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DCA with the Money Supply Index DCA with the Money Supply Index (MSI) by zdmre This strategy is based on the Money Supply Index (MSI) by zdmre and enhances it with two functional options for users: a DCA (Dollar-Cost Averaging) approach and a signal-based buy/sell mode. It’s designed to help traders and investors make data-driven, disciplined entry decisions based on monetary supply trends. 🧠 Concept Overview The Money Supply Index (MSI) provides insight into how liquidity (money supply) influences market movements. This strategy builds upon that foundation by allowing users to either: Accumulate positions over time using DCA, based on favorable MSI conditions. Execute a single buy and sell trade, optimized for bull market conditions. ⚙️ Inputs Explained General Parameters Start Bar Index / Stop Bar Index Defines the range of bars (historical data) for backtesting or strategy visualization. Long DCA Activates the DCA mode. If unchecked, the strategy operates in single-entry/single-exit signal mode. Trading Signal Enables signal-based entries and exits when the MSI reaches predefined thresholds. DCA Parameters Entry Value The MSI value that triggers a DCA buy event. When the MSI crosses below this value, the strategy considers it a favorable moment to deploy the saved capital. Saved Amount The amount of money set aside regularly (e.g., monthly) for investment. This simulates the DCA effect by accumulating capital and deploying it when conditions are optimal. Data Inputs Money Supply The data source for the Money Supply Index (default: ECONOMICS:USM2). Relational Symbol The market instrument to compare against the money supply (default: NASDAQ_DLY:NDX). This allows the strategy to measure liquidity impact on a specific market. Chart Display Options You can toggle these metrics on the chart for better visualization: Entry Price (green) – The price level of executed buys. Cash Balance (yellow) – Remaining uninvested capital. Invested Capital (red) – Total amount currently invested. Current Value (blue) – The current valuation of the investment. Profit (purple) – The total realized and unrealized profit. Trades on Chart / Signal Labels / Quantity – Enables trade markers, signal text, and position size visualization. 📈 How the Strategy Works 1️⃣ DCA Mode In DCA mode, the strategy simulates periodic savings and only invests when the MSI indicates favorable liquidity conditions (based on the Entry Value). This approach aims to achieve the best possible average entry price over time — a powerful strategy for long-term investors seeking stable accumulation with reduced emotional bias. 2️⃣ Signal-Based Mode In signal mode (with DCA disabled), the strategy performs one buy and one sell trade based on MSI turning points. It’s most effective during bull markets, where liquidity expansion supports upward momentum. This mode helps identify high-probability entry and exit zones rather than averaging in continuously. 💡 Additional Notes This strategy includes helpful metrics to monitor your personal investment performance — showing invested capital, cash reserves, and profit in real-time. The goal is to combine macroeconomic insight (money supply) with disciplined execution and capital management. ⚠️ Disclaimer This strategy is for educational and research purposes only. It does not constitute financial advice. Always conduct your own analysis before making investment decisions.
Estratégia Pine Script®
por MightyCologne
PulseWave StrategyThe PulseWave Strategy is designed to identify trend-aligned momentum bursts in price action, using a combination of EMA trend filters, RSI momentum, and volume surge detection. 📌 Features – Dual EMA crossover for trend direction – RSI filter to avoid overbought/sold traps – Volume surge detection to catch market "pulses" – ATR-based trailing exit and trend-reversal stop ⚙️ Inputs You Can Customize – EMA lengths – RSI period and thresholds – Volume surge sensitivity – ATR length and trailing logic 📈 Backtest Sample (BTCUSD 1h) – Return: +127% – Win Rate: 54% – Max Drawdown: 18% – Period: Jan 2023 – Oct 2025 (Replace with your actual test results) 🔧 Built for educational use. Always validate on your own data and strategy framework before using live. ⚠️ Disclaimer This tool is for research and educational purposes only. It is not financial advice. Trade responsibly and use proper risk management.
