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SuperTrend Strategy with Trend-Based Exits🟩 SuperTrend Strategy with Trend-Based Exits This is a fully automated trend-following strategy based on the popular SuperTrend indicator, enhanced with a position sizing algorithm tied to stop-loss distance and dynamic entry/exit rules. The strategy is designed for futures trading with an emphasis on sustainable risk, realistic backtesting, and transparent logic. 🧠 Concept and Methodology The strategy uses the SuperTrend indicator, which is derived from ATR (Average True Range) and is widely used to capture medium- to long-term market trends. Key features: ✅ Entries are triggered only when the SuperTrend direction changes (trend reversal). ✅ Exits are performed using a dynamic stop-loss placed at the SuperTrend line. ✅ Position size is automatically calculated based on the trader’s fixed dollar risk per trade and the current distance to the stop-loss. ✅ Rounding logic is included to ensure quantity is valid for the exchange’s lot size. This strategy does not use any take-profit or classic trailing stop — the position is only closed when the trend reverses or the stop is hit by touching the SuperTrend line. ⚙️ Default Parameters ATR Length: 300 Factor: 7.5 Risk per trade: $90 (3% of the default $3,000 capital) Lot step: 10 Commission: 0.05% These default parameters are not universal. They were optimized specifically for STXUSDT swap at 15M timeframe at Bybit and may not produce viable results on other pairs and timeframes. Users are encouraged to customize the settings according to specific asset’s volatility, timeframe and other characteristics. ❗ These default settings yield meaningful backtesting results on STXUSDT with a reasonable number of trades (105+) over 7-month period. If applied to other assets, results may vary significantly. 📈 Position Sizing Logic The strategy uses a dynamic position sizing formula: Pine Script® position_size = floor((risk_per_trade / stop_loss_distance) / lot_step) * lot_step This ensures the trader always risks a fixed dollar amount per trade and never exceeds a sustainable equity exposure (recommended 2% or less). ✅ Realism in Backtesting To ensure realistic and non-misleading backtest results, this strategy includes: — Slippage and commission settings matching average exchange conditions (commission = 0.05%, slippage 5 ticks). — Position sizing based on stop-loss distance (not fixed contract quantity).* — A fixed risk-per-trade model that adheres to responsible capital management principles. — This is in compliance with TradingView's Script publishing rules and House Rules. 📌 How to Use Apply the strategy to a clean chart (preferably 15M for STXUSDT by default). If using another asset, adjust: - ATR Length - Factor - Risk per trade - Qty step (lot precision for the symbol) Avoid using with other indicators unless you understand their purpose. Use the Strategy Tester to evaluate performance and optimize parameters. ⚠️ Disclaimer This is not financial advice. Always perform forward testing and assess risk before deploying any strategy on live capital. The strategy is designed for educational and experimental use.
Strategia Pine Script®
di nefyodov.artyom
ZigZag Volume Profile [ChartPrime]⯁ OVERVIEW ZigZag Volume Profile combines swing structure with volume analytics by plotting a ZigZag of major price swings and overlaying a detailed volume profile around each swing. At the end of each swing, it highlights the Point of Control (POC) — the price level with the highest traded volume — and extends it forward to identify key areas of potential support or resistance. ⯁ KEY FEATURES ZigZag Swing Detection: Automatically detects swing highs and lows based on a user-defined length, creating clean visual segments of market structure. These segments act as boundaries for volume profile calculations. swingHigh = ta.highest(swingLength) swingLow = ta.lowest(swingLength) ZigZag Channel Visualization: The ZigZag structure is connected with sloped lines, forming a visual “channel” of the price movement. The ZigZag can optionally, scaled by ATR. Volume Profile Around Each Swing: For every completed swing (high to low or low to high), the indicator constructs a full volume profile using user-defined bin counts. It scans volume across price levels in the swing and plots histogram-style bins using a gradient color to indicate volume magnitude. Dynamic Bin Width and Slope Adjustment: Bins are distributed across a vertical ATR-based range, and their width is adjusted based on the percentage of total swing volume. The volume fill direction is adapted to the swing’s slope for visually aligned plotting. POC Detection and Extension: The highest volume bin in each swing is identified as the Point of Control (POC). This level is plotted with a thicker line and extended horizontally into the future as a key reaction level. Automatic POC Expiry on Price Interaction: POC lines are continuously extended unless breached by price. When price crosses the