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PJSTR_Multi_Confluence_Gates&ExitsPJSTR Multi Confluence Gates & Exits A non-repainting, confluence-based strategy designed to study and optimize long-biased market participation across multiple crypto assets and timeframes. This script combines several widely used technical concepts into a modular framework where filters can be enabled or disabled to evaluate their impact on signal quality, drawdown behavior, and trade consistency. The default configuration is optimized for a 4-hour chart, but the logic is adaptable to other markets and settings. Key characteristics • Confluence-based logic using multiple independent filters • Non-repainting design with bar-close evaluation • Long-biased, spot-oriented approach (no leverage, no pyramiding) • Strong safety mechanisms to help control drawdown • Modular structure suitable for different assets and market regimes • Designed for research, evaluation, and strategy development • Multi-switchable Plots for the filters, Buy-Gates and Exits Performance context Back testing shows that the strategy can outperform a passive buy-and-hold approach under certain market conditions, while aiming to keep maximum equity drawdown as controlled as possible. Results vary depending on asset, timeframe, and settings. Usage notes This script is provided for educational and analytical purposes. Default settings are example parameters and may require adjustment for different instruments or market environments. Back testing results are historical simulations and not guarantees of future performance. Automation & alerts This strategy can be used with TradingView alerts at the user’s discretion and in accordance with platform guidelines.
Strategi Pine Script®
oleh PJooris1408
TradeX ORB Sniper v3.6Breakout Strategy Framework TradeX ORB Sniper v3.6 is a closed-source breakout strategy framework designed to identify and manage structured opening range breakouts across different session models and market conditions. It is not a simple ORB line tool or a mashup of existing public indicators. All calculations and logic are developed in-house and operate under a unified internal rule engine. The framework standardizes how opening ranges are defined, measured, and evaluated, allowing users to objectively study breakout behavior and execution structure across multiple range constructions without changing tools or visual logic. Core Concept ORB Sniper implements four internally coded opening range modes, each defining the range differently based on time, session structure, and market behavior: Pre-market session range 5-minute opening range 15-minute opening range Volume-adaptive range model Users can toggle between these four variations while the underlying breakout logic remains consistent. Rather than relying on generic fixed boxes, each range mode applies the same internal rule structure so that breakout conditions can be identified, reviewed, and compared within a controlled and repeatable framework. This design allows traders to evaluate how different opening range constructions behave as entry frameworks under identical execution rules. Breakout Detection & Entry Logic A breakout condition is recognized only when a candle closes outside the active range. When this occurs, the framework highlights that candle as a visual event marker (“Get Ready Candle”), indicating that the range has structurally resolved and directional bias is defined. This marker represents the strategy’s primary setup trigger and identifies the point at which the framework considers a valid breakout condition to exist. Range-Based Risk & Target Structure Following a breakout trigger, the framework projects two calculated zones derived directly from the selected opening range: Risk Zone Defines the invalidation area for the breakout thesis. If price retraces into this zone, the breakout condition is considered failed based on the framework’s internal logic. Continuation Zone Represents a measured-move projection derived from the same range calculations. This zone maps the expected expansion objective associated with the breakout structure. Both zones are mathematically linked to the internally calculated range and update dynamically based on the active mode. They are not static multipliers or arbitrary drawings, but proportional extensions of the opening range structure itself. Customization & Inputs The framework allows user-level customization of visual and structural components, including: Range mode selection (V1–V4) Risk zone color Continuation zone color Breakout candle highlight color Optional status line display These inputs allow adaptation to different instruments, sessions, and chart layouts while preserving the underlying strategy logic. Development Methodology The range models and projection logic were originally prototyped and tested in Python using historical market data. Variations in volume behavior, volatility structure, and session timing were evaluated to refine how ranges are constructed and how post-breakout behavior is measured. The most stable rule sets were then implemented into Pine Script as a closed-source framework