Estratégia Pine Script®
por Markking77
Golden StrategyTitle: XAUUSD (Gold) Smart Entry Strategy with Dynamic Scaling Description: This is a precision-based entry strategy for XAUUSD (Gold), optimized for lower timeframes like the 5-minute and 15-minute charts. It uses a custom logic engine to detect potential reversals and applies dynamic scaling (pyramiding) to build positions strategically based on price behavior. 🔍 Key Features: ✅ Smart entry logic for trend shifts ✅ Configurable position scaling up to 7 level ✅ Built-in capital efficiency for smaller accounts ✅ Backtest window control for historical testing ✅ Compact on-screen table for user guidance Timeframes Recommended: 🔸 15-minute: Best balance of risk and consistency 🔸 5-minute: More frequent signals, slightly higher risk ⚠️ Important Disclaimer This script is for educational and informational purposes only. It is not financial advice or a signal service. Trading carries risk, and past performance does not guarantee future results. Use at your own discretion and always manage risk appropriately.
Estratégia Pine Script®
por hdkd5636
Diabolos Long What the strategy tries to do It looks for RSI dips into oversold, then waits for RSI to recover above a chosen level before placing a limit buy slightly below the current price. If the limit doesn’t fill within a few bars, it cancels it. Once in a trade, it sets a fixed take-profit and stop-loss. It can pyramid up to 3 entries. Step-by-step 1) Inputs you control RSI Length (rsiLen), Oversold level (rsiOS), and a re-entry threshold (rsiEntryLevel) you want RSI to reach after oversold. Entry offset % (entryOffset): how far below the current close to place your limit buy. Cancel after N bars (cancelAfterBars): if still not filled after this many bars, the limit order is canceled. Risk & compounding knobs: initialRisk (% of equity for first order), compoundRate (% to artificially grow the equity base after each signal), plus fixed TP% and SL%. 2) RSI logic (arming the setup) It calculates rsi = ta.rsi(close, rsiLen). If RSI falls below rsiOS, it sets a flag inOversold := true (this “arms” the next potential long). A long signal (longCondition) happens only when: inOversold is true (we were oversold), RSI comes back above rsiOS, and RSI is at least rsiEntryLevel. So: dip into OS → recover above OS and to your threshold → signal fires. 3) Placing the entry order When longCondition is true: It computes a limit price: close * (1 - entryOffset/100) (i.e., below the current bar’s close). It sizes the order as positionRisk / close, where: positionRisk starts as accountEquity * (initialRisk/100). accountEquity was set once at script start to strategy.equity. It places a limit long: strategy.order("Long Entry", strategy.long, qty=..., limit=limitPrice). It then resets inOversold := false (disarms until RSI goes oversold again). It remembers the bar index (orderBarIndex := bar_index) so it can cancel later if unfilled. Important nuance about “compounding” here After signaling, it does: compoundedEquity := compoundedEquity * (1 + compoundRate/100) positionRisk := compoundedEquity * (initialRisk/100) This means your future order sizes grow by a fixed compound rate every time a signal occurs, regardless of whether previous trades won or lost. It’s not tied to actual PnL; it’s an artificial growth curve. Also, accountEquity was captured only once at start, so it doesn’t automatically track live equity changes. 4) Auto-cancel the limit if it doesn’t fill On each bar, if bar_index - orderBarIndex >= cancelAfterBars, it does strategy.cancel("Long Entry") and clears orderBarIndex. If the order already filled, cancel does nothing (there’s nothing pending with that id). Behavioral consequence: Because you set inOversold := false at signal time (not on fill), if a limit order never fills and later gets canceled, the strategy will not fire a new entry until RSI goes below oversold again to re-arm. 5) Managing the open position If strategy.position_size > 0, it reads the avg entry price, then sets: takeProfitPrice = avgEntryPrice * (1 + exitGainPercentage/100) stopLossPrice = avgEntryPrice * (1 - stopLossPercentage/100) It places a combined exit: strategy.exit("TP / SL", from_entry="Long Entry", limit=takeProfitPrice, stop=stopLossPrice) With pyramiding=3, multiple fills can stack into one net long position. Using the same from_entry id ties the TP/SL to that logical entry group (not per-layer). That’s OK in TradingView (it will manage TP/SL for the position), but you don’t get per-layer TP/SL. 6) Visuals & alerts It plots a green triangle under the bar when the long signal condition occurs. It exposes an alert you can hook to: “Покупка при достижении уровня”. A quick example timeline RSI drops below rsiOS → inOversold = true (armed). RSI rises back above rsiOS and reaches rsiEntryLevel → signal. Strategy places a limit buy a bit below current price. 4a) If price dips to fill within cancelAfterBars, you’re long. TP/SL are set as fixed % from avg entry. 4b) If price doesn’t dip enough, after N bars the limit is canceled. The system won’t re-try until RSI becomes oversold again. Key quirks to be aware of Risk sizing isn’t PnL-aware. accountEquity is frozen at start, and compoundedEquity grows on every signal, not on wins. So size doesn’t reflect real equity changes unless you rewrite it to use strategy.equity each time and (optionally) size by stop distance. Disarm on signal, not on fill. If a limit order goes stale and is canceled, the system won’t try again unless RSI re-enters oversold. That’s intentional but can reduce fills. Single TP/SL id for pyramiding. Works, but you can’t manage each add-on with different exits.