POC level, the extension is terminated — signaling that the level may have been absorbed. Clean Volume Bin Visualization: Bin colors range from green (low volume) to blue (higher volume), with the POC always marked in red by default for easy identification. Volume percentages are optionally labeled at each bin level. Flexible Swing Profile Parameters: Users can control: Number of volume bins Bin width Channel width (ATR factor) Visibility of the swing channel or POC lines Efficient Memory Handling: Old POC lines and volume profiles are automatically removed from memory after a threshold to keep charts clean and performant. ⯁ USAGE Use ZigZag swings to define market structure visually. Analyze volume profile around each swing to understand where most trading activity occurred. Use POC extensions as dynamic support/resistance zones for entries, stops, or take-profits. Watch for price interaction with extended POC lines — breaks may suggest absorbed liquidity or breakout potential. Use the ATR-based channel width to adapt profiles based on market volatility. ⯁ CONCLUSION ZigZag Volume Profile offers a powerful fusion of structure and volume. By plotting detailed volume profiles over each price swing and extending the POC as actionable S/R levels, this tool provides deep insight into market participation zones — giving traders a tactical edge in both ranging and trending environments.
Indicatore Pine Script®
di ChartPrime
3
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®
di EfeErdost
Mig Trade Model - Kill Zones Key features: Liquidity Hunt Detection: Spots aggressive moves that "hunt" stops beyond recent swing highs/lows. Consolidation Filter: Requires 1-3 small-range candles after a hunt before confirming with a strong candle. Bias Application: Uses daily open/close to auto-detect bias or allows manual override. Kill Zone Restriction: Limits signals to London (default: 7-10 AM UTC) and NY (default: 12-3 PM UTC) sessions for better relevance in active markets. This strategy is inspired by smart money concepts (SMC) and ICT (Inner Circle Trader) methodologies, aiming to capture venom-like "stings" in price action where liquidity is grabbed before reversals. How It Works ATR Calculation: Uses a user-defined ATR length (default: 14) to measure volatility, which scales candle body and range thresholds. Bias Determination: Auto: Compares daily close to open (bullish if close > open). Manual: User selects "Bullish" or "Bearish." Strong Candles: Bullish: Green candle with body > 2x ATR (configurable). Bearish: Red candle with body > 2x ATR. Small Range Candles: Candles where high-low < 0.5x ATR (configurable). Liquidity Hunt: Bullish Hunt: Strong bearish candle making a new low below the past swing low (default: 10 bars). Bearish Hunt: Strong bullish candle making a new high above the past swing high. Signal Generation: After a hunt, counts 1-3 small-range candles. Confirms with a strong candle in the opposite direction (e.g., strong bullish after bearish hunt). Resets if >3 small candles or an opposing strong candle appears. Kill Zone Filter: Checks if the current bar's time (in UTC) falls within London or NY Kill Zones. Only allows final "Buy" (bullish entry) or "Sell" (bearish entry) if bias matches and in Kill Zone. Plots: Yellow circle (below): Bullish liquidity hunt. Orange circle (above): Bearish liquidity hunt. Blue diamond (below): Raw bullish signal. Purple diamond (above): Raw bearish signal. Green triangle up ("Buy"): Filtered bullish entry. Red triangle down ("Sell"): Filtered bearish entry. Inputs Bias: "Auto" (default), "Bullish", or "Bearish" – Controls signal direction based on daily trend. ATR Length: 14 (default) – Period for ATR calculation. Swing Length for Liquidity Hunt: 10 (default) – Bars to look back for swing highs/lows. Strong Candle Body Multiplier (x ATR): 2.0 (default) – Threshold for strong candle bodies. Small Range Multiplier (x ATR): 0.5 (default) – Threshold for small-range candles. London Kill Zone Start/End Hour (UTC): 7/10 (default) – Customize London session hours. NY Kill Zone Start/End Hour (UTC): 12/15 (default) – Customize New York session hours. Usage Tips Timeframe: Best on lower timeframes (e.g., 5-15 min) for intraday trading, especially forex pairs like EURUSD or GBPUSD. Timezone Adjustment: Inputs are in UTC. If your chart is in a different timezone (e.g., EST = UTC-5), adjust hours accordingly (e.g., London: 2-5 AM EST → 7-10 UTC). Risk Management: Use with stop-loss (e.g., beyond the hunt low/high) and take-profit based on ATR multiples. Not financial advice—backtest thoroughly. Customization: Tweak multipliers for different assets; higher for volatile cryptos, lower for stocks. Limitations: Relies on historical data; may generate false signals in ranging markets. Combine with other indicators like volume or support/resistance. This indicator is for educational purposes. Always use discretion and proper risk management in live trading. If you find it useful, feel free to share feedback or suggestions!