to maintain consistency and prevent discretionary reinterpretation of the strategy model. Intended Use This script is designed to function as a structured opening range breakout framework. It provides: Defined breakout conditions based on opening range resolution Directional bias confirmation via close-based breakout detection Calculated risk and continuation zones derived from range structure A repeatable, rules-based method for evaluating breakout setups The script does not auto-execute trades and does not guarantee profitability. Default settings are provided as a starting configuration. Users are expected to evaluate and optimize parameters based on their own instruments, sessions, timeframes, and risk preferences. Originality Statement TradeX ORB Sniper is a proprietary framework. While it incorporates widely known market concepts such as opening ranges and volume behavior, it applies them through an original internal rule structure governing: How ranges are calculated How breakouts are confirmed How risk and continuation zones are derived How all modes remain behaviorally consistent within a unified strategy model It is not a mashup of public indicators and does not rely on built-in strategy templates or public-domain scripts. Strategy Testing & Risk Controls (New) To support systematic evaluation and controlled backtesting, the framework includes a dedicated risk management section designed specifically for use with the Strategy Tester. Users can define: Risk parameters applied directly to strategy tester executions, allowing comparison of different ORB variations under consistent risk assumptions. A maximum contract size, which helps normalize results and prevents unrealistic position sizing in backtests. These controls are intended to support research and optimization, allowing users to evaluate how different opening range constructions, filters, and risk constraints affect performance across historical data. The strategy tester functionality is not intended to be used as a blind signal generator, but as a tool for structured analysis and variation testing. Additional Breakout Filtering (New) An optional ORB Wick Rejection Filter has been added. When enabled, breakout conditions are filtered to only allow setups where price demonstrates a wick rejection at the defined opening range. This filter is designed to help isolate breakout attempts where liquidity interaction occurs at the range boundary before continuation, reducing lower-quality breakout conditions while preserving the core breakout logic. Visual Configuration All major visual components of the framework can be customized through user inputs, including: Risk zone color Continuation (reward) zone color Breakout (“Get Ready”) candle highlight color Label font size These options allow users to adapt the framework to different chart styles and layouts while keeping all calculations and execution logic unchanged. Default Strategy Tester settings use realistic assumptions for position sizing, commission, and slippage to avoid overstating historical performance.
Strategi Pine Script®
oleh tradexictsmc
1M Intraday TrendCapture: Momentum Reclaim Pattern (MRP) Overview This is a high-precision intraday trend-following strategy designed specifically for the 1-minute timeframe on major indices (Nifty, BankNifty, etc.). It utilizes the Momentum Reclaim Pattern (MRP), which focuses on entering trades only after a confirmed momentum expansion followed by a structural reclaim. Core Logic The strategy combines three layers of confirmation to filter out market noise: Trend Bias (Multi-Timeframe CCI): Uses a proprietary CCI alignment across 1m, 3m, and 5m timeframes to identify Overbought/Oversold exhaustion points before a trend reversal. Trend Filter (EMA Stack): Uses a triple EMA sequence (108, 216, 324) to ensure trades are only taken in the direction of the institutional trend. Structural Trigger (Fractal Pivots): Entries are triggered only when price breaks a confirmed Fractal High (for Longs) or Fractal Low (for Shorts). Key Features Dynamic RR Plotting: Automatically draws and expands Risk/Reward boxes (Stop Loss and Take Profit zones) in real-time. Intraday Time Windows: Built-in session controls to avoid "choppy" market openings and late-day volatility. Includes a Pause Window for mid-day lunch hours. Risk Management: Calculates position sizing based on a fixed Rupee risk (e.g., ₹2400 per trade) and automatically adjusts for different Index lot sizes. Automated Targets: Selectable RR ratios from 1:1 up to 1:9 via the user settings. Visual Dashboard: On-screen labels for "Get Ready" setups, including strike price suggestions (CE/PE) and risk point calculations. How to Use Setup: Look for the "GET READY" label and the orange risk highlight box. Execution: The strategy enters automatically (or provides a signal) when price breaks the structural fractal levels. Exit: The strategy plots a green TP zone and a red SL zone. It manages the exit via the built-in strategy.exit logic. Note: This script is optimized for the 1-minute chart. It is highly recommended to keep "Process orders on close" enabled for backtesting accuracy.