Estratégia Pine Script®
por traderhub
Order Block Volumatic FVG StrategyInspired by: Volumatic Fair Value Gaps — License: CC BY-NC-SA 4.0 (Creative Commons Attribution–NonCommercial–ShareAlike). This script is a non-commercial derivative work that credits the original author and keeps the same license. What this strategy does This turns BigBeluga’s visual FVG concept into an entry/exit strategy. It scans bullish and bearish FVG boxes, measures how deep price has mitigated into a box (as a percentage), and opens a long/short when your mitigation threshold and filters are satisfied. Risk is managed with a fixed Stop Loss % and a Trailing Stop that activates only after a user-defined profit trigger. Additions vs. the original indicator ✅ Strategy entries based on % mitigation into FVGs (long/short). ✅ Lower-TF volume split using upticks/downticks; fallback if LTF data is missing (distributes prior bar volume by close’s position in its H–L range) to avoid NaN/0. ✅ Per-FVG total volume filter (min/max) so you can skip weak boxes. ✅ Age filter (min bars since the FVG was created) to avoid fresh/immature boxes. ✅ Bull% / Bear% share filter (the 46%/53% numbers you see inside each FVG). ✅ Optional candle confirmation and cooldown between trades. ✅ Risk management: fixed SL % + Trailing Stop with a profit trigger (doesn’t trail until your trigger is reached). ✅ Pine v6 safety: no unsupported args, no indexof/clamp/when, reverse-index deletes, guards against zero/NaN. How a trade is decided (logic overview) Detect FVGs (same rules as the original visual logic). For each FVG currently intersected by the bar, compute: Mitigation % (how deep price has entered the box). Bull%/Bear% split (internal volume share). Total volume (printed on the box) from LTF aggregation or fallback. Age (bars) since the box was created. Apply your filters: Mitigation ≥ Long/Short threshold. Volume between your min and max (if enabled). Age ≥ min bars (if enabled). Bull% / Bear% within your limits (if enabled). (Optional) the current candle must be in trade direction (confirm). If multiple FVGs qualify on the same bar, the strategy uses the most recent one. Enter long/short (no pyramiding). Exit with: Fixed Stop Loss %, and Trailing Stop that only starts after price reaches your profit trigger %. Input settings (quick guide) Mitigation source: close or high/low. Use high/low for intrabar touches; close is stricter. Mitigation % thresholds: minimal mitigation for Long and Short. TOTAL Volume filter: skip FVGs with too little/too much total volume (per box). Bull/Bear share filter: require, e.g., Long only if Bull% ≥ 50; avoid Short when Bull% is high (Short Bull% max). Age filter (bars): e.g., ≥ 20–30 bars to avoid fresh boxes. Confirm candle: require candle direction to match the trade. Cooldown (bars): minimum bars between entries. Risk: Stop Loss % (fixed from entry price). Activate trailing at +% profit (the trigger). Trailing distance % (the trailing gap once active). Lower-TF aggregation: Auto: TF/Divisor → picks 1/3/5m automatically. Fixed: choose 1/3/5/15m explicitly. If LTF can’t be fetched, fallback allocates prior bar’s volume by its close position in the bar’s H–L. Suggested starting presets (you should optimize per market) Mitigation: 60–80% for both Long/Short. Bull/Bear share: Long: Bull% ≥ 50–70, Bear% ≤ 100. Short: Bull% ≤ 60 (avoid shorting into strong support), Bear% ≥ 0–70 as you prefer. Age: ≥ 20–30 bars. Volume: pick a min that filters noise for your symbol/timeframe. Risk: SL 4–6%, trailing trigger 1–2%, distance 1–2% (crypto example). Set slippage/fees in Strategy Properties. Notes, limitations & best practices Data differences: The LTF split uses request.security_lower_tf. If the exchange/data feed has sparse LTF data, the fallback kicks in (it’s deliberate to avoid NaNs but is a heuristic). Real-time vs backtest: The current bar can update until close; results on historical bars use closed data. Use “Bar Replay” to understand intrabar effects. No pyramiding: Only one position at a time. Modify pyramiding in the header if you need scaling. Assets: For spot/crypto, TradingView “volume” is exchange volume; in some markets it may be tick volume—interpret filters accordingly. Risk disclosure: Past performance ≠ future results. Use appropriate position sizing and risk controls; this is not financial advice. Credits Visual FVG concept and original implementation: BigBeluga. This derivative strategy adds entry/exit logic, volume/age/share filters, robust LTF handling, and risk management while preserving the original spirit. License remains CC BY-NC-SA 4.0 (non-commercial, attribution required, share-alike).
Estratégia Pine Script®
por TagsTrading
KD The ScalperWe have to take the trade when all three EMAs are pointing in the same direction (no criss-cross, no up/down, sideways). All 3 EMAs should be cleanly separated from each other with strong spacing between them; they are not tangled, sideways, or messy. This is our first filter before entering the trade. Are the EMAs stacked neatly, and is the price outside of the 25 EMA? If price pulls back and closes near or below the 25 or 50 EMA and breaks the 100 EMA, we don't trade. Use the 100 EMA as a safety net and refrain from trading if the price touches or falls below the 100 EMA. 1. Confirm the trend- All 3 EMAs must align, and they must spread 2. Watch price pull back to the 25th or the 50 EMA 3. Wait for the price to bounce - And re-approach the 25 EMA Why is this powerful? Removes 80% of the low-probability Trades It keeps you out of choppy markets Avoids Reversal Traps Anchors us to momentum We take the entry when the price moves up again and touches the 25 EMA from below, and then when it breaks above the 25 EMA, or even better, when a lovely green bullish candle forms. A bullish candle indicates good momentum. When a bullish candle closes in green, it means the momentum has increased significantly. This is when we enter a long trade, with the stop-loss just below the 50 EMA and the profit target being 1.5 times the stop-loss. The same rule applies to the bearish trade.
