Get started

Indicators and strategies

SigmaKernel - AdaptiveSigmaKernel - Adaptive Self-Optimizing Multi-Factor Trading System SigmaKernel - Adaptive is a self-learning algorithmic trading strategy that combines four distinct analytical dimensions—momentum, market structure, volume flow, and reversal patterns—within a machine-learning-inspired framework that continuously adjusts its own parameters based on realized trading performance. Unlike traditional fixed-parameter strategies that maintain static weightings regardless of market conditions or results, this system implements a feedback loop that tracks which signal types, directional biases, and market conditions produce profitable outcomes, then mathematically adjusts component weightings, minimum score thresholds, position sizing multipliers, and trade spacing requirements to optimize future performance. The strategy is designed for futures traders operating on prop firm accounts or live capital, incorporating realistic execution mechanics including configurable entry modes (stop breakout orders, limit pullback entries, or market-on-open), commission structures calibrated to retail futures contracts ($0.62 per contract default), one-tick slippage modeling, and professional risk controls including trailing drawdown guards, daily loss limits, and weekly profit targets. The system features universal futures compatibility—it automatically detects and adapts to any futures contract by reading the instrument's tick size and point value directly from the chart, eliminating the need for manual configuration across different markets. What Makes This Approach Different Adaptive Weight Optimization System The core differentiation is the adaptive learning architecture. The strategy maintains four independent scoring components: momentum analysis (using RSI multi-timeframe, MACD histogram, and DMI/ADX), market structure detection (breakout identification via pivot-based support/resistance and moving average positioning), volume flow analysis (Volume Price Trend indicator with standard deviation confirmation), and reversal pattern recognition (oversold/overbought conditions combined with structural levels). Each component generates a directional score that is multiplied by its current weight. After every closed trade, the system performs a retrospective analysis on the last N trades (configurable Learning Period, default 15 trades) to calculate win rates for each signal type independently. For example, if momentum-driven trades won 65% of the time while reversal trades won only 35%, the adaptive algorithm increases the momentum weight and decreases the reversal weight proportionally. The adjustment formula is: New_Weight = Current_Weight + (Component_Win_Rate - Average_Win_Rate) × Adaptation_Speed This creates a self-correcting mechanism where successful signal generators receive more influence in future composite scores, while underperforming components are de-emphasized. The system separately tracks long versus short win rates and applies directional bias corrections—if shorts consistently outperform longs, the strategy applies a 10% reduction to bullish signals to prevent fighting the prevailing market character. Dynamic Parameter Adjustment Beyond component weightings, three critical strategy parameters self-adjust based on performance: Minimum Signal Score: The threshold required to trigger a trade. If overall win rate falls below 45%, the system increments this threshold by 0.10 per adjustment cycle, making the strategy more selective. If win rate exceeds 60%, the threshold decreases to allow more opportunities. This prevents the strategy from overtrading during unfavorable conditions and capitalizes on high-probability environments. Risk Multiplier: Controls position sizing aggression. When drawdown exceeds 5%, risk per trade reduces by 10% per cycle. When drawdown falls below 2%, risk increases by 5% per cycle. This implements the professional risk management principle of "bet small when losing, bet bigger when winning" algorithmically. Bars Between Trades: Spacing filter to prevent overtrading. Base value (default 9 bars) multiplies by drawdown factor and losing streak factor. During drawdown or consecutive losses, spacing expands up to 2x to allow market conditions to change before re-entering. All adaptation operates during live forward-testing or real trading—there is no in-sample optimization applied to historical data. The system learns solely from its own realized trades. Universal Futures Compatibility The strategy implements universal futures instrument detection that automatically adapts to any futures contract without requiring manual configuration. Instead of hardcoding specific contract specifications, the system reads three critical values directly from TradingView's symbol information: Tick Size Detection: Uses `syminfo.mintick` to obtain the minimum price increment for the current instrument. This value varies widely across markets—ES trades in 0.25 ticks, crude oil (CL) in 0.01 ticks, gold (GC) in 0.10 ticks, and treasury futures (ZB) in increments of 1/32nds. The strategy adapts all entry buffer calculations and stop placement logic to the detected tick size. Point Value Detection: Uses `syminfo.pointvalue` to determine the dollar value per full point of price movement. For ES, one point equals $50; for crude oil, one point equals $1,000; for gold, one point equals $100. This automatic detection ensures accurate P&L calculations and risk-per-contract measurements across all instruments. Tick Value Calculation: Combines tick size and point value to compute dollar value per tick: Tick_Value = Tick_Size × Point_Value. This derived value drives all position sizing calculations, ensuring the risk management system correctly accounts for each instrument's economic characteristics. This universal approach means the strategy functions identically on emini indices (ES, MES, NQ, MNQ), micro indices, energy contracts (CL, NG, RB), metals (GC, SI, HG), agricultural futures (ZC, ZS, ZW), treasury futures (ZB, ZN, ZF), currency futures (6E, 6J, 6B), and any other futures contract available on TradingView. No parameter adjustments or instrument-specific branches exist in the code—the adaptation happens automatically through symbol information queries. Stop-Out Rate Monitoring System The strategy includes an intelligent stop-out rate tracking system that monitors the percentage of your last 20 trades (or available trades if fewer than 20) that were stopped out. This metric appears in the dashboard's Performance section with color-coded guidance: Green (<30% stop-out rate): Very few trades are being stopped out. This suggests either your stops are too loose (giving back profits on reversals) or you're in an exceptional trending market. Consider tightening your Stop Loss ATR multiplier to lock in profits more efficiently. Orange (30-65% stop-out rate): Healthy range. Your stop placement is appropriately sized for current market conditions and the strategy's risk-reward profile. No adjustment needed. Red (>65% stop-out rate): Too many trades are being stopped out prematurely. Your stops are likely too tight for the current volatility regime. Consider widening your Stop Loss ATR multiplier to give trades more room to develop. Critical Design Philosophy: Unlike some systems that automatically adjust stops based on performance statistics, this strategy intentionally keeps stop-loss control in the user's hands. Automatic stop adjustment creates dangerous feedback loops—widening stops increases risk per contract, which forces position size reduction, which distorts performance metrics, leading to incorrect adaptations. Instead, the dashboard provides visibility into stop performance, empowering you to make informed manual adjustments when warranted. This preserves the integrity of the adaptive system while giving you the critical data needed for stop optimization. Execution Kernel Architecture The entry system offers three distinct execution modes to match trader preference and market character: StopBreakout Mode: Places buy-stop orders above the prior bar's high (for longs) or sell-stop orders below the prior bar's low (for shorts), plus a 2-tick buffer. This ensures entries only occur when price confirms directional momentum by breaking recent structure. Ideal for trending and momentum-driven markets. LimitPullback Mode: Places limit orders at a pullback price calculated as: Entry_Price = Close - (ATR × Pullback_Multiplier) for longs, or Close + (ATR × Pullback_Multiplier) for shorts. Default multiplier is 0.5 ATR. This waits for mean-reversion before entering in the signal direction, capturing better prices in volatile or oscillating markets. MarketNextOpen Mode: Executes at market on the bar immediately following signal generation. This provides fastest execution but sacrifices the filtering effect of requiring price confirmation. All pending entry orders include a configurable Time-To-Live (TTL, default 6 bars). If an order is not filled within the TTL period, it cancels automatically to prevent stale signals from executing in changed market conditions. Professional Exit Management The exit system implements a three-stage progression: initial stop loss, breakeven adjustment, and dynamic trailing stop. Initial Stop Loss: Calculated as entry price ± (ATR × User_Stop_Multiplier × Volatility_Adjustment). Users have direct control via the Stop Loss ATR multiplier (default 1.25). The system then applies volatility regime adjustments: ×1.2 in high-volatility environments (stops automatically widen), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. This ensures stops adapt to market character while maintaining user