Strategi Pine Script®
oleh Manonidhi09
Solaris BankNifty Strategy Overview • Rather than using decorative or complex visuals the chart is intentionally kept simple and uncluttered to emphasize readability and precision over aesthetics. • Calibrated for 5 minute intraday charts. These settings are for Bank Nifty • Each asset (stocks, indices, commodities, cryptocurrencies, etc..) requires individual calibration. • Since market dynamics shift weekly, how can indicator values stay constant, and how can one asset’s settings apply to all assets? • Retracement entry is best. • Restrict trading to the first two signals per day. • Fine tune input values weekly to adjust for changing volatility. • Refer to the above pic for value setting. Strategy Settings • More than 80% of trades should be profitable (calibration goal). • Minimum of 7 (more is better) trades in the last 30 days . • Strategy uses 10 input values that must be precisely fine tuned. Important Notes • There is no holy grail—discipline and risk management are essential. • Always forward test thoroughly before live trading. • For questions, feel free to DM me. Current settings for Bank nifty Index Sun 5.8 Pluto 61 Mars 20 Charon 1 9 Charon 2 21 Rahu 0.55 Laxmi 2 Sun Moon A 20 Mercury 26 ISM 0.5 In style untick following for clean chart-- Bar color Trades on chart Signal labels Quantity Disclaimer : This strategy is for educational and research purposes only and should not be considered investment advice. Always conduct your own research and consult your financial advisor before making trading decisions. Past performance does not guarantee future results. For any query feel free to DM me
Strategi Pine Script®
oleh Trader-Solaris
VANTYX Scalper Bot DR ABIRAM SIVPRASADVANTYX Scalper Bot – Trend & Momentum System Strategy Overview VANTYX™ Scalper Bot is a high-precision algorithmic trading strategy designed for Crypto & Forex scalping. It combines multi-timeframe trend analysis with momentum validation to filter out noise and capture high-probability moves. This specific version includes a "Reversal Fix" engine, meaning it auto-corrects bias: if a Long condition is met while a Short is active, it immediately closes the Short and flips Long (and vice versa), ensuring you are always on the right side of the immediate trend. Core Technology & Indicators This strategy does not rely on a single indicator. Instead, it uses a "Confluence Engine" requiring 4 layers of confirmation before taking a trade: 1. Half Trend (Primary Signal) Acts as the immediate trigger for entry. Uses a proprietary amplitude algorithm to detect valid trend shifts while ignoring minor chop. Bullish: Price breaks above the Half Trend channel. Bearish: Price breaks below the Half Trend channel. 2. Multi-Timeframe (MTF) ADX & DMI Momentum Filter: The strategy checks the ADX (Average Directional Index) on a higher timeframe (default: 15m) to ensure the trend has real strength. Threshold: Trades are only taken if ADX > 23 (configurable), preventing entries during dead/ranging markets. Non-Repainting: Uses strict "bar merge" logic to ensure backtest results match live performance. 3. MTF EMA Trend Filter The "Big Trend" Guardrail: Checks a higher timeframe EMA (default: 200 EMA on 1H) to define the macro bias. Rule: The bot will ONLY Long if price is above the MTF EMA, and ONLY Short if price is below it. This prevents "catching falling knives." 4. Volume Validation Fakeout Prevention: Checks if the current volume is above the Volume Moving Average (20-period). Logic: Volume must confirm price action. Low-volume breakouts are ignored. Risk Management (VANTYX AI Logic) The bot features a dynamic, ATR-based risk engine that adapts to market volatility: Dynamic Stop Loss: Hard Stop is calculated using ATR (default 1.5x). In volatile markets, the stop widens; in quiet markets, it tightens. Take Profit: Fixed ATR-based target (default 3.0x). Trailing Stop (Ratchet System): Once in profit, a Trailing Stop activates. For Longs: The stop only moves UP. For Shorts: The stop only moves DOWN. This locks in profits during strong impulsive moves. ⚙️How to Use & Best Settings Recommended Timeframe: 1 minute - 5 minutes (for Scalping). Asset Class: Crypto Perpetuals (BTC, ETH, SOL) or Major Forex Pairs. Default Settings: ADX TF: 15 Minutes EMA TF: 