Estratégia Pine Script®
por krish16887
1
G. Santostasi Bitcoin Power Law StrategyG. Santostasi Bitcoin Power Law Strategy Overview The "G. Santostasi Bitcoin Power Law Strategy" is a TradingView strategy script built upon the foundational Bitcoin Power Law Theory by physicist Giovanni Santostasi. Unlike the companion Monte Carlo indicator, this strategy focuses on generating actionable buy entry and exit signals for trading Bitcoin, leveraging the normalized "Daily Slopes" metric to detect deviations from the long-term power-law trend. It employs two moving windows to compute local means (mu) of the Daily Slopes—a short-term 3-day window for responsive signals and a longer 2-week (14-day) window for establishing baseline bands. By comparing the short-term mu against deviation bands derived from the longer window's parameters, the strategy identifies entry points during undervalued dips and exit points during overvalued peaks. This approach capitalizes on Bitcoin's scale-invariant behavior, where price follows a power law P(t)= c t^n, with n~5.9. since the Genesis Block, resulting in diminishing but predictable returns. Backtested over Bitcoin's full history, the strategy boasts a 77% winning rate and a profit factor of 3.2, making it a robust tool for trend-following with mean-reversion elements. It emphasizes Bitcoin's long-term stability while navigating short-term oscillations, treating cycles as temporary deviations from the core power-law "DNA. "Core Concept: Daily Slopes The strategy inherits the Daily Slopes metric from the power-law framework, which normalizes daily logarithmic returns to reveal a stable local slope that oscillates around the global value of ~5.9.Definition and Calculation: Daily log returns: log⁡(P2/P1)\, where P2 and P1 are consecutive closing prices. Normalization: Divide by log⁡((t+1)/t), where ( t ) is days since the Genesis Block, yielding: Daily Slope=log⁡(P2/P1)log⁡((t+1)/t). This produces a "local n" that remains stable over time, with no long-term drift observed in Bitcoin's 16+ years of data. The metric accounts for diminishing returns, showing constant relative volatility in recent years despite absolute price stabilization. Distribution and Parameters: Daily Slopes are fitted to a t-location scale distribution over moving windows, estimating:μ (mu): The location/mean, stable around 5.9 globally. σ (sigma): Scale/volatility measure. ν (nu): Degrees of freedom for tail heaviness. For the strategy, focus is on mu and sigma from the windows, enabling deviation-based signals. Strategy Logic: Dual Moving Window Mus and Deviation Bands The strategy computes two mus via rolling fits to the t-distribution: Short Window mu (3 days): A fast-moving average of Daily Slopes, sensitive to immediate price action for timely signals. Long Window mu (2 weeks/14 days): A slower baseline, capturing medium-term trends and providing stability. Deviation bands are derived from the long window's mu and sigma: Upper Band: Long mu + Long sigma Lower Band: Long mu - Long sigma These bands represent 1-standard-deviation ranges around the longer-term mean, highlighting overbought and oversold conditions relative to the power-law trend. The short mu acts as a "signal line," crossing the bands to trigger trades. Plotting: Short mu: Responsive line for crossovers. Long mu: Central baseline. Bands: Upper (+σ) and lower (-σ) lines from the long window. Additional elements: Raw Daily Slopes and strategy signals (arrows for entries/exits). Entry and Exit Rules: The strategy generates long-only signals (buy/sell) based on crossovers, assuming a single-position approach without leverage or shorting: Buy Entry: Triggered when the short-window mu crosses above the lower band (long mu - long sigma). This detects potential local minima, signaling undervaluation and a reversion to the power-law mean. Sell Exit: Triggered when the short-window mu meets or crosses below the upper band (long mu + long sigma). This identifies local maxima, indicating overvaluation and a potential pullback. Trade Management: No stop-loss or take-profit hardcoded; users can add via TradingView settings. Positions close on exit signals, with re-entry on the next valid buy. Filters for false signals: Optional confirmation from global slope (e.g., only trade if long mu > 5.0) to align with bullish regimes. This crossover mechanic blends momentum (short mu) with mean-reversion (bands), exploiting Bitcoin's oscillatory nature around the power law without predicting bubbles or crashes explicitly. Performance Metrics: Backtested on BTCUSD daily data from the Genesis Block to present (assuming continuous updates):Winning Rate: 77% – A high hit rate due to the strategy's focus on statistically stable deviations. Profit Factor: 3.2 – Gross profits are 3.2 times gross losses, reflecting asymmetric upside from power-law reversion. Additional Stats (hypothetical based on historical fits): Average trade duration ~30-60 days; drawdown <20% in most cycles; outperforms buy-and-hold in volatile periods by avoiding peaks. Caveats: Past performance is not indicative of future results. The strategy shines in trending markets but may underperform in prolonged sideways action. Transaction costs (e.g., fees, slippage) not included in base metrics. Usage Notes Inputs: Customize window lengths (default: 3 days short, 14 days long), global slope (5.9), and signal thresholds. Enable alerts for entries/exits. Visuals: Strategy overlays on log-scale BTCUSD charts; use with volume or RSI for confirmation. Limitations: Designed for spot trading; not optimized for derivatives or high-frequency. Assumes power-law persistence—major regime shifts (e.g., adoption plateaus) could impact efficacy. Extensions: Adapt for other power-law metrics like network addresses or hash rate for multi-signal confirmation. This strategy operationalizes Santostasi's insights into a practical trading system, prioritizing data-driven decisions over speculation.
