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MACD of RSI [TORYS]MACD of RSI — Momentum & Divergence Scanner Description: This enhanced oscillator applies MACD logic directly to the Relative Strength Index (RSI) rather than price, giving traders a clearer look at internal momentum and early shifts in trend strength. Now featuring a custom histogram, dual MA types, and RSI-based divergence detection — it’s a complete toolkit for identifying exhaustion, acceleration, and hidden reversal points in real time. How It Works: Calculates the MACD line as the difference between a fast and slow moving average of RSI. Adds a Signal Line (MA of the MACD) and plots a Histogram to show momentum acceleration/deceleration. Both RSI MAs and the Signal Line can be toggled between EMA and SMA for custom tuning. Divergence Detection: Bullish Divergence : Price makes a lower low while RSI makes a higher low → labeled with a green “D” below the curve. Bearish Divergence : Price makes a higher high while RSI makes a lower high → labeled with a red “D” above the curve. Configurable lookback window for tuning sensitivity to pivots, with 4 as the sweet spot. RSI Pivot Dot Signals: Plots green dots at RSI oversold pivot lows below 30, Plots red dots at overbought pivot highs above 70. Helps detect short-term exhaustion or bounce zones, plotted right on the MACD-RSI curve. RSI 50 Crosses (Optional): Optional ▲ and ▼ labels when RSI crosses its 50 midline — useful for momentum trend shifts or pullback confirmation, or to detect consolidation. Histogram: Plotted as a column chart showing the distance between MACD and Signal Line. Colored dynamically: Bright green : Momentum rising above zero Light green : Weakening above zero Bright red : Momentum falling below zero Light red : Weakening below zero The zero line serves as the mid-point: Above = Bullish Bias Below = Bearish Bias How to Interpret: Momentum Confirmation: Use MACD cross above Signal Line with a rising histogram to confirm breakouts or trend entries. Histogram shrinking near zero = momentum weakening → caution or reversal. Exhaustion & Reversals: Dot signals near RSI extremes + histogram peak can suggest overbought/oversold pressure. Use divergence labels ("D") to spot early reversal signals before price breaks structure. Inputs & Settings: RSI Length Fast/Slow MA Lengths for MACD (applied to RSI) Signal Line Length MA Type: Choose between EMA and SMA for MACD and Signal Line Pivot Sensitivity for dot markers Divergence Logic Toggle Show/hide RSI 50 Crosses Best For: Traders who want momentum insight from inside RSI, not price Scalpers using divergence or exhaustion entries Swing traders seeking entry confirmation from signal crossovers Anyone using multi-timeframe confluence with RSI and trend filters Pro Tips: Combine this with: Bollinger Bands breakouts and reversals VWAP or EMAs to filter entries by trend Volume spikes or BBW squeezes for volatility confirmation TTM Scalper Alert to sync structure and momentum
Indicador Pine Script®
por alexrainman
Plyo Tap'n'Slap (TnS) by OutOfOptionsThe Model This Strategy/Model takes advantage of the strongest trend signature in the market, which is also the most basic move in the market. This basic move is what most traders consider to be a staircase, or trendline. ICT traders call this setup a “unicorn” which is just another word for when an Order block overlaps with an FVG. The beauty of this model is that you don't need to know what ANY of these things are. The entry comes when a candles High or Low overlaps with a FVG that is at least 3 points away from both edges of the FVG. If the candle is too close to the edge then the setups is invalid (see rules for more). TO find a candle that overlaps with the FVG it also can not cut through any other price action, for example, A potential entry cant cut through another wick to make it overlap with the FVG. (see rules for more) TnS gets its TP by analyzing what is called the "OG TP" The OG TP is determined by looking for the first tapped into the FVG, then looking for an immediate High or Low to the left of the candle that first tapped the FVG. IF there is no immediate High or low next to the candle that first tapped the FVG, then target the candle itself (see rules