60 Minutes Risk: 1.5x SL / 3.0x TP / 2.0x Trail Customization: All parameters (Amplitude, EMA lengths, ATR multipliers) are fully adjustable in the settings menu. Alert Setup This strategy is fully Alert-Ready for automation (3Commas, PineConnector, etc.). Add to Chart. Create Alert -> Select "VANTYX Scalper Bot". IMPORTANT: Select "Order Fills Only" in the action settings. The bot will output "LONG ENTRY", "EXIT LONG", etc., dynamically. Disclaimer This script is for educational and backtesting purposes only. Past performance does not guarantee future results. Please manage your risk responsibly and test on a demo account before live trading. Trade Safe. Trade Smart. ~ Dr. Abhiram SS
Strategi Pine Script®
oleh abiramsivprasad
Strategy: Institutional Liquidity Engin💎 Institutional Liquidity Engine Introducing the flagship update to our trading system, engineered at the intersection of statistical analysis and market gravity models. Version 25.2 isn't just a strategy—it’s a comprehensive engine designed to hunt and execute based on institutional liquidity. 🧠 What’s New in v25.2? Unlike traditional indicators, this engine analyzes the market as a physical system where liquidity levels possess "mass" and "attraction." Core Technology Modules: Gravity Model 2.0 🧲 — The system calculates a dynamic Gravity Ratio. When price is squeezed between large order blocks, the algorithm determines which side has the strongest "magnetism," applying a Decay Constant to age out stale levels. HTF Context Bias 🌐 — A built-in High-Timeframe (H1) filter. The system blocks shorts during strong bullish hourly closes and vice versa, preventing you from trading against the primary institutional flow. Adaptive Z-Score Normalization 📊 — Every "sweep" (liquidity grab) undergoes a statistical stress test. A signal is only generated when the Confidence Level exceeds 70%, based on volume anomalies and volatility expansion. Shutterstock Открыть Cause Model 2.0 🏗️ — Based on the law of "Cause and Effect." The algorithm measures the quality of consolidation (compression). The longer the market builds a "Cause," the more ambitious the Take Profit targets become. 🛡 Risk Management & Execution The system features a Dynamic Risk Scaling module. Position size is never static—it adaptively increases when signals align with the HTF trend and gravity bias, and scales down during "choppy" market regimes. Anti-Chop Logic: Automatically blocks entries in the middle of a range when ADX is low. Automatic Scale-out: Locks in 50% profit at the first target to move the trade to Breakeven. ML Feature Export: Every trade generates a high-dimensional data vector (Z-Score, Confidence, Gravity Ratio, Vol Ratio) ready for neural network training. 📋 Specifications: Platform: Pine Script v5 (TradingView) Type: Mean Reversion / Momentum Continuation (on Sweeps) Assets: Futures, Crypto, FX (Optimized for high-volatility instruments) Timeframe: M5 execution with H1 context analysis Summary: This is a professional-grade workspace for traders who want to move beyond "indicators" and trade the underlying logic of liquidity and statistical anomalies. #TradingView #PineScript #SmartMoney #LiquidityEngine #AlgoTrading #QuantitativeTrading #MachineLearning #FinTech
Strategi Pine Script®
oleh Evgenii_Novokshonov
Swing Strategy Feature Set W [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set W includes concepts beginning with the letter "W" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Wave Period Oscillator Williams Accumulation/Distribution Williams Variable Accumulation/Distribution Williams Fractal Williams Percent Range █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET W SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com As there are no built-in TradingView indicators for the WPO, WAD and WVAD values used in this script, code samples are provided in the relevant sections so that users can build their own Pine Script indicators. For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com Wave Period Oscillator (WPO) Filters As there is no built-in indicator for the WPO value used in this script, users can build their own WPO indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Wave Period Oscillator", shorttitle = "WPO", overlay = false) import TradingView/ta/12 as ta wpo_length = input.int(title = 'WPO Length', defval = 10, minval = 1, group = 'Wave Period Oscillator (WPO)') wpo = ta.wpo(wpo_length) plot(wpo, color = color.blue) The default WPO length is set to 10. Users can adjust the WPO length via strategy Settings/Inputs/WAVE PERIOD OSCILLATOR (WPO). The WPO minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply WPO above-equal is set to false. WPO above-equal threshold is set to -100. Apply WPO below-equal is set to false. WPO below-equal threshold is set to 0. The WPO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The WPO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the WPO filters and adjust filter parameters via strategy Settings/Inputs/WPO FILTERS. Williams Accumulation/Distribution (WAD) Filters As there is no built-in indicator for the WAD value used in this script, users can build their own WAD indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Williams Accumulation/Distribution", shorttitle = "WAD", overlay = false) wad = ta.wad plot(wad, color = color.blue) The WAD minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The WAD trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the WAD filters and adjust filter parameters via strategy Settings/Inputs/WILLIAMS ACCUMULATION/DISTRIBUTION (WAD) FILTERS. Williams Variable Accumulation/Distribution (WVAD) Filters As there is no built-in indicator for the WVAD value used in this script, users can build their own WVAD indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Williams Variable Accumulation/Distribution", shorttitle = "WVAD", overlay = false) wvad = ta.wvad plot(wvad, color = color.blue) The WVAD minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The WVAD trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the WVAD filters and adjust filter parameters via strategy Settings/Inputs/WILLIAMS VARIABLE ACCUMULATION/DISTRIBUTION (WVAD) FILTERS. Williams Fractal (WF) Filter Although TradingView provides a built-in WF indicator that users may apply as a visual aid, the fractal logic used in this script is hard-fixed to a 2-period WF calculation. This fixed length ensures structural compatibility with the core swing high and swing low entry logic used throughout the strategy. Fractal lengths greater than 2 would introduce confirmation delays that conflict with the strategy’s swing completion rules and would therefore be incompatible with the intended entry structure. The WF filter is defined as an entry filter that requires structural alignment between swing conditions and confirmed fractal signals. When applied: For long trades, the filter returns true only when a swing low forms and a 2-period up fractal is confirmed. For short trades, the filter returns true only when a swing high forms and a 2-period down fractal is confirmed. By default, the WF filter is set to false. Users can apply the WF filter via strategy Settings/Inputs/WILLIAMS FRACTAL (WF) FILTER. Williams Percent Range (WPR) Filters The default WPR settings are as follows: Length is set to 14. Source is set to "Close". Users can adjust the WPR inputs via strategy Settings/Inputs/WILLIAMS PERCENT RANGE (WPR). The WPR minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply WPR above-equal is set to false. WPR above-equal threshold is set to -100. Apply WPR below-equal is set to false. WPR below-equal threshold is set to 0. The WPR minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The WPR trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the WPR filters and adjust filter parameters via strategy Settings/Inputs/WPR FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Strategi Pine Script®
oleh theEccentricTrader
MACD HTF - Accurate Backtest Metrics// ╔══════════════════════════════════════════════════════════════════════════════╗ // ║ MACD HTF STRATEGY WITH ACCURATE BACKTEST ║ // ╚══════════════════════════════════════════════════════════════════════════════╝ // // 📊 STRATEGY OVERVIEW: // This advanced MACD strategy allows you to execute trades based on Higher Timeframe (HTF) // signals while operating on lower timeframe charts for precise entry timing. // // ⚡ KEY FEATURES: // • Higher Timeframe Signal Detection (e.g., 15min signals on 1min chart) // • Accurate Backtest Calculations with Commission & Slippage // • Trailing Stop Loss with Offset // • Hard