Estratégia Pine Script®
por Quantonomyfund
1
Quantura - Quantified Price Action StrategyIntroduction “Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices. Originality & Value The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of: Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity. Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs. RSI filter: Can be set to normal or aggressive, confirming momentum before trades. Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies. EMA filter: Aligns trades with the broader market trend. Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions. This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow. Functionality & Indicators Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap. Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection. RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness. FVG filter: Adds validation by requiring price interaction with inefficiency zones. EMA filter: Ensures longs are above EMA and shorts below EMA. Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status. Parameters & Customization Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options. Liquidity filter: Mode (Run or Sweep), display, and swing length. RSI: Enable/disable, length, and style (normal or aggressive). Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles. EMA: Length, enable/disable, and visualization. Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing. Visualization: Custom candle coloring and optional overlay for better clarity. Default Properties (Strategy Settings) Initial Capital: 10,000 USD Position Size: 100% of equity per trade (backtest default) Commission: 0.1% Slippage: 1 Pyramiding: 0 (only one position at a time) Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%. Backtesting & Performance Backtests on XPTUSD over 2.5 years with the default settings produced: 129 trades 73.64% win rate Profit factor: 2.6 Maximum drawdown: 18.2% These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (129) is sufficient for statistical analysis, results may vary across markets and timeframes. Risk Management Three configurable take-profit levels with percentage allocation. Initial stop-loss based on user-defined percentage. Dynamic stop-loss that adjusts with market movement. Break-even logic that shifts stops to entry after predefined gains. Position sizing based on risk percentage of equity. This framework allows both conservative and aggressive configurations, depending on user preference. Limitations & Market Conditions Works best in volatile and liquid markets such as crypto, metals, indices, and FX. May produce false signals in low-volume or sideways environments. Unexpected news or macro events can override technical conditions. Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use. Usage Guide Add “Quantura – Quantified Price Action Strategy” to your chart. Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe. Configure risk management: take-profits, stop-loss, and risk-per-trade percentage. Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions. Optimize parameters before applying the strategy to different markets. Author & Access Developed 100% by Quantura. Published as an Invite-Only script. Access is available upon request via the Author’s Instructions field. Important This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Estratégia Pine Script®
por Quantura
AR Alerts Basic 🤖A non-repainting, ATR-based trailing stop strategy and session-based trading filters. Features: Dynamic buy/sell trailing stops using ATR for stable exits. EMA exit for remaining positions to lock in profits. Time session filters: trade only during defined market hours. Trend detection using EMA50/EMA100 coloring. Backtest dashboard Table showing total trades, win rate, P&L, growth, profit factor, and max drawdown. can be uncheck from Style Tab. Fully non-repainting signals for reliable historical testing. Perfect for traders who want stable signals, trailing stops, and a clean backtest summary in one indicator. @infonatics
Estratégia Pine Script®
por infonatics
AVGO Advanced Day Trading Strategy📈 Overview The AVGO Advanced Day Trading Strategy is a comprehensive, multi-timeframe trading system designed for active day traders seeking consistent performance with robust risk management. Originally optimized for AVGO (Broadcom), this strategy adapts well to other liquid stocks and can be customized for various trading styles. 