Indicatore Pine Script®
di EfeErdost
Basic ORB [MOT]Basic ORB – Opening Range Breakout Tool The Basic ORB is a visual tool designed to assist intraday traders by identifying the opening range from 9:30–9:45 AM ET. It automatically plots the high, low, and midpoint of this range to help traders analyze potential areas of interest. This script provides a simple and customizable way to frame market structure during the early trading session. It is intended to support various intraday strategies across multiple asset classes including futures, stocks, ETFs, indexes, and crypto. 🔹 Key Features 1. Opening Range Levels - Automatically plots the High, Low, and Midline of the 9:30–9:45 AM ET session. - Midline helps visualize the midpoint of the range. - Customizable colors and line thickness. 2. Previous ORB Ranges - Option to display previous days’ ORB levels for visual pattern recognition. - Useful for spotting recurring reactions to prior day levels. 3. Dynamic Price Labels - Adds price labels to each ORB line for quick reference. - Fully customizable: adjust text size, background color, label position, and offset. 4. Clean Settings Panel - Customize all visual elements to match your charting style. - Control how many previous ORBs to display. - Toggle features on or off for a simplified interface. 🧠 How to Use - Best viewed on 1m, 5m, or 15m charts. - Combine with your existing entry/exit criteria to monitor how price interacts with the opening range. - Common use cases include breakout confirmation, rejection trades, and support/resistance analysis based on prior ORBs. ⚠️ Disclaimer This script is for educational and informational purposes only. It does not constitute financial advice. Trading carries risk, and users should test any tools in a demo environment before live use. Always implement proper risk management.
Indicatore Pine Script®
di TheBigDaddyMax
1
MSTY-WNTR Rebalancing SignalMSTY-WNTR Rebalancing Signal ## Overview The **MSTY-WNTR Rebalancing Signal** is a custom TradingView indicator designed to help investors dynamically allocate between two YieldMax ETFs: **MSTY** (YieldMax MSTR Option Income Strategy ETF) and **WNTR** (YieldMax Short MSTR Option Income Strategy ETF). These ETFs are tied to MicroStrategy (MSTR) stock, which is heavily influenced by Bitcoin's price due to MSTR's significant Bitcoin holdings. MSTY benefits from upward movements in MSTR (and thus Bitcoin) through a covered call strategy that generates income but caps upside potential. WNTR, on the other hand, provides inverse exposure, profiting from MSTR declines but losing in rallies. This indicator uses Bitcoin's momentum and MSTR's relative strength to signal when to hold MSTY (bullish phases), WNTR (bearish phases), or stay neutral, aiming to optimize returns by switching allocations at key turning points. Inspired by strategies discussed in crypto communities (e.g., X posts analyzing MSTR-linked ETFs), this indicator promotes an active rebalancing approach over a "set and forget" buy-and-hold strategy. In simulated backtests over the past 12 months (as of August 4, 2025), the optimized version has shown potential to outperform holding 100% MSTY or 100% WNTR alone, with an illustrative APY of ~125% vs. ~6% for MSTY and ~-15% for WNTR in one scenario. **Important Disclaimer**: This is not financial advice. Past performance does not guarantee future results. Always consult a financial advisor. Trading involves risk, and you could lose money. The indicator is for educational and informational purposes only. ## Key Features - **Momentum-Based Signals**: Uses a Simple Moving Average (SMA) on Bitcoin's price to detect bullish (price > SMA) or bearish (price < SMA) trends. - **RSI Confirmation**: Incorporates MSTR's Relative Strength Index (RSI) to filter signals, avoiding overbought conditions for MSTY and oversold for WNTR. - **Visual Cues**: - Green upward triangle for "Hold MSTY". - Red downward triangle for "Hold WNTR". - Yellow cross for "Switch" signals. - Background color: Green for MSTY, red for WNTR. - **Information Panel**: A table in the top-right corner displays real-time data: BTC Price, SMA value, MSTR RSI, and current Allocation (MSTY, WNTR, or Neutral). - **Alerts**: Configurable alerts for holding MSTY, holding WNTR, or switching. - **Optimized Parameters**: Defaults are tuned (SMA: 10 days, RSI: 15 periods, Overbought: 80, Oversold: 20) based on simulations to reduce whipsaws and capture trends effectively. ## How It Works The indicator's logic is straightforward yet effective for volatile assets like Bitcoin and MSTR: 1. **Primary Trigger (Bitcoin Momentum)**: - Calculate the SMA of Bitcoin's closing price (default: 10-day). - Bullish: Current BTC price > SMA → Potential MSTY hold. - Bearish: Current BTC price < SMA → Potential WNTR hold. 2. **Secondary Filter (MSTR RSI Confirmation)**: - Compute RSI on MSTR stock (default: 15-period). - For bullish signals: If RSI > Overbought (80), signal Neutral (avoid overextended rallies). - For bearish signals: If RSI < Oversold (20), signal Neutral (avoid capitulation bottoms). 3. **Allocation Rules**: - Hold 100% MSTY if bullish and not overbought. - Hold 100% WNTR if bearish and not oversold. - Neutral otherwise (e.g., during choppy or extreme markets) – consider holding cash or avoiding trades. 4. **Rebalancing**: - Switch signals trigger when the hold changes (e.g., from MSTY to WNTR). - Recommended frequency: Weekly reviews or on 5% BTC moves to minimize trading costs (aim for 4-6 trades/year). This approach leverages Bitcoin's influence on MSTR while mitigating the risks of MSTY's covered call drag during downtrends and WNTR's losses in uptrends. ## Setup and Usage 1. **Chart Requirements**: - Apply this indicator to a Bitcoin chart (e.g., BTCUSD on Binance or Coinbase, daily timeframe recommended). - Ensure MSTR stock data is accessible (TradingView supports it natively). 2. **Adding to TradingView**: - Open the Pine Editor. - Paste the script code. - Save and add to your chart. - Customize inputs if needed (e.g., adjust SMA/RSI lengths for different timeframes). 3. **Interpretation**: - **Green Background/Triangle**: Allocate 100% to MSTY – Bitcoin is in an uptrend, MSTR not overbought. - **Red Background/Triangle**: Allocate 100% to WNTR – Bitcoin in downtrend, MSTR not oversold. - **Yellow Switch Cross**: Rebalance your portfolio immediately. - **Neutral (No Signal)**: Panel shows "Neutral" – Hold cash or previous position; reassess weekly. - Monitor the panel for key metrics to validate signals manually. 4. **Backtesting and Strategy Integration**: - Convert to a strategy script by changing `indicator()` to `strategy()` and adding entry/exit logic for automated testing. - In simulations (e.g., using Python or TradingView's backtester), it has outperformed buy-and-hold in volatile markets by ~100-200% relative APY, but results vary. - Factor in fees: ETF expense ratios (~0.99%), trading commissions (~$0.40/trade), and slippage. 5. **Risk Management**: - Use with a diversified portfolio; never allocate more than you can afford to lose. - Add stop-losses (e.g., 10% trailing) to protect against extreme moves. - Rebalance sparingly to avoid over-trading in sideways markets. - Dividends: Reinvest MSTY/WNTR payouts into the current hold for compounding. ## Performance Insights (Simulated as of August 4, 2025) Based on synthetic backtests modeling the last 12 months: - **Optimized Strategy APY**: ~125% (by timing switches effectively). - **Hold 100% MSTY APY**: ~6% (gains from BTC rallies offset by downtrends). - **Hold 100% WNTR APY**: ~-15% (losses in bull phases outweigh bear gains). In one scenario with stronger volatility, the strategy achieved ~4533% APY vs. 10% for MSTY and -34% for WNTR, highlighting its potential in dynamic markets. However, these are illustrative; real results depend on actual BTC/MSTR movements. Test thoroughly on historical data. ## Limitations and Considerations - **Data Dependency**: Relies on accurate BTC and MSTR data; delays or gaps can affect signals. - **Market Risks**: Bitcoin's volatility can lead to false signals (whipsaws); the RSI filter helps but isn't perfect. - **No Guarantees**: This indicator doesn't predict the future. MSTR's correlation to BTC may change (e.g., due to regulatory events). - **Not for All Users**: Best for intermediate/advanced traders familiar with ETFs and crypto. Beginners should paper trade first. - **Updates**: As of August 4, 2025, this is version 1.0. Future updates may include volume filters or EMA options. If you find this indicator useful, consider leaving a like or comment on TradingView. Feedback welcome for improvements!