for more). IF the "OG TP" has already been hit before TnS gets its entry, then look to the left of the TnS entry candle for the immediate High or Low next to it. If there is no immediate High or Low next to the TnS Entry candle, then target the Entry candles, High or Low (see rules for more) Model Rules Overlapping H/L MUST be at least 3 points away from both edges of the FVG, Overlapping H/L cannot cut through PA to make it overlap with the FVG, Entries can only be the highest overlapping high or the lowest overlapping low, If TnS Has already played out within the FVG then it should no longer be used, If the FVGs OG TP has already been hit then use the TnS entry to re-align for your target, No using NWOGs/NDOGs for setups. A NWOG is NOT the same thing as an FVG so this example V2 Rules If its a Bullish FVG then you need a bearish candle H/L that overlaps for your entry If its a Bearish FVG then you need a bullish candle H/L that overlaps for your entry Indicator Functionality The indicator uses specific logic to identify FVGs that match the requirements of the TnS model, ensuring at least one valid entry exists per the default V1 rules of the model, or the stricter V2 rules if configured via settings. If entries (up to 2 per model rules) are identified, the FVG is highlighted, and each entry and its stop loss is marked with a line. The line styles, colors, and FVG color, which can vary depending on whether the entry is bullish or bearish, are configurable via settings. Once the FVG is tapped into, the indicator will highlight the take profit spot and list all applicable entries, stop losses, and take profits in a table, the position and presence of which can be controlled within the indicator settings. When price action hits either stop loss or take profit, all elements are removed from the chart to avoid clutter. Additionally, the indicator allows filtering of entries based on Risk/Reward (R:R), filtering out entries where take profit is less than the model stop loss and entries for which the stop loss resides inside the FVG itself. To help visualize setups where the FVG is outside the current visual range, the indicator has options to extend the FVG box and lines by a configurable number of bars. Once the FVG is tapped, the indicator will automatically extend lines/FVG box to the bar that tapped the FVG plus the configured number of bars.
Indicador Pine Script®
por outofoptions
Gap Down Detector (Custom %)This indicator is designed specifically for the Indian stock market, and it helps traders detect significant gap-down openings at 9:15 AM IST, which is the start of the Indian trading session. 🔍 What It Does: Marks the 9:15 AM candle with a green triangle below the bar if the opening price is lower than the previous day's close by more than a user-defined percentage. Displays a label below the candle showing the gap down amount and percentage. Built for use on 5-minute timeframes or lower. Automatically handles daily gap comparison using the previous day's close from the daily timeframe. ⚙️ Customizable Setting: Minimum Gap Down %: Enter the percentage threshold (e.g., 3%) to control what qualifies as a significant gap down. 📍 Time Zone: This script uses the Asia/Kolkata time zone, matching the Indian stock market (NSE/BSE). ✅ Use Cases: Identify potential bearish momentum at market open. Filter stocks or indices showing high volatility right from the start of the session. Combine with volume and price action for intraday strategy development.
Indicador Pine Script®
por Blu_Dragon
New York Open MarkerNEW YORK OPEN MARKER This indicator highlights two key time points: the New York Open at 9:30 AM and the 10:00 AM NY time. For many traders, the NY Open is a crucial session. Manually marking these candles every day can be repetitive and time-consuming — this tool automates that process. When enabled, it will: - Mark 9:30 AM NY Time with a Blue marker. - Mark 10:00 AM NY Time with a Red marker. You can easily toggle the indicator on or off, customize the labels, or even hide them entirely. The marker colors are also fully adjustable to match your chart style. This tool is especially handy during backtesting, helping you quickly identify these critical candles without scanning the chart manually.