🎯 Key Features Multiple Entry Methods EMA Crossover: Classic trend-following signals using fast (9) and medium (16) EMAs MACD + RSI Confluence: Momentum-based entries combining MACD crossovers with RSI positioning Price Momentum: Consecutive price action patterns with EMA and RSI confirmation Hybrid System: Advanced multi-trigger approach combining all methodologies Advanced Technical Arsenal When enabled, the strategy analyzes 8+ additional indicators for confluence: Volume Price Trend (VPT): Measures volume-weighted price momentum On-Balance Volume (OBV): Tracks cumulative volume flow Accumulation/Distribution Line: Identifies institutional money flow Williams %R: Momentum oscillator for entry timing Rate of Change Suite: Multi-timeframe momentum analysis (5, 14, 18 periods) Commodity Channel Index (CCI): Cyclical turning points Average Directional Index (ADX): Trend strength measurement Parabolic SAR: Dynamic support/resistance levels 🛡️ Risk Management System Position Sizing Risk-based position sizing (default 1% per trade) Maximum position limits (default 25% of equity) Daily loss limits with automatic position closure Multiple Profit Targets Target 1: 1.5% gain (50% position exit) Target 2: 2.5% gain (30% position exit) Target 3: 3.6% gain (20% position exit) Configurable exit percentages and target levels Stop Loss Protection ATR-based or percentage-based stop losses Optional trailing stops Dynamic stop adjustment based on market volatility 📊 Technical Specifications Primary Indicators EMAs: 9 (Fast), 16 (Medium), 50 (Long) VWAP: Volume-weighted average price filter RSI: 6-period momentum oscillator MACD: 8/13/5 configuration for faster signals Volume Confirmation Volume filter requiring 1.6x average volume 19-period volume moving average baseline Optional volume confirmation bypass Market Structure Analysis Bollinger Bands (20-period, 2.0 multiplier) Squeeze detection for breakout opportunities Fractal and pivot point analysis ⏰ Trading Hours & Filters Time Management Configurable trading hours (default: 9:30 AM - 3:30 PM EST) Weekend and holiday filtering Session-based trade management Market Condition Filters Trend alignment requirements VWAP positioning filters Volatility-based entry conditions 📱 Visual Features Information Dashboard Real-time display of: Current entry method and signals Bullish/bearish signal counts RSI and MACD status Trend direction and strength Position status and P&L Volume and time filter status Chart Visualization EMA plots with customizable colors Entry signal markers Target and stop level lines Background color coding for trends Optional Bollinger Bands and SAR display 🔔 Alert System Entry Alerts Customizable alerts for long and short entries Method-specific alert messages Signal confluence notifications Advanced Alerts Strong confluence threshold alerts Custom alert messages with signal counts Risk management alerts ⚙️ Customization Options Strategy Parameters Enable/disable long or short trades Adjustable risk parameters Multiple entry method selection Advanced indicator on/off toggle Visual Customization Color schemes for all indicators Dashboard position and size options Show/hide various chart elements Background color preferences 📋 Default Settings Initial Capital: $100,000 Commission: 0.1% Default Position Size: 10% of equity Risk Per Trade: 1.0% RSI Length: 6 periods MACD: 8/13/5 configuration Stop Loss: 1.1% or ATR-based 🎯 Best Use Cases Day Trading: Designed for intraday opportunities Swing Trading: Adaptable for longer-term positions Momentum Trading: Excellent for trending markets Risk-Conscious Trading: Built-in risk management protocols ⚠️ Important Notes Paper Trading Recommended: Test thoroughly before live trading Market Conditions: Performance varies with market volatility Customization: Adjust parameters based on your risk tolerance Educational Purpose: Use as a learning tool and customize for your needs 🏆 Performance Features Detailed performance metrics Trade-by-trade analysis capability Customizable risk/reward ratios Comprehensive backtesting support This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and consider your financial situation before trading.
Estratégia Pine Script®
por r0b3rtcc
7
Alpha SignalsThis strategy is designed to highlight potential short-term market setups using a fast and slow EMA crossover system on a 5-minute chart. It provides visual signals directly on the chart to help traders observe trend changes and potential entry points. Key Features: EMA Crossover Entries – The strategy enters long trades when the fast EMA crosses above the slow EMA and short trades when the fast EMA crosses below the slow EMA. Time-Based Exits – Trades are automatically closed after a configurable number of bars to manage exposure. Visual Alerts – Buy and sell signals are displayed as labels directly on the chart for easy interpretation. Configurable Settings – Users can adjust fast and slow EMA lengths as well as the exit bar count to suit their trading preferences. Usage: Suitable for short-term traders focusing on the NQ1 futures contract or other instruments with similar volatility. Can be used for observation, back testing, or as a confirmation tool alongside other strategies. Does not guarantee profitability; intended for educational purposes and strategy testing only.
Estratégia Pine Script®
por danny_faltas