control over baseline risk tolerance. Breakeven Trigger: When profit reaches a configurable multiple of initial risk (default 1.0R), the stop loss automatically moves to breakeven (entry price). This locks in zero-loss status once the trade demonstrates favorable movement. Trailing Stop Activation: When profit reaches the Trail_Trigger_R multiple (default 1.2R), the system cancels the fixed stop and activates a dynamic trailing stop. The trail uses Step and Offset parameters defined in R-multiples. For example, with Trail_Offset_R = 1.0 and Trail_Step_R = 1.5, the stop trails 1.0R behind price and moves in 1.5R increments. This captures extended moves while protecting accumulated profit. Additional failsafes include maximum time-in-trade (exits after N bars if specified) and end-of-session flatten (automatically closes all positions X minutes before session end to avoid overnight exposure). Core Calculation Methodology Signal Component Scoring Momentum Component: - Calculates 14-period DMI (Directional Movement Index) with ADX strength filter (trending when ADX > 25) - Computes three RSI timeframes: fast (7-period), medium (14-period), slow (21-period) - Analyzes MACD (12/26/9) histogram for directional acceleration - Bullish momentum: uptrend (DI+ > DI- with ADX > 25) + MACD histogram rising above zero + RSI fast between 50-80 = +1.6 score - Bearish momentum: downtrend (DI- > DI+ with ADX > 25) + MACD histogram falling below zero + RSI fast between 20-50 = -1.6 score - Score multiplies by volatility adjustment factor: ×0.8 in high volatility (momentum less reliable), ×1.2 in low volatility (momentum more persistent) Structure Component: - Identifies swing highs and lows using 10-bar pivot lookback on both sides - Maintains most recent swing high as dynamic resistance, most recent swing low as dynamic support - Detects breakouts: bullish when close crosses above resistance with prior bar below; bearish when close crosses below support with prior bar above - Breakout score: ±1.0 for confirmed break - Moving average alignment: +0.5 when price > SMA20 > SMA50 (bullish structure); -0.5 when price < SMA20 < SMA50 (bearish structure) - Total structure range: -1.5 to +1.5 Volume Component: - Calculates Volume Price Trend: VPT = Σ [(Close - Close ) / Close × Volume] - Compares VPT to its 10-period EMA as signal line (similar to MACD logic) - Computes 20-period volume moving average and standard deviation - High volume event: current volume > (volume_average + 1× std_dev) - Bullish volume: VPT > VPT_signal AND high_volume = +1.0 - Bearish volume: VPT < VPT_signal AND high_volume = -1.0 - No score if volume is not elevated (filters out low-conviction moves) Reversal Component: - Identifies extreme RSI conditions: RSI slow < 30 (oversold) or > 70 (overbought) - Requires structural confluence: price at or below support level for bullish reversal; at or above resistance for bearish reversal - Requires momentum shift: RSI fast must be rising (for bull) or falling (for bear) to confirm reversal in progress - Bullish reversal: RSI < 30 AND price ≤ support AND RSI rising = +1.0 - Bearish reversal: RSI > 70 AND price ≥ resistance AND RSI falling = -1.0 Composite Score Calculation Final_Score = (Momentum × Weight_M) + (Structure × Weight_S) + (Volume × Weight_V) + (Reversal × Weight_R) Initial weights: Momentum = 1.0, Structure = 1.2, Volume = 0.8, Reversal = 0.6 These weights adapt after each trade based on component-specific performance as described above. The system also applies directional bias adjustment: if recent long trades have significantly lower win rate than shorts, bullish scores multiply by 0.9 to reduce aggressive long entries. Vice versa for underperforming shorts. Position Sizing Algorithm The position sizing calculation incorporates multiple confidence factors and automatically scales to any futures contract: 1. Base risk amount = Account_Size × Base_Risk_Percent × Adaptive_Risk_Multiplier 2. Stop distance in price units = ATR × User_Stop_Multiplier × Volatility_Regime_Multiplier × Entry_Buffer 3. Risk per contract = Stop_Distance × Dollar_Per_Point (automatically detected from instrument) 4. Raw position size = Risk_Amount / Risk_Per_Contract Then applies confidence scaling: - Signal confidence = min(|Weighted_Score| / Min_Score_Threshold, 2.0) — higher scores receive larger size, capped at 2× - Direction confidence = Long_Win_Rate (for bulls) or Short_Win_Rate (for bears) - Type confidence = Win_Rate of dominant signal type (momentum/structure/volume/reversal) - Total confidence = (Signal_Confidence + Direction_Confidence + Type_Confidence) / 3 Adjusted size = Raw_Size × Total_Confidence × Losing_Streak_Reduction Losing streak reduction = 0.5 if losing_streak ≥ 5, otherwise 1.0 Universal Maximum Position Calculation: Instead of hardcoded limits per instrument, the system calculates maximum position size as: Max_Contracts = Account_Size / 25000, clamped between 1 and 10 contracts. This means a $50,000 account allows up to 2 contracts, a $100,000 account allows up to 4 contracts, regardless of which futures contract is being traded. This universal approach maintains consistent risk exposure across different instruments while preventing overleveraging. Final size is rounded to integer and bounded by the calculated maximum. Session and Risk Management System Timezone-Aware Session Control The strategy implements timezone-correct session filtering. Users specify session start hour, end hour, and timezone from 12 supported zones (New York, Chicago, Los Angeles, London, Frankfurt, Moscow, Tokyo, Hong Kong, Shanghai, Singapore, Sydney, UTC). The system converts bar timestamps to the selected timezone before applying session logic. For split sessions (e.g., Asian session 18:00-02:00), the logic correctly handles time wraparound. Weekend trading can be optionally disabled (default: disabled) to avoid low-liquidity weekend price action. Multi-Layer Risk Controls Daily Loss Limit: Strategy ceases all new entries when daily P&L reaches negative threshold (default $2,000). This prevents catastrophic drawdown days. Resets at timezone-corrected day boundary. Weekly Profit Target: Strategy ceases trading when weekly profit reaches target (default $10,000). This implements the professional principle of "take the win and stop pushing luck." Resets on timezone-corrected Monday. Maximum Daily Trades: Hard cap on entries per day (default 20) to prevent overtrading during volatile conditions when many signals may generate. Trailing Drawdown Guard: Optional prop-firm-style trailing stop on account equity. When enabled, if equity drops below (Peak_Equity - Trailing_DD_Amount), all trading halts. This simulates the common prop firm rule where exceeding trailing drawdown results in account termination. All limits display status in the real-time dashboard, showing "MAX LOSS HIT", "WEEKLY TARGET MET", or "ACTIVE" depending on current state. How To Use This Strategy Initial Setup 1. Apply the strategy to your desired futures chart (tested on 5-minute through daily timeframes) 2. The strategy will automatically detect your instrument's specifications—no manual configuration needed for different contracts 3. Configure your account size and risk parameters in the Core Settings section 4. Set your trading session hours and timezone to match your availability 5. Adjust the Stop Loss ATR multiplier based on your risk tolerance (0.8-1.2 for tighter stops, 1.5-2.5 for wider stops) 6. Select your preferred entry execution mode (recommend StopBreakout for beginners) 7. Enable adaptation (recommended) or disable for fixed-parameter operation 8. Review the strategy's Properties in the Strategy Tester settings and verify commission/slippage match your broker's actual costs The universal futures detection means you can switch between ES, NQ, CL, GC, ZB, or any other futures contract without changing any strategy parameters—the system will automatically adapt its calculations to each instrument's unique specifications. Dashboard Interpretation The strategy displays a comprehensive real-time dashboard in the top-right corner showing: Market State Section: - Trend: Shows UPTREND/DOWNTREND/CONSOLIDATING/NEUTRAL based on ADX and DMI analysis - ADX Value: Current trend strength (>25 = strong trend, <20 = consolidating) - Momentum: BULL/BEAR/NEUTRAL classification with current momentum score - Volatility: HIGH/LOW/NORMAL regime with ATR percentage of price Volume Profile Section (Large dashboard only): - VPT Flow: Directional bias from volume analysis - Volume Status: HIGH/LOW/NORMAL with relative volume multiplier Performance Section: - Daily P&L: Current day's profit/loss with color coding - Daily Trades: Number of completed trades today - Weekly P&L: Current week's profit/loss - Target %: Progress toward weekly profit target - Stop-Out Rate: Percentage of last 20 trades (or available trades if <20) that were stopped out. Includes all stop types: initial stops, breakeven stops, trailing stops, timeout exits, and EOD flattens. Color coded with actionable guidance: - Green (<30%): Shows "TIGHTEN" guidance. Very few stop-outs suggests stops may be too loose or exceptional market conditions. Consider reducing Stop Loss ATR multiplier. - Orange (30-65%): Shows "OK" guidance. Healthy stop-out rate indicating appropriate stop placement for current conditions. - Red (>65%): Shows "WIDEN" guidance. Too many premature stop-outs. Consider increasing Stop Loss ATR multiplier to give trades more room. - Status: Overall trading status (ACTIVE/MAX LOSS HIT/WEEKLY TARGET MET/FILTERS ACTIVE) Adaptive Engine Section: - Min Score: Current minimum threshold for trade entry (higher = more selective) - Risk Mult: Current position sizing