Indicador Pine Script®
por ForCasper
Enhanced Market Structure & Trading SignalsEnhanced Market Structure & Trading Signals A Smart Support/Resistance Indicator with Buy/Sell Alerts This indicator identifies key support & resistance levels and generates high-probability buy/sell signals based on price action and candle structure. It helps traders spot potential reversals at critical levels, just like manual analysis but with algorithmic precision. 🔹 Key Features ✅ Clean Support/Resistance Lines – Draws horizontal levels like manual charting ✅ Smart Buy/Sell Signals – Detects reversals at key levels with confirmation ✅ Price Action Filter – Only triggers signals on strong bullish/bearish candles ✅ ATR-Based Proximity Check – Ensures signals occur near valid S/R zones ✅ Customizable Settings – Adjust sensitivity, confirmation bars, and visibility 🔹 How It Works Support/Resistance Detection – Uses pivot highs/lows to mark key levels Bullish Signals (Green ▲) – Triggers near support after a strong bullish candle + confirmation Bearish Signals (Red ▼) – Triggers near resistance after a strong bearish candle + confirmation 🔹 Recommended Settings Timeframe: 1H or higher (works best on swing trading) Confirmation Bars: 2-3 (for stricter signals) Left/Right Bars: 10-20 (adjust based on market volatility) 🔹 How to Trade with This Indicator Go Long when a green ▲ appears near support Go Short when a red ▼ appears near resistance Combine with: Trend analysis, volume confirmation, or RSI for higher accuracy 📌 Note: Works best in trending or ranging markets. Avoid using in choppy/low-liquidity conditions.
Indicador Pine Script®
por w_thejazz
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it. EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been. EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac. If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context. ▶️ What is period in EMA used for? What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it. Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name. For example: Period 10 → alpha = 0.1818 Period 11 → alpha = 0.1667 What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels. Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading! ▶️ Calculating EMAs Efficiently The standard textbook formula for EMA is: EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha) But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra: EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction. That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants. Relative CPU cost of float operations : Addition/Subtraction: ~1 cycle Multiplication: ~5 cycles (depending on precision and architecture) Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator. ▶️ The Warmup Problem: how to start the EMA sequence right How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history: Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months. Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward. Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug. Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile. These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record. ▶️ A Better Way to start EMA: Decaying compensation Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday. But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point. Here's how phantom data compensation works: We start our normal EMA calculation: EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday) But we add a correction factor that adjusts for the missing history: Correction = 1 at the start Correction = Correction × (1-α) after each calculation We then apply this correction: True_EMA = Raw_EMA / (1-Correction) This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant. Let's see how this works in practice: For the first price bar: Raw_EMA = 0 Correction = 1 True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price) For the second price bar: Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2 Correction = 1 × (1-α) = (1-α) True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2 For the third price bar: Raw_EMA updates using the standard formula Correction = (1-α) × (1-α) = (1-α)² True_EMA = Raw_EMA ÷ (1-(1-α)²) With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data. This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase. Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible. // Enhanced EMA function with proper initialization and efficient calculation ema(series float source, simple int period=0, simple float alpha=0)=> // Input validation - one of alpha or period must be provided if alpha<=0 and period<=0 runtime.error("Alpha or period must be provided") // Calculate alpha from period if alpha not directly specified float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1) // Initialize variables for EMA calculation var float ema = na // Stores raw EMA value var float result = na // Stores final corrected EMA var float e = 1.0 // Decay compensation factor var bool warmup = true // Flag for warmup phase if not na(source) if na(ema) // First value case - initialize EMA to zero // (we'll correct this immediately with the compensation) ema := 0 result := source else // Standard EMA calculation (optimized formula) ema := a * (source - ema) + ema if warmup // During warmup phase, apply decay compensation e *= (1-a) // Update decay factor float c = 1.0 / (1.0 - e) // Calculate correction multiplier result := c * ema // Apply correction // Stop warmup phase when correction becomes negligible if e <= 1e-10 warmup := false else // After warmup, EMA operates without correction result := ema result // Return the properly compensated EMA value ▶️ CONCLUSION EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques. By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O. The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions. EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Indicador Pine Script®
por mihakralj
Divergence SupertrendThe Divergence Supertrend indicator combines Fibonacci-based Supertrend calculations with momentum-based signals to identify potential buy and sell opportunities. It uses three Supertrend lines with varying sensitivity (Fibonacci factors 0.8, 2.0, and 3.0) averaged into a smoothed trend. Signals are generated using RSI momentum filters and WaveTrend, with a cooldown period to prevent over-signaling. Adaptive smoothing toggles between a base (34-period EMA) and responsive (8-period EMA) length after signals. Buy/sell signals appear as triangles when momentum aligns with the Supertrend direction, with customizable alerts for trading.
