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ZenTrend Follower Signals (Backtest)Buy/Sell Entry signals based on the ZenTrend Follower indicator. Entries are taken from the setup and trend breakout level, exits from the trailing stop loss. Overextension and trend re-entry signals are ignored. The indicator is linked below If you enjoy these posts please like and subscribe so more people can join you :) If you want to tryout the indicator and strategy, follow me and drop a comment or pm and I’ll get you set up. Stay calm, and happy trading! More information on the indicator can be found below:
Strategia Pine Script®
od DariusZen
7
MULTIPLE TIME-FRAME STRATEGY(TREND, MOMENTUM, ENTRY) Hey everyone, this is one strategy that I have found profitable over time. It is a multiple time frame strategy that utilizes 3 time-frames. Highest time-frame is the trend, medium time-frame is the momentum and short time-frame is the entry point. Long Term: - If closed candle is above entry then we are looking for longs, otherwise we are looking for shorts Medium Term: - If Stoch SmoothK is above or below SmoothK and the momentum matches long term trend then we look for entries. Short Term: - If a moving average crossover(long)/crossunder(short) occurs then place a trade in the direction of the trend. Close Trade: - Trade is closed when the Medium term SmoothK Crosses under/above SmoothD. You can mess with the settings to get the best Profit Factor / Percent Profit that matches your plan. Best of luck!
Strategia Pine Script®
od tux
4
Deep in the Tape – VSA (Invite Only)Deep in the Tape – VSA (Invite-Only) Overview This invite-only study is built entirely on the Volume Spread Analysis (VSA) methodology developed by Tom Williams. VSA examines the interplay of volume, spread (bar range), and close position to highlight the footprints of professional activity. The aim of this tool is educational: to make it easier for traders to study how supply and demand pressures appear on the chart in real time. It does not generate trading advice, but instead plots markers based on classical VSA principles so students of the method can recognize strength, weakness, confirmations, and traps without the cryptic complexity often found in raw VSA study. What It Displays Key VSA Events (visual markers on the chart): Stopping Volume (SV): Wide down bars with climactic volume closing off the lows. Selling Climax (SC): Exhaustion selling at the end of a decline, often near bottoms. Shakeout (SO): A sharp push down that springs back to close strong. No Supply (NS): Narrow down bar on low volume, showing lack of selling pressure. No Demand (ND): Narrow up bar on low volume, showing lack of buying interest. Supply Coming In: Volume surge after an up-move, suggesting sellers active. Buying Climax (BC): Wide up bar with climactic volume and weakness into the close. Upthrust (UT): False break above prior highs with a weak close. End of Rising Market (EoRM): Narrow up bar on very high volume, closing weak, often signaling distribution. Test Bar: Down bar on very low volume in an uptrend, testing for lack of supply. Contextual Tools: Trigger Levels: High/low of ultra-high volume bars projected forward, serving as natural support/resistance levels. Cluster Zones: Optional shading to mark zones of repeated high-volume activity (potential accumulation/distribution). Background MA: A simple moving average for context only — not a signal generator. Interpreting the Markers (Tom Williams Style) Bullish Background (professional strength): Events: Stopping Volume, Selling Climax, Shakeout, No Supply. Best studied when price is trading above trigger levels and above the MA, showing demand in control. Bearish Background (professional weakness): Events: Buying Climax, Upthrust, Supply Coming In, End of Rising Market. Best studied when price is below trigger levels and below the MA, showing supply dominance. Failures (Educational Study Only) Not all setups confirm. In VSA, Tests sometimes fail, and No Demand or No Supply bars can be absorbed. These are marked as Failure markers. Their purpose is purely educational: To show where expectations do not play out. To help students see how traps or absorptions form. To illustrate Tom Williams’ lesson that the market is a testing ground — not a perfect pattern machine. How to Use It Study Background Activity: Watch for climactic volume and projected trigger levels. Look for Response: After signs of strength (SC, SV, SO, NS), seek confirming Tests or NS bars. After signs of weakness (UT, BC, Supply Coming In), look for ND or UT confirmation. Apply Context: Confirm whether price is above/below triggers and the MA to judge whether demand or supply has the upper hand. Learn from Failures: Pay attention to failures as they show where expectations break down — some of the most valuable lessons in VSA. Observe Clusters: Use cluster zones to study where professional activity tends to re-appear. Why It’s Original Built directly from Tom Williams’ VSA logic — spread, volume relative to average, wick size, close location, and background context. Adds projected trigger levels and cluster zones for educational context. Designed for clarity and study, removing unnecessary complexity while staying faithful to VSA principles. This is not a mash-up of other scripts or public code; it’s a purpose-built framework for studying supply and demand dynamics. I built this because it's what I wanted to see in a script ,true VSA Education . Disclaimer This script is for educational and analytical purposes only. It does not generate buy/sell/alert signals, nor does it provide financial advice. Always perform your own analysis and risk management before making trading decisions.