Stop Loss (Percentage or Points based) // • Cooldown Period after trade exits // • Detailed Performance Metrics Panel // • Visual Stop Loss Lines // • Real-time Signal State Tracking // // 📈 HOW IT WORKS: // 1. SIGNAL GENERATION: // - Detects MACD crossovers on selected timeframe (current or HTF) // - HTF mode: Captures 15min (or custom) signals while on 1min chart // - Bullish: MACD crosses above Signal line → BUY // - Bearish: MACD crosses below Signal line → SELL // // 2. ENTRY EXECUTION: // - Current TF Mode: Executes immediately on signal // - HTF Mode + Close: Waits for HTF candle close (more accurate) // - HTF Mode + Immediate: Executes as soon as HTF signal appears // // 3. RISK MANAGEMENT: // - Hard Stop Loss: Fixed percentage or points from entry // - Trailing Stop: Activates after reaching trail points profit // - Trail Offset: Maintains distance from highest/lowest point // - Cooldown: Prevents overtrading after exits // // 4. POSITION MANAGEMENT: // - Long Only / Short Only / Both directions // - Automatic position reversal on opposite signals // - One position at a time (no pyramiding) // // 🎯 RECOMMENDED SETTINGS: // • For Scalping: 1min chart with 15min HTF signals // • For Day Trading: 5min chart with 1H HTF signals // • For Swing Trading: 1H chart with 4H/Daily HTF signals // // 📊 BACKTEST ACCURACY: // • Commission: 0.1% per trade (adjustable) // • Slippage: 3 ticks default (adjustable) // • Execution: On bar close for realistic results // • No repainting: lookahead=false on security calls // // ⚠️ IMPORTANT NOTES: // • HTF signals may appear delayed on lower timeframes // • Always wait for HTF close for most accurate backtesting // • Stop losses may trigger intrabar (not visible in backtest) // • Past performance does not guarantee future results // // 📝 USAGE INSTRUCTIONS: // 1. Add to chart (recommended: 1min or 5min) // 2. Enable "Use Higher Timeframe Signals" // 3. Set Signal Timeframe (15min, 30min, 1H, etc.) // 4. Configure Stop Loss settings // 5. Set appropriate Cooldown period // 6. Review backtest metrics in bottom-right panel // // 🔧 CUSTOMIZATION: // • Adjust MACD parameters (Fast/Slow/Signal) // • Modify Stop Loss percentage or points // • Change trailing stop activation and offset // • Set custom backtest date range // • Fine-tune commission and slippage // // 💡 PRO TIPS: // • Use HTF for trend direction, LTF for entry timing // • Higher commission/slippage = more realistic results // • Longer cooldown periods reduce overtrading // • Trail offset prevents premature exits // // 📧 SUPPORT: // For questions or suggestions, please comment on TradingView
Strategi Pine Script®
oleh bhavneetsinghwalia
Solaris-XAUUSD Strategy Overview • Rather than using decorative or complex visuals the chart is intentionally kept simple and uncluttered to emphasize readability and precision over aesthetics. • Designed for 15 minute intraday charts. These settings are for XAUUSD • Each asset (stocks, indices, commodities, cryptocurrencies, etc..) requires individual calibration. Since market dynamics shift weekly, how can indicator values stay constant, and how can one asset’s settings apply to all assets? • Retracement entry is best. • Restrict trading to the first two signals per day. • Fine tune input values weekly to adjust for changing volatility. • Refer to the above pic for value setting. Strategy Settings • More than 80% of trades should be profitable (calibration goal). • Minimum of 10 trades in the last 30 days (more is better). • Strategy uses 10 input values that must be precisely fine tuned. Important Notes • There is no holy grail—discipline and risk management are essential. • Always forward test thoroughly before live trading. • For questions, feel free to DM me. Current settings for XAUUSD Sun 4.53 Pluto 86 Mars 18 Charon 1 10 Charon 2 0 Rahu 1.15 Laxmi 0.1 Sun Moon A 100 Mercury 25 ISM 0.5 Less important --ATR Period 14, ATR Smoothing EMA , ATR multiplier 1.25 In style untick following for clean chart-- Bar color Trades on chart Signal labels Quantity Disclaimer : This strategy is for educational and research purposes only and should not be considered investment advice. Always conduct your own research and consult your financial advisor before making trading decisions. Past performance does not guarantee future results.