Indicador Pine Script®
por DefiDigits
Fair Value Gap with EMA ConfirmationThis indicator detects Fair Value Gaps (FVGs) confirmed by Fast EMA (default 9) and Slow EMA (default 50). It generates: - Bullish signals when a candle tests the Fast EMA after an FVG (high touches without closing above when Fast EMA < Slow EMA, or low touches without closing below when Fast EMA > Slow EMA). - Bearish signals with similar logic. Features: - Customizable Fast/Slow EMA lengths. - Profit target (green), stop loss (red), and signal (yellow) lines starting at confirmation. - Optional historical signal cleanup. - Alerts for bullish/bearish confirmations. To use alerts, select "Bullish FVG Confirmed" or "Bearish FVG Confirmed" in the alert settings.
Indicador Pine Script®
por SmartGatorTrader
Volumen + Agotamiento + Tendencia Vol ↓This script detects potential exhaustion zones based on volume behavior, ideal for intraday trading on the 5-minute timeframe. 🔍 What it highlights: - **Exhaustion signals** (bullish or bearish) when: - Current volume is **below the 30-period moving average**. - The previous candle had higher volume. - Price attempts to continue in one direction but shows weakness. 📉 It also displays: - A subtle "Vol ↓" label when there is a **volume downtrend**, defined as at least 60% of the last 5 candles showing decreasing volume. 🕒 Time filter: - Signals only appear between **9:00 AM and 2:00 PM (New York time)**, aligning with the most liquid trading hours. ✅ Recommended usage: - Best suited for **5-minute charts** and **intraday setups**. - Works great as a confirmation layer for support/resistance levels, VWAP zones, or trend exhaustion. - Can be combined with order flow tools like Bookmap or delta-based analysis for precise execution. ⚠️ Note: This is not a delta or absorption-based indicator. It simplifies visual exhaustion detection based on volume structure. Use it as a **contextual alert**, not a standalone signal generator. 📎 Script by: Daniel Gonzalez 🔁 100% open-source and customizable
Indicador Pine Script®
por daniel_glz18
Grid Tendence V1The “Grid Tendence V1” strategy is based on the classic Grid strategy, only in this case the entries and exits are made in favor of the trend, which allows you to take advantage of large movements to maximize profits, because you can also enter and exit with the entire balance with a controlled risk, because precisely the distance between each Grid works as a natural and adaptive stop loss and take profit. In version 1 of the script the entries and exits are always at the market, and based on the percentage change of the price, not on the profit or loss of the current position. However, it is recommended to optimize the parameters so that the strategy is effective for each asset and for each time frame.
Estratégia Pine Script®
por morzns
Squeeze Momentum [Ryu_xp] - EnhancedSqueeze Momentum – Enhanced (Pine v6) combines the classic “Bollinger Bands vs. Keltner Channels” squeeze with a momentum oscillator to highlight breakouts and momentum shifts in one pane. Key Components: Pine v6: fully updated to TradingView’s latest Pine Script version (v6). Configurable Inputs: BB Length & MultFactor: set your Bollinger Bands. KC Length & MultFactor (optionally using True Range): set your Keltner Channels. Squeeze Logic: Squeeze On when Bollinger Bands contract inside Keltner Channels (low volatility). Squeeze Off when Bollinger Bands expand beyond Keltner Channels (volatility breakout). No Squeeze in all other cases. Momentum Oscillator: Centered on zero, built via linear regression of price vs. a combined SMA/high–low average. Plot as a filled area: Bright lime = rising bullish momentum Green = bullish but slowing Red = falling bearish momentum Maroon = bearish but slowing Squeeze State Marker: Cross‐style plot at zero: Black dot = in squeeze Gray dot = squeeze released Blue dot = neutral (no squeeze) Usage Tips: • Apply to a clean chart (no other indicators). • Watch for squeeze release (black→gray) aligned with a color flip in the oscillator to time high-probability entries. • Tweak BB/KC lengths and multipliers to suit different timeframes and instruments.