Wskaźnik Pine Script®
od deep_in_the_tape_1
THE HEDGE FUND TM PROP ROOM V2.0WHAT THE INDICATOR DOES THE HEDGE FUND™ PROP ROOM V2.0, created by SIR DEANGELO, is a professional trend-based trading tool that offers: ✅ Trend Identification Detects shifts in market momentum using an ATR-filtered SMA breakout. Confirms breakout direction when price breaches dynamic high/low zones. ✅ Automatic Entry, SL, and 3 Profit Targets Marks entry at breakout candle’s close. Places stop loss (SL) dynamically based on ATR-buffered trend zones. Generates Target 1–3 using calculated R-multiples (risk-based distances). ✅ Visual Feedback Draws ENTRY, SL, and TARGET lines directly on the chart. Displays ✔ when a target is hit, and ✖ when SL is hit. 🎯 HOW TO USE Add the indicator to any chart and timeframe. Wait for a BUY (green triangle) or SELL (red triangle) to appear. Use the plotted lines as guidance: ENTRY = suggested entry price. SL = suggested stop loss. Target 1–3 = potential take-profit levels. Watch for visual ✔ symbols to confirm profit target hits. Set up alerts for buy/sell signals (see below). 🔧 BEST SETTINGS BY MARKET TYPE Optimized for volatility and behavior of specific instruments: 🟢 Nasdaq (NQ100 Futures or CFD) Trend Length: 10–14 ATR Buffer: 0.10 TP R Multiple: 1.5 Timeframes: 5min (scalping), 15min, 1h (swing) Notes: High volatility. Favor clean setups on higher timeframes unless scalping with confluence. 🟡 Gold (XAU/USD or Futures) Trend Length: 8–12 ATR Buffer: 0.12 TP R Multiple: 1.2 Timeframes: 15min, 1h Notes: Intraday noise is high; shorter trends + moderate risk-reward = optimal. 🟠 Crude Oil (WTI/Brent) Trend Length: 12–16 ATR Buffer: 0.08 TP R Multiple: 1.7 Timeframes: 5min (news), 1h, 4h Notes: Strong directional moves follow news; wide targets help catch them. 🔵 Forex (EUR/USD, GBP/JPY, etc.) Trend Length: 10–12 ATR Buffer: 0.10 TP R Multiple: 1.0–1.5 Timeframes: 15min, 1h, 4h Notes: Lower volatility; smaller R targets and shorter lengths are more consistent. ⚙️ SETTINGS EXPLAINED Trend Length: Determines trend sensitivity. Lower = faster, higher = smoother. ATR Buffer: Adjusts how far SL sits below/above trend zone. TP R Multiple: Risk/reward ratio for placing Targets 1–3. EMA Length: Only for chart visualization — not used in signal generation. Manual SL: Optional override of the auto-calculated stop. 📢 ALERTS Add these to get notified or automate trades: BUY Alert: When price breaks above the trend zone. SELL Alert: When price breaks below the trend zone. To add: Right-click chart or click the 🔔 icon. Choose the script and alert condition (Buy or Sell). Select options: popup, sound, webhook, etc. 📘 FINAL NOTES Use with additional confluence: support/resistance, session timing (e.g., London or NY open), volume confirmation. Best for non-repainting setups — this script doesn’t repaint. Suitable for both manual and algorithmic workflows. Built for traders who demand precision and clarity in trend shifts.