multiplier (adjusts with performance) - Bars BTW: Current minimum bars required between trades - Drawdown: Current drawdown percentage from equity peak - Weights: M/S/V/R showing current component weightings Win Rates Section: - Type: Win rates for Momentum, Structure, Volume, Reversal signal types - Direction: Win rates for Long vs Short trades Color coding shows green for >50% win rate, red for <50% Session Info Section: - Session Hours: Active trading window with timezone - Weekend Trading: ENABLED/DISABLED status - Session Status: ACTIVE/INACTIVE based on current time Signal Generation and Entry The strategy generates entries when the weighted composite score exceeds the adaptive minimum threshold (initial value configurable, typically 1.5 to 2.5). Entries display as layered triangle markers on the chart: - Long Signal: Three green upward triangles below the entry bar - Short Signal: Three red downward triangles above the entry bar Triangle tooltip shows the signal score and dominant signal type (MOMENTUM/STRUCTURE/VOLUME/REVERSAL). Position Management and Stop Optimization Once entered, the strategy automatically manages the position through its three-stage exit system. Monitor the Stop-Out Rate metric in the dashboard to optimize your stop placement: If Stop-Out Rate is Green (<30%): You're rarely being stopped out. This could mean: - Your stops are too loose, allowing trades to give back too much profit on reversals - You're in an exceptional trending market where tight stops would work better - Action: Consider reducing your Stop Loss ATR multiplier by 0.1-0.2 to tighten stops and lock in profits more efficiently If Stop-Out Rate is Orange (30-65%): Optimal range. Your stops are appropriately sized for the strategy's risk-reward profile and current market volatility. No adjustment needed. If Stop-Out Rate is Red (>65%): You're being stopped out too frequently. This means: - Your stops are too tight for current market volatility - Trades need more room to develop before reaching profit targets - Action: Increase your Stop Loss ATR multiplier by 0.1-0.3 to give trades more breathing room Remember: The stop-out rate calculation includes all exit types (initial stops, breakeven stops, trailing stops, timeouts, EOD flattens). A trade that reaches breakeven and gets stopped out at entry price counts as a stop-out, even though it didn't lose money. This is intentional—it indicates the stop placement didn't allow the trade to develop into profit. Optimization Workflow For traders wanting to customize the strategy for their specific instrument and timeframe: Week 1-2: Run with defaults, adaptation enabled Allow the system to execute at least 30-50 trades (the Learning Period plus additional buffer). Monitor which session periods, signal types, and market conditions produce the best results. Observe your stop-out rate—if it's consistently red or green, plan to adjust Stop Loss ATR multiplier after the learning period. Do not adjust parameters yet—let the adaptive system establish baseline performance data. Week 3-4: Analyze adaptation behavior and optimize stops Review the dashboard's adaptive weights and win rates. If certain signal types consistently show <40% win rate, consider slightly reducing their base weight. If a particular entry mode produces better fill quality and win rate, switch to that mode. If you notice the minimum score threshold has climbed very high (>3.0), market conditions may not suit the strategy's logic—consider switching instruments or timeframes. Based on your Stop-Out Rate observations: - Consistently <30%: Reduce Stop Loss ATR multiplier by 0.2-0.3 - Consistently >65%: Increase Stop Loss ATR multiplier by 0.2-0.4 - Oscillating between zones: Leave stops at default and let volatility regime adjustments handle it Ongoing: Fine-tune risk and execution Adjust the following based on your risk tolerance and account type: - Base Risk Per Trade: 0.5% for conservative, 0.75% for moderate, 1.0% for aggressive - Stop Loss ATR Multiplier: 0.8-1.2 for tight stops (scalping), 1.5-2.5 for wide stops (swing trading) - Bars Between Trades: Lower (5-7) for more opportunities, higher (12-20) for more selective - Entry Mode: Experiment between modes to find best fit for current market character - Session Hours: Narrow to specific high-performance session windows if certain hours consistently underperform Never adjust: Do not manually modify the adaptive weights, minimum score, or risk multiplier after the system has begun learning. These parameters are self-optimizing and manual interference defeats the adaptive mechanism. Parameter Descriptions and Optimization Guidelines Adaptive Intelligence Group Enable Self-Optimization (default: true): Master switch for the adaptive learning system. When enabled, component weights, minimum score, risk multiplier, and trade spacing adjust based on realized performance. Disable to run the strategy with fixed parameters (useful for comparing adaptive vs non-adaptive performance). Learning Period (default: 15 trades): Number of most recent trades to analyze for performance calculations. Shorter values (10-12) adapt more quickly to recent conditions but may overreact to variance. Longer values (20-30) produce more stable adaptations but respond slower to regime changes. For volatile markets, use shorter periods. For stable trends, use longer periods. Adaptation Speed (default: 0.25): Controls the magnitude of parameter adjustments per learning cycle. Lower values (0.05-0.15) make gradual, conservative changes. Higher values (0.35-0.50) make aggressive adjustments. Faster adaptation helps in rapidly changing markets but increases parameter instability. Start with default and increase only if you observe the system failing to adapt quickly enough to obvious performance patterns. Performance Memory (default: 100 trades): Maximum number of historical trades stored for analysis. This array size does not affect learning (which uses only Learning Period trades) but provides data for future analytics features including stop-out rate tracking. Higher values consume more memory but provide richer historical dataset. Typical users should not need to modify this. Core Settings Group Account Size (default: $50,000): Starting capital for position sizing calculations. This should match your actual account size for accurate risk per trade. The strategy uses this value to calculate dollar risk amounts and determine maximum position size (1 contract per $25,000). Weekly Profit Target (default: $10,000): When weekly P&L reaches this value, the strategy stops taking new trades for the remainder of the week. This implements a "quit while ahead" rule common in professional trading. Set to a realistic weekly goal—20% of account size per week ($10K on $50K) is very aggressive; 5-10% is more sustainable. Max Daily Loss (default: $2,000): When daily P&L reaches this negative threshold, strategy stops all new entries for the day. This is your maximum acceptable daily loss. Professional traders typically set this at 2-4% of account size. A $2,000 loss on a $50,000 account = 4%. Base Risk Per Trade % (default: 0.5%): Initial percentage of account to risk on each trade before adaptive multiplier and confidence scaling. 0.5% is conservative, 0.75% is moderate, 1.0-1.5% is aggressive. Remember that actual risk per trade = Base Risk × Adaptive Risk Multiplier × Confidence Factors, so the realized risk will vary. Trade Filters Group Base Minimum Signal Score (default: 1.5): Initial threshold that composite weighted score must exceed to generate a signal. Lower values (1.0-1.5) produce more trades with lower average quality. Higher values (2.0-3.0) produce fewer, higher-quality setups. This value adapts automatically when adaptive mode is enabled, but the base sets the starting point. For trending markets, lower values work well. For choppy markets, use higher values. Base Bars Between Trades (default: 9): Minimum bars that must elapse after an entry before another signal can trigger. This prevents overtrading and allows previous trades time to develop. Lower values (3-6) suit scalping on lower timeframes. Higher values (15-30) suit swing trading on higher timeframes. This value also adapts based on drawdown and losing streaks. Max Daily Trades (default: 20): Hard limit on total trades per day regardless of signal quality. This prevents runaway trading during extremely volatile days when many signals may generate. For 5-minute charts, 20 trades/day is reasonable. For 1-hour charts, 5-10 trades/day is more typical. Session Group Session Start Hour (default: 5): Hour (0-23 format) when trading is allowed to begin, in the timezone specified. For US futures trading in Chicago time, session typically starts at 5:00 or 6:00 PM (17:00 or 18:00) Sunday evening. Session End Hour (default: 17): Hour when trading stops and no new entries are allowed. For US equity index futures, regular session ends at 4:00 PM (16:00) Central Time. Allow Weekend Trading (default: false): Whether strategy can trade on Saturday/Sunday. Most futures have low volume on weekends; keeping this disabled is recommended unless you specifically trade Sunday evening open. Session Timezone (default: America/Chicago): Timezone for session hour interpretation. Select your local timezone or the timezone of your instrument's primary exchange. This ensures session logic aligns with your intended trading hours. Prop Guards Group Trailing Drawdown Guard (default: false): Enables prop-firm-style trailing maximum drawdown. When enabled, if equity drops below (Peak Equity - Trailing DD Amount), all trading halts for the remainder of the backtest/live session. This simulates rules used by funded trader