Indicador Pine Script®
por ProfitXbtc
PDHL + Current Day HL Tracker V1.1PDHL + Current Day HL Tracker — Release Notes Version: 1.1 Date: 2025-05-17 Summary This update improves the timing accuracy of the current day high/low (CDH/CDL) lines drawing logic by syncing it precisely to the chart’s exchange timezone, including automatic handling of daylight saving time (DST). This ensures the 30-minute post-open trigger fires exactly as expected in all time zones. Key Changes 30-Minute Trigger Accuracy: The current day high/low lines are now drawn exactly 30 minutes after the market open (e.g., 10:00 AM Eastern for US markets), regardless of the user’s location or DST. Behavior Preservation: Original behavior of prior day high/low (PDH/PDL) lines and their breach logic remain unchanged. Current day lines still appear either on breach or automatically after 30 minutes. Impact More reliable visualization of intraday support/resistance levels based on prior and current day price extremes. Avoids late or early drawing of current day lines due to timezone mismatches. Improves usability for traders operating in different time zones or during DST transitions. Notes No other functional or stylistic changes have been made. The indicator remains lightweight and easy to read on charts. Works on any symbol and timeframe supported by TradingView.
Indicador Pine Script®
por wjarrodreed
The Mended Collective: London High/Low KillzonesBuilt by a software engineer & futures day trader, this indicator automatically marks the London Killzone (3AM–8AM EST) and locks in the session's high and low. No more manually drawing lines every morning — this script does it all for you: 🔹 Features: ✅ Auto-detects the London Killzone (3AM–8AM EST, New York time) ✅ Highlights the session with a shaded background ✅ Plots London High and London Low as flat horizontal lines after 8AM ✅ Labels both levels for easy reference ✅ Includes optional alerts when price breaks above or below the range 🎯 Ideal For: Futures traders (NQ, ES, Gold, etc.) Supply & demand traders Smart money concept strategies Backtesters looking for clean session structure 💡 Why I Built It: As both a coder and a trader, I was tired of drawing the same zone every morning. So I built this tool to automate it and keep my focus on execution — and now I’m sharing it with the trading community.
Indicador Pine Script®
por themendedcollective
Beta -> The New SystemBeta → The New System 📊 Calculate and visualize your asset’s sensitivity to a benchmark over a rolling lookback period. What is Beta? 🤔 Beta measures how much your asset moves in relation to a chosen benchmark. A Beta of 1 means it moves in perfect sync; above 1 means it’s more volatile (amplified moves), and below 1 means it’s less volatile (dampened moves). By tracking Beta you see if your asset is a risky rocket or a stable ship compared to the market. 🚀⚓️ Indicator Inputs ⚙️ Lookback Period ⏳ Number of bars (e.g. days) over which to compute rolling averages, covariance, and variance. Benchmark Symbol 🏷️ The ticker of the market or index you want to compare against (e.g. BTCUSD, ETHUSD, an index). How It Works 🧮 Fetch prices for both your asset and the benchmark at each bar. Compute returns by calculating the percentage change from bar to bar. Smooth returns with a simple moving average over the lookback period to get mean asset and benchmark returns. Calculate covariance between asset and benchmark returns to see how they move together. Calculate variance of the benchmark returns to measure its own volatility. Divide covariance by variance (with a check to avoid division by zero)—that ratio is your Beta. Plot & Interpretation 🎨 Line Color Always blue for Beta, emphasizing volatility comparison. Reference Line A dashed gray line at Beta = 1 marks “market-level” sensitivity. Reading Beta β > 1 🟥 Asset tends to exaggerate benchmark moves—higher upside potential but larger downside risk. β = 1 🟩 Asset moves in lockstep with your benchmark. β < 1 🟦 Asset smooths out benchmark swings—less risk but also muted returns. Pro Tips 💡 Combine Alpha + Beta: high Beta with positive Alpha can be great in up-markets but painful in drawdowns. Monitor Beta shifts: a sudden jump could signal a regime change or new correlation dynamics. Test different benchmarks: small-cap altcoins may track a broader crypto index differently than they track Bitcoin. By keeping an eye on Beta in real time, you’ll understand not just how much you’re making, but how much market risk you’re taking on every trade.
Indicador Pine Script®
por LiquidityTrckr