Wskaźnik Pine Script®
od THEHEDGEFUND
Vsa Volume How to Use (Educational) Spot abnormal effort: Ultra-High and High bars often coincide with key areas of effort (e.g., absorption, climaxes, shakeouts). Use the background bands to quickly see when activity is entering an elevated regime. Pair with price action: Compare volume categories with bar spread and close location. High effort on narrow spread can suggest absorption; high effort on wide spread can suggest aggressive participation. Context over time: Track sequences (e.g., repeated High/Ultra-High) to identify pressure building or exhaustion. Parameter tuning: Increase smoothingPeriod to smooth noisy symbols; decrease it to make the classification more responsive. This is a stand-alone study. It can be used with any price analysis, including VSA-style reading of spread/close, but it does not generate buy/sell/alert signals. Settings Smoothing Value for Average Volume (smoothingPeriod, default 14): period for the simple moving average that defines the relative scale. Originality The tool focuses on a clear, thresholded classification of volume using chart-relative multipliers and contextual effort bands. It is purpose-built to make abnormal volume regimes visually obvious in real time without mixing in unrelated indicators or external dependencies. Disclaimer For educational and analytical purposes only. This study does not provide trading signals, alerts, or financial advice. Always perform your own analysis and risk management.
Wskaźnik Pine Script®
od deep_in_the_tape_1
EMA + RSI Daily Bias Clarity Indi🌸 EMA + RSI Daily Bias Sniper 🌸 This indicator blends adjustable EMAs with a Daily RSI Bias filter so you can trade with more clarity and confidence. Works across scalp ⏱, intraday 📊, and swing 📅 timeframes. ✨ What It Does 📈 Adjustable EMAs → tune them for scalp, intraday, or swing. 🧭 Daily Bias → automatic (based on daily EMAs) or manual override. 💪 RSI Daily Bias → extra confirmation from higher timeframe momentum. 🪞 Panel Display → shows bias clearly so you don’t second guess. ⚠️ Note → this tool is for clarity & assistance only, not buy/sell signals. 📖 How to Use 1. Timeframes ⏱ Scalp → 1m to 15m 📊 Intraday → 15m to 1H 📅 Swing → 4H to Daily 2. Bias Logic 🟢 Bullish Bias → Fast EMA above Slow EMA + RSI > 55 🔴 Bearish Bias → Fast EMA below Slow EMA + RSI < 45 ⚪ Neutral Bias → no clear direction 3. Trade Guidelines 🟢 Longs when EMA Bias + RSI Bias = Bullish 🔴 Shorts when EMA Bias + RSI Bias = Bearish ☕ If biases don’t match → stay patient and wait 4. Risk Management 🎯 Take partial profits according to your plan 🛑 Always protect yourself with a stop loss 💡 Best Practices Adjust EMA lengths depending on your style (shorter for scalps, longer for swings). Combine with your own support/resistance or supply & demand zones. Remember → this panel is for clarity, not prediction magic 🧚 ⚡ Disclaimer This indicator is for assistance and education only. It does not guarantee profits. Please trade responsibly and manage risk 💖 🌸 EMA + RSI Daily Bias Sniper 🌸 Adjustable EMAs + Daily RSI Bias for scalp, intraday, and swing. Designed for clarity & assistance 💖 — not signals. Stay patient, follow bias, and always manage risk 🛑
Wskaźnik Pine Script®
od WallStreetPrincess
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail. 1. General Description Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions. Key Features: Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes. Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses. Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes. Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold). Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle). Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results). Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio. Strategy Settings: Initial capital: $10,000. Pyramiding: Up to 3 positions. Position size: 10% of equity (default_qty_value=10). Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management. Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading. 2. Working Logic (Step by Step) The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works: a. Input Parameters The inputs are grouped for clarity: Herd Behavior (🐑): RSI Period (14): For overbought/oversold detection. Volume MA Period (20): To calculate average volume for spike detection. Herd Threshold (2.0): Volume multiplier for detecting herd activity. Liquidity Analysis (💧): Liquidity Lookback (50): Bars to check for recent highs/lows. Liquidity Sensitivity (1.5): Volume multiplier for trap detection. Institutional Flow (🏦): Institutional Volume Multiplier (2.5): For detecting large volume spikes. Institutional MA Period (21): For Accumulation/Distribution smoothing. Nash Equilibrium (⚖️): Nash Period (100): For calculating price mean and standard deviation. Nash Deviation (0.02): Multiplier for equilibrium bands. Risk Management (🛡️): Use Stop-Loss (true): Enables SL at 2% below/above entry price. Use Take-Profit (true): Enables TP at 5% above/below entry price. b. Herd Behavior Detection RSI (14): Checks for extreme conditions: Overbought: RSI > 70 (potential herd buying). Oversold: RSI < 30 (potential herd selling). Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold). Momentum: Price change over 10 bars (close - close ) compared to its SMA(20). Herd Signals: Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background). Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background). c. Liquidity Trap Detection Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback). Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones. Trap Conditions: Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5). Down Trap: Price breaks recent low, closes above it, with a volume spike. Visualization: Traps are marked with small red/green crosses above/below bars. d. Institutional Flow Analysis Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity. Accumulation/Distribution (AD): Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time. Smoothed with SMA(21) (inst_ma_length). Accumulation: AD > MA + high volume = Institutions buying. Distribution: AD < MA + high volume = Institutions selling. Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying. e. Nash Equilibrium Calculation: Price mean: SMA(100) (nash_period). Standard deviation: stdev(100). Upper Nash: Mean + StdDev x 0.02 (nash_deviation). Lower Nash: Mean - StdDev x 0.02. Conditions: Near Equilibrium: Price between upper and lower Nash bands (stable market). Above Nash: Price > upper band (overbought, sell potential). Below Nash: Price < lower band (oversold, buy potential). Visualization: Orange line (mean), red/green lines (upper/lower bands). f. Game Theory Signals The strategy generates three types of signals, combined into long/short triggers: Contrarian Signals: Buy: Herd selling + (accumulation or down trap) = Go against retail panic. Sell: Herd buying + (distribution or up trap). Momentum Signals: Buy: Below Nash + positive smart money + no herd buying. Sell: Above Nash + negative smart money + no herd selling. Nash Reversion Signals: Buy: Below Nash + rising close (close > close ) + volume > MA. Sell: Above Nash + falling close + volume > MA. Final Signals: Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy. Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell. g. Position Management Position Sizing (Minimax Principle): Default: 1.0 (10% of equity). In Nash equilibrium: Reduced to 0.5 (conservative). During institutional volume: Increased to 1.5 (aggressive). Entries: Long: If long_signal is true and no existing long position (strategy.position_size <= 0). Short: If short_signal is true and no existing short position (strategy.position_size >= 0). Exits: Stop-Loss: If use_sl=true, set at 2% below/above entry price. Take-Profit: If use_tp=true, set at 5% above/below entry price. Pyramiding: Up to 3 concurrent positions allowed. h. Visualization Nash Bands: Orange (mean), red (upper), green (lower). Background Colors: Herd buying: Red (90% transparency). Herd selling: Green. Institutional volume: Blue. Signals: Contrarian buy/sell: Green/red triangles below/above bars. Liquidity traps: Red/green crosses above/below bars. Tables: Game Theory Table (Top-Right): Herd Behavior: Buying frenzy, selling panic, or normal. Institutional Flow: Accumulation, distribution, or neutral. Nash Equilibrium: In equilibrium, above, or below. Liquidity Status: Trap detected or safe. Position Suggestion: Long (green), Short (red), or Wait (gray). Backtest Table (Bottom-Right): Total Trades: Number of closed trades. Win Rate: Percentage of winning trades. Net Profit/Loss: In USD, colored green/red. Profit Factor: Gross profit / gross loss. Max Drawdown: Peak-to-trough equity drop (%). Win/Loss Trades: Number of winning/losing trades. Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown). Avg Win/Loss Ratio: Average win per trade / average loss per trade. Last Update: Current time. i. Backtesting Metrics Tracks: Total trades, winning/losing trades. Win rate (%). Net profit ($). Profit factor (gross profit / gross loss). Max drawdown (%). Simplified Sharpe ratio (returns / drawdown). Average win/loss ratio. Updates metrics on each closed trade. Displays a label on the last bar with backtest period, total trades, win rate, and net profit. j. Alerts No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")). Use TradingView's alert system with Strategy Tester outputs. 3. Usage Tips Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals. Settings: Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping). Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets. Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto). Nash Period: Increase to 200 for longer-term analysis. Backtesting: Use TradingView's Strategy Tester to evaluate performance. Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability. Test on different assets/timeframes to ensure robustness. Live Trading: Start with a demo account. Combine with other indicators (e.g., EMAs, support/resistance) for confirmation. Monitor liquidity traps and institutional flow for context. Risk Management: Always use SL/TP to limit losses. Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading). Avoid over-leveraging (pyramiding=3 can amplify risk). Troubleshooting: If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity). Ensure sufficient historical data for Nash and liquidity calculations. If tables overlap, adjust position.top_right/bottom_right coordinates. 4. Key Differences from the Previous Indicator Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting. Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones. Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns. Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator. Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy. Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator. 5. Conclusion The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management. If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
Strategia Pine Script®
od EfeErdost