programs where exceeding trailing drawdown terminates the account. Trailing DD Amount (default: $2,500): Dollar amount of drawdown allowed from equity peak. If your equity reaches $55,000, the trailing stop sets at $52,500. If equity then drops to $52,499, the guard triggers and trading ceases. Execution Kernel Group Entry Mode (default: StopBreakout): - StopBreakout: Places stop orders above/below signal bar requiring price confirmation - LimitPullback: Places limit orders at pullback prices seeking better fills - MarketNextOpen: Executes immediately at market on next bar Limit Offset (default: 0.5x ATR): For LimitPullback mode, how far below/above current price to place the limit order. Smaller values (0.3-0.5) seek minor pullbacks. Larger values (0.8-1.2) wait for deeper retracements but may miss trades. Entry TTL (default: 6 bars, 0=off): Bars an entry order remains pending before cancelling. Shorter values (3-4) keep signals fresh. Longer values (8-12) allow more time for fills but risk executing stale signals. Set to 0 to disable TTL (orders remain active indefinitely until filled or opposite signal). Exits Group Stop Loss (default: 1.25x ATR): Base stop distance as a multiple of the 14-period ATR. This is your primary risk control parameter and directly impacts your stop-out rate. Lower values (0.8-1.0) create tighter stops that reduce risk per trade but may get stopped out prematurely in volatile conditions—expect stop-out rates above 65% (red zone). Higher values (1.5-2.5) give trades more room to breathe but increase risk per contract—expect stop-out rates below 30% (green zone). The system applies additional volatility regime adjustments on top of this base: ×1.2 in high volatility environments (stops widen automatically), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. For scalping on lower timeframes, use 0.8-1.2. For swing trading on higher timeframes, use 1.5-2.5. Monitor the Stop-Out Rate metric in the dashboard and adjust this parameter to keep it in the healthy 30-65% orange zone. Move to Breakeven at (default: 1.0R): When profit reaches this multiple of initial risk, stop moves to breakeven. 1.0R means after price moves in your favor by the distance you risked, you're protected at entry price. Lower values (0.5-0.8R) lock in breakeven faster. Higher values (1.5-2.0R) allow more room before protection. Start Trailing at (default: 1.2R): When profit reaches this multiple, the fixed stop transitions to a dynamic trailing stop. This should be greater than the BE trigger. Values typically range 1.0-2.0R depending on how much profit you want secured before trailing activates. Trail Offset (default: 1.0R): How far behind price the trailing stop follows. Tighter offsets (0.5-0.8R) protect profit more aggressively but may exit prematurely. Wider offsets (1.5-2.5R) allow more room for profit to run but risk giving back more on reversals. Trail Step (default: 1.5R): How far price must move in profitable direction before the stop advances. Smaller steps (0.5-1.0R) move the stop more frequently, tightening protection continuously. Larger steps (2.0-3.0R) move the stop less often, giving trades more breathing room. Max Bars In Trade (default: 0=off): Maximum bars allowed in a position before forced exit. This prevents trades from "going stale" during periods of no meaningful price action. For 5-minute charts, 50-100 bars (4-8 hours) is reasonable. For daily charts, 5-10 bars (1-2 weeks) is typical. Set to 0 to disable. Flatten near Session End (default: true): Whether to automatically close all positions as session end approaches. Recommended to avoid carrying positions into off-hours with low liquidity. Minutes before end (default: 5): How many minutes before session end to flatten. 5-15 minutes provides buffer for order execution before the session boundary. Visual Effects Configuration Group Dashboard Size (default: Normal): Controls information density in the dashboard. Small shows only critical metrics (excludes stop-out rate). Normal shows comprehensive data including stop-out rate. Large shows all available metrics including weights, session info, and volume analysis. Larger sizes consume more screen space but provide complete visibility. Show Quantum Field (default: true): Displays animated grid pattern on the chart indicating market state. Disable if you prefer cleaner charts or experience performance issues on lower-end hardware. Show Wick Pressure Lines (default: true): Draws dynamic lines from bars with extreme wicks, indicating potential support/resistance or liquidity absorption zones. Disable for simpler visualization. Show Morphism Energy Beams (default: true): Displays directional beams showing momentum energy flow. Beams intensify during strong trends. Disable if you find this visually distracting. Show Order Flow Clouds (default: true): Draws translucent boxes representing volume flow bullish/bearish bias. Disable for cleaner price action visibility. Show Fractal Grid (default: true): Displays multi-timeframe support/resistance levels based on fractal price structure at 10/20/30/40/50 bar periods. Disable if you only want to see primary pivot levels. Glow Intensity (default: 4): Controls the brightness and thickness of visual effects. Lower values (1-2) for subtle visualization. Higher values (7-10) for maximum visibility but potentially cluttered charts. Color Theme (default: Cyber): Visual color scheme. Cyber uses cyan/magenta futuristic colors. Quantum uses aqua/purple. Matrix uses green/red terminal style. Aurora uses pastel pink/purple gradient. Choose based on personal preference and monitor calibration. Show Watermark (default: true): Displays animated watermark at bottom of chart with creator credit and current P&L. Disable if you want completely clean charts or need screen space. Performance Characteristics and Best Use Cases Optimal Conditions This strategy performs best in markets exhibiting: Trending phases with periodic pullbacks: The combination of momentum and structure components excels when price establishes directional bias but provides retracement opportunities for entries. Markets with 60-70% trending bars and 30-40% consolidation produce the highest win rates. Medium to high volatility: The ATR-based stop sizing and dynamic risk adjustment require sufficient price movement to generate meaningful profit relative to risk. Instruments with 2-4% daily ATR relative to price work well. Extremely low volatility (<1% daily ATR) generates too many scratch trades. Clear volume patterns: The VPT volume component adds significant edge when volume expansions align with directional moves. Instruments and timeframes where volume data reflects actual transaction flow (versus tick volume proxies) perform better. Regular session structure: Futures markets with defined opening and closing hours, consistent liquidity throughout the session, and clear overnight/day session separation allow the session controls and time-based failsafes to function optimally. Sufficient liquidity for stop execution: The stop breakout entry mode requires that stop orders can fill without significant slippage. Highly liquid contracts work better than illiquid instruments where stop orders may face adverse fills. Suboptimal Conditions The strategy may struggle with: Extreme chop with no directional persistence: When ADX remains below 15 for extended periods and price oscillates rapidly without establishing trends, the momentum component generates conflicting signals. Win rate typically drops below 40% in these conditions, triggering the adaptive system to increase minimum score thresholds until conditions improve. Stop-out rates may also spike into the red zone. Gap-heavy instruments: Markets with frequent overnight gaps disrupt the continuous price assumptions underlying ATR stops and EMA-based structure analysis. Gaps can also cause stop orders to fill at prices far from intended levels, distorting stop-out rate metrics. Very low timeframes with excessive noise: On 1-minute or tick charts, the signal components react to micro-structure noise rather than meaningful price swings. The strategy works best on 5-minute through daily timeframes where price movements reflect actual order flow shifts. Extended low-volatility compression: During historically low volatility periods, profit targets become difficult to reach before mean-reversion occurs. The trail offset, even when set to minimum, may be too wide for the compressed price environment. Stop-out rates may drop to green zone indicating stops should be tightened. Parabolic moves or climactic exhaustion: Vertical price advances or selloffs where price moves multiple ATRs in single bars can trigger momentum signals at exhaustion points. The structure and reversal components attempt to filter these, but extreme moves may override normal logic. The adaptive learning system naturally reduces signal frequency and position sizing during unfavorable conditions. If you observe multiple consecutive days with zero trades and "FILTERS ACTIVE" status, this indicates the strategy has self-adjusted to avoid poor conditions rather than forcing trades. Instrument Recommendations Emini Index Futures (ES, MES, NQ, MNQ, YM, RTY): Excellent fit. High liquidity, clear volatility patterns, strong volume signals, defined session structure. These instruments have been extensively tested and the universal detection handles all contract specifications automatically. Micro Index Futures (MES, MNQ, M2K, MYM): Excellent fit for smaller accounts. Same market characteristics as the standard eminis but with reduced contract sizes allowing proper risk management on accounts below $50,000. Energy Futures (CL, NG, RB, HO): Good to mixed fit. Crude