Strategi Pine Script®
oleh Trader-Solaris
1
SBP Multimode Trading System v1.0 (Invite Only)Overview SBP Multimode Trading System is a fully adaptive, professional-grade trading system designed for Scalping, Intraday, and Swing Trading across Index, Commodity, and Crypto markets. This system integrates AI-style consensus logic, dynamic trend filtering, volatility adaptation, and liquidity-aware protection to deliver high-quality, low-noise trading signals. Built for serious traders who value precision, discipline, and consistency. 🚀 Key Features ✅ Multi-Mode Trading Engine Scalping / Intraday / Swing presets Automatic parameter optimization per mode ✅ AI Smart Consensus System Combines Trend + DTF + UW MA + Momentum + Ribbon Generates high-confidence Buy/Sell signals Anti-overtrading alternation lock ✅ Dynamic Trend Filter (DTF) Auto / Stable / Dynamic modes Adapts to volatility and timeframe Non-repainting confirmation ✅ Adaptive UW Moving Average Volatility-based length adjustment Market-specific presets Strong trend validation ✅ PMR Ribbon System Trend direction Choppy market detection Reversal & trap signals ✅ Momentum & Impulse Engine Strength-based entries Cooldown protection Noise filtering ✅ SM-Lite Liquidity Filters Stop-hunt detection Equal high/low blocking Wick spike protection ✅ Automatic Market Detection Index / Commodity / Crypto Instrument-aware presets ✅ Auto Timeframe Optimization ATR, DTF, Momentum auto scaling Optimized for 1m to 30m charts ✅ Fibonacci Golden Zone Auto swing detection 23%–38% retracement zones Trend-based projection ✅ Professional Risk Engine (Backtest Mode) ATR-based SL / TP Trailing stops Daily trade limits ✅ Strategy + Indicator Hybrid Indicator Mode (Manual Trading) Strategy Mode (Backtesting) 📊 Signal Types 🔹 AI Buy / Sell – High-confidence consensus signals 🔹 Scalping Arrows & Dots – Fast momentum entries 🔹 Ribbon Trap Signals – False breakout reversals 🔹 Swing / Intraday Signals – Trend-based setups 🔹 Exit Labels – Clear position management All signals are non-repainting (bar-confirmed). ⚙️ Recommended Usage Trading Style Timeframe Mode Scalping 1m – 5m SCALPING Intraday 5m – 15m INTRADAY Swing 15m – Daily SWING ✔ Works best on: NIFTY / BANKNIFTY / FINNIFTY Gold / Crude / Silver BTC / ETH / Major Alts 📈 How to Trade (Basic Rules) 🟢 Buy Setup AI Buy / Scalp Buy / Trend Buy appears Price above DTF & UW MA Ribbon turns bullish Enter on candle close 🔴 Sell Setup AI Sell / Scalp Sell / Trend Sell appears Price below DTF & UW MA Ribbon turns bearish Enter on candle close 🎯 Exit Use Exit Labels Or ATR-based targets Or trail with market structure ⚠️ Always follow your own risk management. 🔒 Access Policy This is a Private / Invite-Only proprietary system. ✔ No redistribution ✔ No resale ✔ No sharing ✔ License bound to account Unauthorized usage may lead to permanent revocation. 📞 Support & Updates Subscribers receive: ✔ Regular updates ✔ Performance improvements ✔ Bug fixes ✔ Feature enhancements For access and support, contact the author. ⚠️ Disclaimer This tool is for educational and analytical purposes only. Not financial advice No guaranteed returns Trading involves substantial risk Past performance does not guarantee future results Use at your own responsibility.
