk management, and judgment → No indicator works 100% of the time in all market conditions ❌ ANALYSIS PANEL DISCLAIMER The "Trade Analysis Panel" provides ALGORITHMIC ANALYSIS of market factors. → It does NOT provide investment advice or recommendations → Factor scores are mathematical calculations, not predictions → Guidance messages are informational, not directives → All trading decisions remain your responsibility ❌ BACKTESTING LIMITATIONS → This is an indicator, not a strategy, so no backtesting results are provided → Any backtesting you perform includes hindsight bias and optimization bias → Historical performance does not indicate future performance → Slippage, commissions, and real-world execution differ from backtests ❌ MARKET CONDITIONS → This indicator performs differently in trending vs. ranging markets → Extreme volatility can produce false signals or whipsaws → Low liquidity periods increase execution risk → Major news events can invalidate technical analysis BY USING THIS INDICATOR, YOU ACKNOWLEDGE: → You have read and understood this disclaimer → You accept full responsibility for your trading decisions → You understand the substantial risks involved in trading → You will not hold the author liable for any losses incurred → You are using this tool as part of your own due diligence process KEY FEATURES SUMMARY ✅ Volume-Weighted Kinetic Pulse Engine (proprietary momentum calculation) ✅ 15-Factor Confluence Scoring System (graded signals: A+, A, B) ✅ Multi-Oscillator Divergence Detection (Pulse + CCI + Stochastic) ✅ Higher Timeframe Trend Alignment Filter ✅ Adaptive Period Adjustment (volatility-responsive) ✅ Instrument-Aware Calibration (Forex, Crypto, Indices, Commodities) ✅ Structure-Based Stop Loss Calculation (respects swing highs/lows) ✅ Automated Trade Tracking (entry, stop, TP1, TP2, P/L) ✅ Real-Time Factor Analysis State Machine (5-state system with hysteresis) ✅ Session Awareness (Asian, London, New York, Overlap) ✅ Volatility Regime Detection (blocks signals in extreme conditions) ✅ Choppiness Filter (reduces signals in ranging markets) ✅ Volume Confirmation (relative volume and delta analysis) ✅ Clean Air Check (validates clear path to targets) ✅ Comprehensive Dashboards (market conditions + trade analysis) ✅ Customizable Display (3 signal styles, color themes, positioning) ✅ 9 Built-In Alert Conditions (signals, TP/SL hits, state changes) ✅ Fully Non-Repainting (barstate.isconfirmed, lookahead_off) ✅ Previous Day Levels (PDH/PDL reference lines) ✅ Mobile-Friendly Compact Mode (for smaller screens) TECHNICAL SPECIFICATIONS → Pine Script Version: v6 → Indicator Type: Overlay (displays on price chart) → License: Mozilla Public License 2.0 → Copyright: BULLBYTE → Object Limits: 300 labels, 100 lines, 50 boxes → Memory Management: Automatic cleanup system (FIFO queue) → Repainting: Non-repainting (signals confirmed on bar close) → Timeframe Support: All timeframes (1s to Monthly) → Instrument Support: Forex, Crypto, Indices, Commodities, Stocks → HTF Data Handling: lookahead_off with historical offset VERSION HISTORY v1.0 - Initial Release → Kinetic Pulse engine with volume weighting and Fisher Transform → 15-factor confluence scoring system → Trade analysis state machine with hysteresis → Automated trade tracking and monitoring → Dual dashboard system (market conditions + factor analysis) → 9 alert conditions → 3 signal display styles → Instrument-aware calibration → Full risk management framework WHO IS THIS INDICATOR FOR? IDEAL FOR: ✓ Scalpers and day traders seeking high-confluence reversal entries ✓ Swing traders who want quality over quantity ✓ Traders who appreciate systematic, rules-based analysis ✓ Multi-timeframe traders who value HTF confirmation ✓ Forex traders who respect session timing ✓ Crypto traders needing volatility-adjusted parameters ✓ Traders who want complete trade management (entry, stop, targets) ✓ Analytical traders who want transparency in signal generation NOT IDEAL FOR: ✗ Traders seeking a "set and forget" holy grail system ✗ Traders who don't want to learn the methodology ✗ Traders unwilling to accept losing trades as part of the process ✗ Traders who need constant signals (this is a quality-focused system) ✗ Traders who ignore risk management FINAL THOUGHTS The Kinetic Scalper is the result of extensive research into momentum behavior, volume confirmation, and multi-factor confluence analysis. It's designed to identify high-probability reversal setups while maintaining strict risk management and providing complete transparency. This is NOT a magic solution. It's a sophisticated TOOL that requires: → Understanding of the methodology → Proper risk management discipline → Patience to wait for quality setups → Willingness to accept losses as part of trading → Integration with your own analysis and judgment Used properly as part of a complete trading plan, the Kinetic Scalper can help you identify high-confluence opportunities and manage trades systematically. Remember: Quality over quantity. Discipline over emotion. Risk management over everything. Trade smart. Trade safe. © 2025 BULLBYTE | Kinetic Scalper v1.0 | For Educational Purposes Only
Indicador Pine Script®
por BullByte