oil (CL) works well due to strong trends and reasonable volatility. Natural gas (NG) can be extremely volatile—consider reducing Base Risk to 0.3-0.4% and increasing Stop Loss ATR multiplier to 1.8-2.2 for NG. The strategy automatically detects the $10/tick value for CL and adjusts position sizing accordingly. Metal Futures (GC, SI, HG, PL): Good fit. Gold (GC) and silver (SI) exhibit clear trending behavior and work well with the momentum/structure components. The strategy automatically handles the different point values ($100/point for gold, $5,000/point for silver). Agricultural Futures (ZC, ZS, ZW, ZL): Good fit. Grain futures often trend strongly during seasonal periods. The strategy handles the unique tick sizes (1/4 cent increments) and point values ($50/point for corn/wheat, $60/point for soybeans) automatically. Treasury Futures (ZB, ZN, ZF, ZT): Good fit for trending rates environments. The strategy automatically handles the fractional tick sizing (32nds for ZB/ZN, halves of 32nds for ZF/ZT) through the universal detection system. Currency Futures (6E, 6J, 6B, 6A, 6C): Good fit. Major currency pairs exhibit smooth trending behavior. The strategy automatically detects point values which vary significantly ($12.50/tick for 6E, $12.50/tick for 6J, $6.25/tick for 6B). Cryptocurrency Futures (BTC, ETH, MBT, MET): Mixed fit. These markets have extreme volatility requiring parameter adjustment. Increase Base Risk to 0.8-1.2% and Stop Loss ATR multiplier to 2.0-3.0 to account for wider stop distances. Enable 24-hour trading and weekend trading as these markets have no traditional sessions. The universal futures compatibility means you can apply this strategy to any of these markets without code modification—simply open the chart of your desired contract and the strategy will automatically configure itself to that instrument's specifications. Important Disclaimers and Realistic Expectations This is a sophisticated trading strategy that combines multiple analytical methods within an adaptive framework designed for active traders who will monitor performance and market conditions. It is not a "set and forget" fully automated system, nor should it be treated as a guaranteed profit generator. Backtesting Realism and Limitations The strategy includes realistic trading costs and execution assumptions: - Commission: $0.62 per contract per side (accurate for many retail futures brokers) - Slippage: 1 tick per entry and exit (conservative estimate for liquid futures) - Position sizing: Realistic risk percentages and maximum contract limits based on account size - No repainting: All calculations use confirmed bar data only—signals do not change retroactively However, backtesting cannot fully capture live trading reality: - Order fill delays: In live trading, stop and limit orders may not fill instantly at the exact tick shown in backtest - Volatile periods: During high volatility or low liquidity (news events, rollover days, pre-holidays), slippage may exceed the 1-tick assumption significantly - Gap risk: The backtest assumes stops fill at stop price, but gaps can cause fills far beyond intended exit levels - Psychological factors: Seeing actual capital at risk creates emotional pressures not present in backtesting, potentially leading to premature manual intervention The strategy's backtest results should be viewed as best-case scenarios. Real trading will typically produce 10-30% lower returns than backtest due to the above factors. Risk Warnings All trading involves substantial risk of loss. The adaptive learning system can improve parameter selection over time, but it cannot predict future price movements or guarantee profitable performance. Past wins do not ensure future wins. Losing streaks are inevitable. Even with a 60% win rate, you will encounter sequences of 5, 6, or more consecutive losses due to normal probability distributions. The strategy includes losing streak detection and automatic risk reduction, but you must have sufficient capital to survive these drawdowns. Market regime changes can invalidate learned patterns. If the strategy learns from 50 trades during a trending regime, then the market shifts to a ranging regime, the adapted parameters may initially be misaligned with the new environment. The system will re-adapt, but this transition period may produce suboptimal results. Prop firm traders: understand your specific rules. Every prop firm has different rules regarding maximum drawdown, daily loss limits, consistency requirements, and prohibited trading behaviors. While this strategy includes common prop guardrails, you must verify it complies with your specific firm's rules and adjust parameters accordingly. Never risk capital you cannot afford to lose. This strategy can produce substantial drawdowns, especially during learning periods or market regime shifts. Only trade with speculative capital that, if lost, would not impact your financial stability. Recommended Usage Paper trade first: Run the strategy on a simulated account for at least 50 trades or 1 month before committing real capital. Observe how the adaptive system behaves, identify any patterns in losing trades, monitor your stop-out rate trends, and verify your understanding of the entry/exit mechanics. Start with minimum position sizing: When transitioning to live trading, reduce the Base Risk parameter to 0.3-0.4% initially (vs 0.5-1.0% in testing) to reduce early impact while the system learns your live broker's execution characteristics. Monitor daily, but do not micromanage: Check the dashboard daily to ensure the strategy is operating normally and risk controls have not triggered unexpectedly. Pay special attention to the Stop-Out Rate metric—if it remains in the red or green zones for multiple days, adjust your Stop Loss ATR multiplier accordingly. However, resist the urge to manually adjust adaptive weights or disable trades based on short-term performance. Allow the adaptive system at least 30 trades to establish patterns before making manual changes. Combine with other analysis: While this strategy can operate standalone, professional traders typically use systematic strategies as one component of a broader approach. Consider using the strategy for trade execution while applying your own higher-timeframe analysis or fundamental view for trade filtering or sizing adjustments. Keep a trading journal: Document each week's results, note market conditions (trending vs ranging, high vs low volatility), record stop-out rates and any Stop Loss ATR adjustments you made, and document any manual interventions. Over time, this journal will help you identify conditions where the strategy excels versus struggles, allowing you to selectively enable or disable trading during certain environments. Technical Implementation Notes All calculations execute on closed bars only (`calc_on_every_tick=false`) ensuring that signals and values do not repaint. Once a bar closes and a signal generates, that signal is permanent in the history. The strategy uses fixed-quantity position sizing (`default_qty_type=strategy.fixed, default_qty_value=1`) with the actual contract quantity determined by the position sizing function and passed to the entry commands. This approach provides maximum control over risk allocation. Order management uses Pine Script's native `strategy.entry()` and `strategy.exit()` functions with appropriate parameters for stops, limits, and trailing stops. All orders include explicit from_entry references to ensure they apply to the correct position. The adaptive learning arrays (trade_returns, trade_directions, trade_types, trade_hours, trade_was_stopped) are maintained as circular buffers capped at PERFORMANCE_MEMORY size (default 100 trades). When a new trade closes, its data is added to the beginning of the array using `array.unshift()`, and the oldest trade is removed using `array.pop()` if capacity is exceeded. The stop-out tracking system analyzes the trade_was_stopped array to calculate the rolling percentage displayed in the dashboard. Dashboard rendering occurs only on the confirmed bar (`barstate.isconfirmed`) to minimize computational overhead. The table is pre-created with sufficient rows for the selected dashboard size and cells are populated with current values each update. Visual effects (fractal grid, wick pressure, morphism beams, order flow clouds, quantum field) recalculate on each bar for real-time chart updates. These are computationally intensive—if you experience chart lag, disable these visual components. The core strategy logic continues to function identically regardless of visual settings. Timezone conversions use Pine Script's built-in timezone parameter on the `hour()`, `minute()`, and `dayofweek()` functions. This ensures session logic and daily/weekly resets occur at correct boundaries regardless of the chart's default timezone or the server's timezone. The universal futures detection queries `syminfo.mintick` and `syminfo.pointvalue` on each strategy initialization to obtain the current instrument's specifications. These values remain constant throughout the strategy's execution on a given chart but automatically update when the strategy is applied to a different instrument. The strategy has been tested on TradingView across timeframes from 5-minute through daily and across multiple futures instrument types including equity indices, energy, metals, agriculture, treasuries, and currencies. It functions identically on all instruments due to the percentage-based risk model and ATR-relative calculations which adapt automatically to price scale and volatility, combined with the universal futures detection system that handles contract-specific specifications.