Indicatore Pine Script®
di Smartmate
Accumulation Phase DetectorClean Accumulation Phase Indicator — Description This TradingView indicator visually identifies the Accumulation Phase in price action, based on the Wyckoff methodology and volume-price analysis. The Accumulation Phase is where insiders or "smart money" gradually build positions before a significant price breakout. Key Features: Range Detection: The indicator calculates a price range over a configurable period (Range Length). It marks this range on the chart with red horizontal lines representing support and resistance. Volume Spike Identification: It detects unusually high volume relative to the average volume over the same period (Volume Spike Multiplier). These spikes highlight potential insider buying activity. Accumulation Phase Highlighting: When price action remains within the detected range and volume spikes occur, the indicator considers the market to be in an accumulation phase. Volume bars during this phase are colored blue for easy visualization. Campaign Start & End Labels: The indicator places a "Campaign starts" label at the beginning of the accumulation phase and a "Campaign ends - warehouse full" label when the accumulation ends. This mimics the idea that insiders fill their “warehouses” before a breakout. Breakout Detection: Once accumulation ends, the indicator monitors for a price breakout above the resistance level and places a "Breakout" label at the breakout bar. How to Use: Adjust the Range Length and Volume Spike Multiplier inputs to suit the timeframe and instrument you’re analyzing. Watch for the blue volume bars within the red range lines to identify the accumulation phase. Use the campaign labels to identify when the phase starts and ends. Watch for the breakout label as a potential entry signal.
Indicatore Pine Script®
di Mikeramzee
Hann Window FIR Filter Ribbon [BigBeluga]🔵 OVERVIEW The Hann Window FIR Filter Ribbon is a trend-following visualization tool based on a family of FIR filters using the Hann window function. It plots a smooth and dynamic ribbon formed by six Hann filters of progressively increasing length. Gradient coloring and filled bands reveal trend direction and compression/expansion behavior. When short-term trend shifts occur (via filter crossover), it automatically anchors visual support/resistance zones at the nearest swing highs or lows. 🔵 CONCEPTS Hann FIR Filter: A finite impulse response filter that uses a Hann (cosine-based) window for weighting past price values, resulting in a non-lag, ultra-smooth output. hannFilter(length)=> var float hann = na // Final filter output float filt = 0 float coef = 0 for i = 1 to length weight = 1 - math.cos(2 * math.pi * i / (length + 1)) filt += price * weight coef += weight hann := coef != 0 ? filt / coef : na Ribbon Stack: The indicator plots 6 Hann FIR filters with increasing lengths, creating a smooth "ribbon" that adapts to price shifts and visually encodes volatility. Gradient Coloring: Line colors and fill opacity between layers are dynamically adjusted based on the distance between the filters, showing momentum expansion or contraction. Dynamic Swing Zones: When the shortest filter crosses its nearest neighbor, a swing high/low is located, and a triangle-style level is anchored and projected to the right. Self-Extending Levels: These dynamic levels persist and extend until invalidated or replaced by a new opposite trend break. 🔵 FEATURES Plots 6 Hann FIR filters with increasing lengths (controlled by Ribbon Size input). Automatically colors each filter and the fill between them with smooth gradient transitions. Detects trend shifts via filter crossover and anchors visual resistance (red) or support (green) zones. Support/resistance zones are triangle-style bands built around recent swing highs/lows. Levels auto-extend right and adapt in real time until invalidated by price action. Ribbon responds smoothly to price and shows contraction or expansion behavior clearly. No lag in crossover detection thanks to FIR architecture. Adjustable sensitivity via Length and Ribbon Size inputs. 