Strategi Pine Script®
oleh sbprasad2005
The Best trend following strategy suited for upward BTC markets!🚀 BTC Trend Beast – Simple, High-Conviction, Low-Frequency Trend Strategy Designed for volatile assets like Bitcoin ; catches big trends while keeping your mind at peace. 🧠 We favor long-only trades (very few shorts) to avoid unnecessary stress and whipsaws. Real Backtest Highlights (Jan 2022 – Feb 2026 on BTC, extended to 10+ years historical): Winner Mode ("Trend Confirm"): Sharpe Ratio: 0.95 Total Return: +213% (vs. Buy & Hold +44.5%) Annualized Return: +31.9% Max Drawdown: -30.5% (manageable in crypto volatility) Win Rate: 67% Total Trades: Just 12 (~3 per year!) Profit Factor: 1.23 Why this crushes in trending/volatile markets: Extremely low trade frequency → fewer decisions, less emotional trading Event-based signals (no repainting or daily noise/flicker) Zero warmup issues — pure SMA logic Built for BTC but shines on any strong-trending volatile asset (ETH, SOL, major forex pairs in trends, etc.) Three Built-in Modes (switch easily in settings): Trend Confirm → The proven winner above (our flagship) Low Drawdown → SMA(20/200) Golden Cross + Donchian Channel exit → Only -13.6% max DD! (Ultra-defensive) Breakout → Classic Donchian(55/10) Turtle-style → Great for explosive moves All modes use clean, event-driven entries/exits — no over-optimization fluff. Perfect if you're: Tired of over-trading Want real edge in BTC bull runs Prefer set-it-and-forget-it style with infrequent high-quality signals 📊 Test it yourself on BTC daily/weekly charts — backtest further if you like! DISCLAIMER: This is for educational and research purposes only. Not financial advice. Past performance ≠ future results. Crypto is highly volatile — trade at your own risk, use proper position sizing, and never risk more than you can afford to lose.
Strategi Pine Script®
oleh Gyaani
LBR Medallion Jim Simmons Mean Reversion Regime FilteredLinda Bradford Raschke's Mean Reversion Strategy Inspired by Quantitative Approaches This is a short-term mean reversion strategy that attempts to capture small inefficiencies when price deviates from a dynamic mean (EMA), confirmed by volatility bands (ATR-based), RSI extremes, and an ADX filter to avoid strong trends. Core Logic: - Entry Long: Price below lower band (EMA - mult * ATR), RSI oversold, ADX below threshold (ranging market) - Entry Short: Price above upper band, RSI overbought, ADX low - Optional filters: - Regime: Aligns with higher-timeframe trend (price >/< Daily EMA200) - Volume: Requires above-average volume for confirmation - Exits: Either fixed ATR-based TP/SL or reversion to EMA Designed primarily for ranging or mildly trending markets on liquid assets (e.g., XAUUSD 4H tested). It performs best in non-trending conditions; strong trends can lead to drawdowns. Features: - Market-neutral long/short capability - Volatility-adjusted bands for adaptive deviation - Toggleable regime and volume filters - Visual plots for EMA, bands, and daily regime line Usage Recommendations: - Timeframe: 1H to 4H (tested on 4H XAUUSD) - Assets: High-liquidity instruments (forex pairs, indices, commodities) - Risk: Use proper position sizing (1-2% risk per trade recommended). Backtest on your symbol/timeframe. - This is not financial advice. Past performance does not guarantee future results. Trading involves substantial risk of loss. No external dependencies or repainting issues. Educational/experimental script. Feedback welcome — happy to discuss improvements!
Strategi Pine Script®
oleh uzair2join
SquadAlgo-FoxtrotSquadAlgo-Foxtrot 🤖 runs directly inside TradingView, so you skip extra accounts and avoid platform switching. Open your chart, apply the algorithm, and move straight into execution. Built on an AI backed strategy and validated through deep historical testing 📊, Foxtrot focuses on disciplined trades instead of emotional decisions. Each rule follows measurable data so you operate with clarity. The setup stays simple ⚡. Load the script, connect your market, and start analyzing within minutes. The layout feels familiar because you remain inside TradingView, one of the most trusted charting platforms among active traders. Customization drives performance 🛠️. Adjust inputs, test variants, and review results before placing capital at risk. This workflow supports tighter risk control and stronger consistency. SquadAlgo-Foxtrot fits traders who value precision, speed, and full control without juggling multiple systems 🚀.
Strategi Pine Script®
oleh SquadrantRyan
ORB StrategyOpening Range Break Strategy. It works, sometimes. Stop loss to break even is not currently working, dont rely on that. To be honest in backtesting, it hurt more than it helped. The ORB strategy has been around for a long time; it has ebbs and flows on when it is working. You'll know that it's currently working because your Youtube feed will be full of videos for it. Native Quantlynk and Ghost integration using {{strategy.order.alert_message}} NOT FINANCIAL ADVICE. NO GUARANTEES OF ANY KIND.
Strategi Pine Script®
oleh greatestNothing