Pine Script® strategy
by DskyzInvestments
Trend Pullback System```{"variant":"standard","id":"36492","title":"Trend Pullback System Description"} Trend Pullback System is a price-action trend continuation model that looks to enter on pullbacks, not breakouts. It’s designed to find high-quality long/short entries inside an already established trend, place the stop at meaningful structure, trail that stop as structure evolves, and warn you when the trade thesis is no longer valid. Developed by: Mohammed Bedaiwi --------------------------------- HOW IT WORKS --------------------------------- 1. Trend Detection • The strategy defines overall bias using moving averages. • Bullish environment (“uptrend”): price above the slower MA, fast MA above slow MA, and the slow MA is sloping up. • Bearish environment (“downtrend”): price below the slower MA, fast MA below slow MA, and the slow MA is sloping down. This prevents trading against chop and focuses on continuation moves in the dominant direction. 2. Pullback + Re-entry Logic • The script waits for price to pull back into structure (support in an uptrend, resistance in a downtrend), and then push back in the direction of the main trend. • That “push back” is the setup trigger. We don’t chase the first breakout candle — we buy/sell the retest + resume. 3. Structural Levels (“Diamonds”) • Green diamond (below bar): bullish pivot low formed while the trend is bullish. This marks defended support. - Use it as a re-entry zone for longs. - Use it to trail a stop higher when you’re already long. - Shorts can take profit here because buyers stepped in. • Red diamond (above bar): bearish pivot high formed while the trend is bearish. This marks defended resistance. - Use it as a re-entry zone for shorts. - Use it to trail a stop lower when you’re already short. - Longs can take profit here because sellers stepped in. 4. Entry Signals • BUY arrow (green triangle up under the candle, text like “BUY” / “BUY Zone”): - LongSetup is true. - Trend is bullish or turning bullish. - Price just bounced off recent defended support (green diamond) and reclaimed short-term momentum. Meaning: enter long here or cover/exit shorts. • SELL arrow (red triangle down above the candle): - ShortSetup is true. - Trend is bearish or turning bearish. - Price just rolled down from defended resistance (red diamond) and lost short-term momentum. Meaning: enter short here or take profit on longs. These are the primary trade entries. They are meant to be actionable. 5. Weak Setups (“W” in yellow) • Yellow triangle with “W”: - A possible long/short idea is trying to form, BUT the higher-timeframe confirmation is not fully there yet. - Think of it as early pressure / early caution, not a full signal. • You usually watch these areas rather than jumping in immediately. 6. Exit Warning (orange “EXIT” label above a bar) • The strategy will raise an EXIT marker when you’re in a trade and the *opposite* side just produced a confirmed setup. - You’re short and a valid longSetup appears → EXIT. - You’re long and a valid shortSetup appears → EXIT. • This is basically: “Close or reduce — the other side just took control.” • It’s not just a trailing stop hit; it’s a regime flip warning. 7. Stop, Target, and Trailing • On every new setup, the script records: - Initial stop: recent swing beyond the defended level (below support for longs, above resistance for shorts). - Initial target: recent opposing swing. • While you’re in position, if new confirming diamonds print in your favor, the stop can trail toward the new defended level. • This creates structure-based risk management (not just fixed % or ATR). 8. Reference Levels • The strategy also plots prior higher-timeframe closes (last week’s close, last month’s close, last year’s close). These can behave as magnets or stall points. • They’re helpful for take-profit timing and for reading “are we trading above or below last month’s close?” 9. Momentum Panel (hidden by default) • Internally, the script calculates an SMI-style momentum oscillator with overbought/oversold zones. • This is optional visual confirmation and does not drive the core entry/exit logic. --------------------------------- WHAT A TRADE LOOKS LIKE IN REAL PRICE ACTION --------------------------------- Early warning • Yellow W + red diamonds + red down arrows = “This is getting weak. Short setups are here.” • You may also see something like “My Short Entry Id.” That’s where the short side actually engages. Bearish follow-through, then exhaustion • Price bleeds down. • Then the orange EXIT appears. → Translation: “If you’re still short, close it. Buyers are stepping in hard. Risk of reversal is now high.” Regime flip • Right after EXIT, multiple green BUY arrows fire together (“BUY”, “BUYZone”). • That’s the true long trigger. → This is where you either enter long or flip from short to long. Expansion leg • After that flip, price rips up for multiple candles / days / weeks. • While it runs: - Green diamonds appear under pullbacks → “dip buy zones / trail stop up here.” - More BUY arrows show on minor pullbacks → continuation long / scale adds. Distribution / topping • Later, you start seeing new yellow W triangles again near local highs. That’s your “careful, this might be topping” warning. • You finally get a hard red candle, and green diamonds stop stacking. → That’s where you tighten risk, scale out, or assume the move is mature. In plain terms, the model is doing the following for you: • It puts you short during weakness. • It tells you when to get OUT of the short. • It flips you long right as control changes. • It gives you a structure-based trail the whole way up. • It warns you again when momentum at the top starts cracking. That is exactly how the logic was designed. --------------------------------- QUICK INTERPRETATION CHEAT SHEET --------------------------------- 🔻 Red triangle + “Short Entry” near a red diamond → Short entry zone (or take profit on a long). 🟥 Red diamond above bar → Sellers defended here. Treat it as resistance. Good place to trail short stops just above that level. Avoid chasing longs straight into it. 🟨 Yellow W → Attention only. Early pressure / possible turn. Not fully confirmed. 🟧 EXIT (orange label) → The opposite side just printed a real setup. Close the old idea (cover shorts if you’re short, exit longs if you’re long). Thesis invalid. 🟩 Burst of green BUY triangles after EXIT → Long entry. Also a “cover shorts now” alert. This is the core money entry in bullish reversals. 💎 Green diamond below bar → Bulls defended that level. Good for trailing your long stop up, and good “buy the dip in trend” locations. 📈 Blue / teal MAs stacked and rising → Confirmed bullish structure. You’re in trend continuation mode, so dips are opportunities, not automatic exits. --------------------------------- COLOR / SHAPE KEY --------------------------------- • Green triangle up (“BUY”, “BUY Zone”): Long entry / cover shorts / continuation long trigger. • Red triangle down: Short entry / take profit on longs / continuation short trigger. • Orange “EXIT” label: Opposite side just fired a real setup. The previous trade thesis is now invalid. • Green diamond below price: Bullish defended support in an uptrend. Use for dip buys, trailing stops on longs, and objective cover zones for shorts. • Red diamond above price: Bearish defended resistance in a downtrend. Use for re-entry shorts, trailing stops on shorts, and objective scale-out zones for longs. • Yellow “W”: Weak / early potential setup. Watch it, don’t blindly trust it. • Moving average bands (fast MA, slow MA, Hull MA): When stacked and rising, bullish control. When stacked and falling, bearish control. --------------------------------- INTENT --------------------------------- This system is built to: • Trade with momentum, not against it. • Enter on pullbacks into proven structure, not chase stretched breakouts. • Automate stop/target logic around actual defended swing levels. • Warn you when the other side takes over so you don’t give back gains. Typical usage: 1. In an uptrend, wait for price to pull back, print a green diamond (support proved), then take the first BUY arrow that fires. 2. In a downtrend, wait for a bounce into resistance, print a red diamond (sellers proved), then take the first SELL arrow that fires. 3. Respect EXIT when it appears — that’s the model saying “this trade is done.” --------------------------------- DISCLAIMER --------------------------------- This script is for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security, cryptoasset, or derivative. Markets carry risk. Past performance does not guarantee future results. You are fully responsible for your own decisions, position sizing, risk management, and compliance with all applicable laws and regulations.