🔵 HOW TO USE Use the ribbon gradient as a visual trend strength and smooth direction cue. Watch for crossover of shortest filters as early trend change signals. Monitor support/resistance zones as potential high-probability reaction points. Combine with other tools like momentum or volume to confirm trend breaks. Adjust ribbon thickness and length to suit your trading timeframe and volatility preference. 🔵 CONCLUSION Hann Window FIR Filter Ribbon blends digital signal processing with trading logic to deliver a visually refined, non-lagging trend tool. The adaptive ribbon offers insight into momentum compression and release, while swing-based levels give structure to potential reversals. Ideal for traders who seek smooth trend detection with intelligent, auto-adaptive zone plotting.
Indicatore Pine Script®
di BigBeluga
2
Time-Decaying Percentile Oscillator [BackQuant]Time-Decaying Percentile Oscillator 1. Big-picture idea Traditional percentile or stochastic oscillators treat every bar in the look-back window as equally important. That is fine when markets are slow, but if volatility regime changes quickly yesterday’s print should matter more than last month’s. The Time-Decaying Percentile Oscillator attempts to fix that blind spot by assigning an adjustable weight to every past price before it is ranked. The result is a percentile score that “breathes” with market tempo much faster to flag new extremes yet still smooth enough to ignore random noise. 2. What the script actually does Build a weight curve • You pick a look-back length (default 28 bars). • You decide whether weights fall Linearly , Exponentially , by Power-law or Logarithmically . • A decay factor (lower = faster fade) shapes how quickly the oldest price loses influence. • The array is normalised so all weights still sum to 1. Rank prices by weighted mass • Every close in the window is paired with its weight. • The pairs are sorted from low to high. • The cumulative weight is walked until it equals your chosen percentile level (default 50 = median). • That price becomes the Time-Decayed Percentile . Find dispersion with robust statistics • Instead of a fragile standard deviation the script measures weighted Median-Absolute-Deviation about the new percentile. • You multiply that deviation by the Deviation Multiplier slider (default 1.0) to get a non-parametric volatility band. Build an adaptive channel • Upper band = percentile + (multiplier × deviation) • Lower band = percentile – (multiplier × deviation) Normalise into a 0-100 oscillator • The current close is mapped inside that band: 0 = lower band, 50 = centre, 100 = upper band. • If the channel squeezes, tiny moves still travel the full scale; if volatility explodes, it automatically widens. Optional smoothing • A second-stage moving average (EMA, SMA, DEMA, TEMA, etc.) tames the jitter. • Length 22 EMA by default—change it to tune reaction speed. Threshold logic • Upper Threshold 70 and Lower Threshold 30 separate standard overbought/oversold states. • Extreme bands 85 and 15 paint background heat when aggressive fade or breakout trades might trigger. Divergence engine • Looks back twenty bars. • Flags Bullish divergence when price makes a lower low but oscillator refuses to confirm (value < 40). • Flags Bearish divergence when price prints a higher high but oscillator stalls (value > 60). 3. Component walk-through • Source – Any price series. Close by default, switch to typical price or custom OHLC4 for futures spreads. • Look-back Period – How many bars to rank. Short = faster, long = slower. • Base Percentile Level – 50 shows relative position around the median; set to 25 / 75 for quartile tracking or 90 / 10 for extreme tails. • Deviation Multiplier – Higher values widen the dynamic channel, lowering whipsaw but delaying signals. • Decay Settings – Type decides the curve shape. Exponential (default 1.16) mimics EMA logic. – Factor < 1 shrinks influence faster; > 1 spreads influence flatter. – Toggle Enable Time Decay off to compare with classic equal-weight stochastic. • Smoothing Block – Choose one of seven MA flavours plus length. • Thresholds – Overbought / Oversold / Extreme levels. Push them out when working on very mean-reverting assets like FX; pull them in for trend monsters like crypto. • Display toggles – Show or hide threshold lines, extreme filler zones, bar colouring, divergence labels. • Colours – Bullish green, bearish red, neutral grey. Every gradient step is automatically blended to generate a heat map across the 0-100 range. 