Pine Script® strategy
by mbedaiwi2
HEK Dynamic Price Channel StrategyHEK Dynamic Price Channel Strategy Concept The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium. Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions. How It Works When the price reacts to the midline, the channel bands automatically reposition themselves. Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum. This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality. Advantages ✅ Maintains trend continuity while avoiding overtrading. ✅ Automatically adapts to changing volatility conditions. ✅ Detects early signals of short- and mid-term trend reversals. Applications Directional confirmation in spot and futures markets. A supporting tool in channel breakout strategies. Identifying price consolidation and equilibrium zones. Note This strategy is intended for educational and research purposes only. It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions. © HEK — Adaptive Channel Approach on Dynamic Market Structures
Pine Script® strategy
by hekorucuklu
1
Basic DCA Strategy by Wongsakon KhaisaengThe Core Principle and Philosophy Behind the Basic DCA Strategy 1. Introduction The Basic DCA Strategy (Dollar-Cost Averaging) represents one of the most fundamental and enduring investment methodologies in the realm of systematic accumulation. The philosophy underpinning DCA is rooted not in speculation or prediction, but in disciplined participation. It assumes that the consistent act of investing a fixed amount of capital over time—regardless of short-term price volatility—can yield superior long-term outcomes through the natural smoothing effect of cost averaging. This strategy, expressed through the Pine Script code above, formalizes the DCA concept into a fully systematic trading framework, enabling quantitative backtesting and objective evaluation of long-term accumulation efficiency. 2. Mechanism of Operation At its technical core, the strategy executes a fixed-value buy order at every predefined interval within a specific accumulation period. Each DCA event invests a constant “Investment Amount (USD)” irrespective of price fluctuations. When prices decline, this constant investment buys a larger quantity of the asset; when prices rise, it purchases fewer units. Over time, this behavior lowers the average cost basis of the accumulated position, effectively neutralizing short-term timing risks. Mathematically, this is represented as: Units Purchased = Investment Amount / Closing Price Cost Basis = Total Invested USD / Total Units Acquired Portfolio Value = Total Units Acquired × Current Price The algorithm tracks cumulative investment, acquired units, and commissions dynamically, continuously recalculating key portfolio metrics such as total profit/loss (PnL), CAGR (Compound Annual Growth Rate), and maximum drawdown (peak-to-trough equity decline). Furthermore, the script juxtaposes DCA results with a Buy & Hold benchmark, where the entire initial capital is invested at once. This comparison highlights the behavioral resilience and volatility resistance of the DCA method relative to market-timing strategies. 3. The Essence of DCA Philosophy At its philosophical core, DCA is not a trading system, but a behavioral framework for rational capital deployment under uncertainty. It embodies the principle that time in the market often outweighs timing the market. The DCA approach rejects the illusion of precision forecasting and embraces probabilistic humility—the recognition that even the most skilled investors cannot consistently predict short-term market fluctuations. Instead, it focuses on controlling what is controllable: the frequency, consistency, and size of investment actions. This mindset reflects a broader principle of risk dispersion through temporal diversification. Rather than concentrating entry risk into a single price point (as in lump-sum investing), DCA spreads exposure across multiple time intervals, thereby converting volatility into opportunity. In essence, volatility—often perceived as risk—is reframed as a mechanism for mean reversion advantage. The strategy thrives precisely because markets oscillate; each fluctuation provides a chance to accumulate at varied price levels, improving the weighted-average entry over time. 4. Long-Term Rationality Over Short-Term Emotion DCA’s endurance stems from its ability to neutralize emotional biases inherent in human decision-making. Investors tend to overreact to market euphoria or panic—buying high out of greed and selling low out of fear. By automating purchases through predefined intervals, the DCA model enforces mechanical discipline, detaching decision-making from sentiment. This transforms investing from an emotional endeavor into a systematic, algorithmic routine governed by rules rather than reactions. In doing so, DCA serves not only as a financial model but also as a psychological safeguard—aligning investor behavior with long-term compounding logic rather than short-term speculation. 5. Comparative Insight: DCA vs. Buy & Hold While both DCA and Buy & Hold share a long-term investment horizon, they diverge in their treatment of entry timing. The Buy & Hold model assumes full deployment of capital at the beginning, maximizing exposure to growth but also to volatility. Conversely, DCA smooths the entry curve, trading off short-term returns for long-term stability and improved average entry price. In environments characterized by volatility and cyclical corrections, DCA tends to outperform in terms of risk-adjusted returns, lower drawdowns, and improved investor adherence—since it reduces the psychological pain of entering at local peaks. 6. Conclusion The Basic DCA Strategy exemplifies the synthesis of mathematical rigor and behavioral discipline. Its algorithmic construction in Pine Script transforms a classical investment philosophy into a quantifiable, testable, and transparent framework. By automating fixed-amount purchases across time, the system operationalizes the central axiom of DCA: consistency over conviction. It is not concerned with predicting future prices but with ensuring persistent participation—trusting that the market’s upward bias and the power of compounding will reward patience more than precision. Ultimately, DCA embodies the timeless principle that successful investing is less about forecasting markets, and more about designing behavior that can endure them.
Pine Script® strategy
by Wongsakon
Mean Reversion Trading V1Overview This is a simple mean reversion strategy that combines RSI, Keltner Channels, and MACD Histograms to predict reversals. Current parameters were optimized for NASDAQ 15M and performance varies depending on asset. The strategy can be optimized for specific asset and timeframe. How it works Long Entry (All must be true): 1. RSI < Lower Threshold 2. Close < Lower KC Band 3. MACD Histogram > 0 and rising 4. No open trades Short Entry (All must be true): 1. RSI > Upper Threshold 2. Close > Upper KC Band 3. MACD Histogram < 0 and falling 4. No open trades Long Exit: 1. Stop Loss: Average position size x ( 1 - SL percent) 2. Take Profit: Average position size x ( 1 + TP percent) 3. MACD Histogram crosses below zero Short Exit: 1. Stop Loss: Average position size x ( 1 + SL percent) 2. Take Profit: Average position size x ( 1 - TP percent) 3. MACD Histogram crosses above zero Settings and parameters are explained in the tooltips. Important Initial capital is set as 100,000 by default and 100 percent equity is used for trades
Pine Script® strategy
by Sivchay
Iriza4 -DAX EMA+HULL+ADX TP40 SL205 MIN SKALP. Additional filters improve accuracy: the strategy blocks trades after too many consecutive bullish or bearish candles (streak filter) and ignores signals when price is too far from the EMA (measured by ATR distance). Each position uses a fixed risk-to-reward ratio of 1 : 2 with clear stop-loss and take-profit targets, without partial exits or breakevens. The goal is to identify clean pullbacks inside strong trends and filter out late or exhausted entries
Pine Script® strategy
by Radoje1984
Empire OS Trading Fully Automated Prop Firm Ready💎 Prop-Firm-Ready Momentum System v3 — The Gold-Mine Algorithm 💎 Engineered for the same standards that top prop firms demand — minimal drawdown, consistent equity growth, and precision-based execution. This isn’t a basic indicator; it’s a refined momentum engine built for traders who scale capital and manage risk like professionals. Performance Snapshot • Profit Factor 2.26 • Win Rate 33 % • Max Drawdown 0.9 % • Total P/L + $447 • W/L Ratio 4.6 : 1 Stress-tested on Gold (XAUUSD) across live-market conditions, it stays composed under volatility and delivers structured, data-driven consistency. ⚡ See it. Test it. Scale it. Built for prop-firm precision — from $10 K to $300 K and beyond.
Pine Script® strategy
by Empire-OS-Trading
XAUUSD 5m — NY Supertrend+RSI Optimizer (1:2 RR) — $240k/orderThis strategy is built for XAUUSD (Gold) on the 5-minute timeframe, focusing exclusively on the New York trading session (08:00–17:00 NY time) — the most volatile and liquid hours of the day. It combines a Supertrend trend filter with RSI momentum signals to identify high-probability entries, using a 1:2 risk–reward ratio for disciplined trade management. 🧠 Strategy Logic: Buy Condition: RSI crosses above 55 while Supertrend indicates an uptrend Sell Condition: RSI crosses below 45 while Supertrend indicates a downtrend Session Filter: Trades only between 08:00 → 17:00 New York time Risk/Reward: 1:2 (Take-Profit = 2× Stop-Loss distance from Supertrend line) Position Size: $240,000 notional per order Auto-Exit: Closes all trades at NY session end ⚡ Highlights: Targets NY session volatility Combines trend + momentum for cleaner entries Strict 1:2 RR for consistent outcomes Avoids overnight exposure ⚠️ Disclaimer: This script is intended for educational and research purposes only. Past performance is not indicative of future results. Always forward-test on demo before using live capital.
Pine Script® strategy
by legalPepper72284
XAUUSD 5m — CET 13:00→01:00 Supertrend + RSI (1:2 RR) — $240KThis strategy is designed for XAUUSD (Gold) on the 5-minute chart, optimized for trading during the most active hours (13:00–01:00 CET). It combines a Supertrend direction filter with RSI crossovers for precise entries, and applies a 1:2 risk–reward ratio for consistent risk management. 🧠 Logic Overview: Buy Signal: RSI crosses above 55 while Supertrend is bullish Sell Signal: RSI crosses below 45 while Supertrend is bearish Trading Hours: 13:00 → 01:00 CET (corresponding to 07:00 → 19:00 New York time) Risk Management: Fixed 1:2 RR (TP = 2× SL distance from Supertrend line) Session Management: Automatically closes all trades after 01:00 CET Order Size: $240,000 notional exposure per position 💡 Best used for: Scalping or intraday trading on XAUUSD during high-volatility hours. The setup works best when combined with strong price action or volume confirmation. ⚠️ Disclaimer: This script is for educational and testing purposes only. Past performance does not guarantee future results. Always test on demo before using live funds.
Pine Script® strategy
by legalPepper72284
Nifty Intraday 9:30- 3 Min Candle By Trade Prime Algo.Nifty Intraday 9:30 – 3 Min Candle Strategy by Trade Prime Algo This strategy is designed to help traders identify intraday long entries, stop-loss, and multi-target levels on the Nifty Spot / Nifty Futures based on the first 3-minute candle breakout after 9:30 AM. It automates trade detection, entry marking, target plotting, and trailing stop-loss logic, allowing traders to visualize complete trade flow with clarity and precision. The system offers: ✅ Auto identification of long entries based on candle breakout logic ✅ Configurable stop-loss, trailing SL, and four partial profit targets ✅ Dynamic plotting of entry, TSL, and targets on chart ✅ Custom alert messages for each event (Entry, TP1–TP4, SL, Close) ✅ Adjustable time session and test periods for backtesting ⚙️ How to Use 1️⃣ Set your desired start time (default: 9:15–9:30 AM). 2️⃣ Choose your stop-loss type — percentage or points. 3️⃣ Adjust target levels (TP1–TP4) and trailing SL settings as per your risk appetite. 4️⃣ Use this strategy for educational backtesting and research only — not for live trading signals. 5️⃣ The tool can be combined with price action zones or higher-timeframe analysis for best results. ⚠️ Disclaimer (SEBI & Risk Disclosure) This strategy is developed strictly for educational and research purposes. The creator of this script and Trade Prime Algo are not SEBI-registered advisors. This tool does not guarantee any specific profit or performance. Trading involves risk; users may incur partial or total capital loss. All decisions taken using this indicator or strategy are solely at the user’s discretion and risk. The creator assumes no liability for profit, loss, or any consequences arising from the use of this script. Always perform your own due diligence and trade responsibly.
Pine Script® strategy
by healingcrystalsusa
Trendline Breakout Strategy Strategy should place entries & exits so that it can be backtested (use strategy.entry and strategy.exit with explicit stop and limit prices). Include an option for fixed percent position sizing and an option for fixed contract size. Draw the trendline on the chart (with option to hide/show) and add labels that show: bias (Bull/Bear), trendline slope, entry price, SL, TP and the reason (e.g., "Trendline Breakout"). Provide user inputs for: EMA length (default 200), lookback for pivot detection, pivot sensitivity (left/right bars), quantity mode (percent / contracts), risk percent or fixed size, enable/disable backtest prints, and enable alerts. Avoid repainting: use confirmed pivot logic (pivot detection must use completed bars) and only take entry after breakout confirmed on close. Document any limitations (for example, trendline using two highest/highest bars inside lookback is approximate). Add clear comments, helpful variable names, and include example alertcondition lines for entry and exit signals.
Pine Script® strategy
by chandolaamit
AIBTC Automated Trading Strategy🧠 AIBTC Automated Trading Strategy Overview: The AIBTC Automated Trading Strategy is a fully autonomous system designed for 4-hour timeframes (4H). It dynamically identifies support and resistance levels based on price action, and automatically executes trades when valid breakouts occur above resistance or below support. The system adapts in real time to changing market volatility, ensuring stable performance across different market conditions. ⚙️ Strategy Logic Dynamic Support & Resistance Detection The strategy uses an adaptive Pivot Point algorithm that adjusts parameters according to market volatility (ATR) and price deviation (Standard Deviation). When volatility increases, the algorithm automatically widens its detection range and recalibrates channel width for better accuracy. All support and resistance levels are detected dynamically — no manual configuration is required. Trend & Volatility Filtering The system applies ADX (Average Directional Index) to measure trend strength. When ADX > 25, only strong levels are considered valid to avoid noise during weak trends. ATR-based volatility adjustments automatically optimize lookback periods and detection sensitivity. Breakout Signal Detection A long position is triggered when price breaks above resistance with a valid breakout margin (default filter: 0.1%). A short position is triggered when price breaks below support with the same breakout filter applied. This breakout filter effectively minimizes false breakouts and improves signal quality. Fully Automated Execution The system is designed for both backtesting and live simulation. All buy/sell entries are executed automatically without manual input once conditions are met. 🕒 Recommended Timeframe 4-hour (4H) candles Suitable for short-to-medium term swing trading, balancing signal precision and trade frequency. 📊 Key Features ✅ Fully Automated — Executes long/short positions on valid breakouts ✅ Adaptive Parameters — Automatically adjusts to changing volatility ✅ Trend-Aware Filtering — Uses ADX to avoid false signals in ranging markets ✅ Multi-Asset Compatibility — Works on BTC, ETH, or any high-liquidity instrument ⚠️ Disclaimer This strategy is a technical and algorithmic tool, not financial advice. Always backtest and simulate before using it on live markets. During periods of extreme volatility, signals may delay or show false breakouts — consider using stop-loss mechanisms accordingly.
Pine Script® strategy
by czkingnft12
One For All Strategy by Anson🏆 Exclusive Indicator: One For All Strategy . 📈 Works for stocks, forex, crypto, indices 📈 Easy to use, real-time alerts, no repaint 📈 No grid, no martingale, no hedging 📈 One position at a time . One For All Strategy by Anson A multi-indicator TradingView strategy designed to identify long and short trading opportunities by combining trend-following and momentum signals, paired with risk management rules to guide entries and exits. . Core Logic & Key Indicator: X Moving Average: A proprietary adaptive moving average that adjusts its responsiveness to price changes based on market volatility. It uses an efficiency ratio to modify its smoothing behavior—adapting to whether the market is trending or ranging. Users can toggle a setting to let this ratio dynamically adjust the indicator’s sensitivity or use a fixed smoothing factor. . Entry Conditions: . Long Entry: Triggered when momentum signals strength, price action aligns with a broader upward trend, the X MA indicates short-term upward momentum, and a minimum number of bars have passed since the last trade (to prevent overtrading). . Short Entry: Triggered when momentum signals weakness, price action aligns with a broader downward trend, the X MA indicates short-term downward momentum, and a minimum number of bars have passed since the last trade. . Exit Conditions: . Trailing Stop: Activates after a position has been open for a set number of bars (to avoid premature exits). A trailing stop—based on a percentage of the entry price—locks in profits as the trade moves favorably, adjusting dynamically to protect gains. . Additional Features: Visualisation: Overlays the X MA (orange line) and price (semi-transparent blue) on the chart for clear signal tracking. . See the author's instructions on the right to learn how to get access to the strategy.
Pine Script® strategy
by anson5129
1
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL Summary in one paragraph FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close. Scope and intent • Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs • Timeframes. One minute to daily • Default demo used in the publication. SPY on 30min • Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state • Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes • Testability. All windows and gains are inputs • Portable yardstick. Returns use natural log units and range is bar high minus low • Protected scripts. Not used. Method disclosed plainly here Method overview in plain language Base measures • Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion Components • Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized • Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression • Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves • Energy score. Z scores of the above form a single energy that controls the state gain • One bar projection. Current slope extended by one bar for anticipatory checks Fusion rule Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push. Signal rule • Long suggestion and order when close is below trend and the one bar projection is above the trend • Short suggestion and flip when close is above trend and the one bar projection is below the trend • WAIT is implicit when neither condition holds • In position states end on the opposite condition What you will see on the chart • Colored trendline teal for rising red for falling gray for flat • Optional projection line one bar ahead • Optional background can be enabled in code • Alerts on price cross and on slope flips Inputs with guidance Setup • Price source. Close by default Logic • Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips • Vol window. Typical range 30 to 120. Higher calms curvature • Energy window. Typical range 20 to 80. Higher slows regime changes • Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop UI • Show 1 bar projection. Colors for up down flat Properties visible in this publication • Initial capital 25000 • Base currency USD • Commission percent 0.03 • Slippage 5 • Default order size method percent of equity value 3% • Pyramiding 0 • Process orders on close off • Calc on every tick off • Recalculate after order is filled off Realism and responsible publication • No performance claims • Intrabar reminder. Shapes can move while a bar forms and settle on close • Strategy uses standard candles only Honest limitations and failure modes • Sudden gaps and thin liquidity can still produce fast flips • Very quiet regimes reduce contrast. Use larger windows and lower max gain • Session time uses the exchange time of the chart if you enable any windows later • Past results never guarantee future outcomes Open source reuse and credits • None
Pine Script® strategy
by exlux