4. How to read the chart • Oscillator creeping above 70 = market auctioning near the top of its adaptive range. • Fast poke above 85 with no follow-through = exhaustion fade candidate. • Slow grind that lives above 70 for many bars = valid bullish trend, not a fade. • Cross back through 50 shows balance has shifted; treat it like a micro trend change. • Divergence arrows add extra confidence when you already see two-bar reversal candles at range extremes. • Background shading (semi-transparent red / green) warns of extreme states and throttles your position size. 5. Practical trading playbook Mean-reversion scalps  1. Wait for oscillator to reach your desired OB/ OS levels  2. Check the slope of the smoothing MA—if it is flattening the squeeze is mature.  3. Look for a one- or two-bar reversal pattern.  4. Enter against the move; first target = midline 50, second target = opposite threshold.  5. Stop loss just beyond the extreme band. Trend continuation pullbacks  1. Identify a clean directional trend on the price chart.  2. During the trend, TDP will oscillate between midline and extreme of that side.  3. Buy dips when oscillator hits OS levels, and the same for OB levels & shorting  4. Exit when oscillator re-tags the same-side extreme or prints divergence. Volatility regime filter  • Use the Enable Time Decay switch as a regime test.  • If equal-weight oscillator and decayed oscillator diverge widely, market is entering a new volatility regime—tighten stops and trade smaller. Divergence confirmation for other indicators  • Pair TDP divergence arrows with MACD histogram or RSI to filter false positives.  • The weighted nature means TDP often spots divergence a bar or two earlier than standard RSI. Swing breakout strategy  1. During consolidation, band width compresses and oscillator oscillates around 50.  2. Watch for sudden expansion where oscillator blasts through extreme bands and stays pinned.  3. Enter with momentum in breakout direction; trail stop behind upper or lower band as it re-expands. 6. Customising decay mathematics Linear – Each older bar loses the same fixed amount of influence. Intuitive and stable; good for slow swing charts. Exponential – Influence halves every “decay factor” steps. Mirrors EMA thinking and is fastest to react. Power-law – Mid-history bars keep more authority than exponential but oldest data still fades. Handy for commodities where seasonality matters. Logarithmic – The gentlest curve; weight drops sharply at first then levels off. Mimics how traders remember dramatic moves for weeks but forget ordinary noise quickly. Turn decay off to verify the tool’s added value; most users never switch back. 7. Alert catalogue • TD Overbought / TD Oversold – Cross of regular thresholds. • TD Extreme OB / OS – Breach of danger zones. • TD Bullish / Bearish Divergence – High-probability reversal watch. • TD Midline Cross – Momentum shift that often precedes a window where trend-following systems perform. 8. Visual hygiene tips • If you already plot price on a dark background pick Bullish Color and Bearish Color default; change to pastel tones for light themes. • Hide threshold lines after you memorise the zones to declutter scalping layouts. • Overlay mode set to false so the oscillator lives in its own panel; keep height about 30 % of screen for best resolution. 9. Final notes Time-Decaying Percentile Oscillator marries robust statistical ranking, adaptive dispersion and decay-aware weighting into a simple oscillator. It respects both recent order-flow shocks and historical context, offers granular control over responsiveness and ships with divergence and alert plumbing out of the box. Bolt it onto your price action framework, trend-following system or volatility mean-reversion playbook and see how much sooner it recognises genuine extremes compared to legacy oscillators. Backtest thoroughly, experiment with decay curves on each asset class and remember: in trading, timing beats timidity but patience beats impulse. May this tool help you find that edge.
Indicatore Pine Script®
di BackQuant