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VANTYX- Scalper Bot-Dr Abiram SivprasadVANTYX Scalper Bot is a high-precision algorithmic strategy designed for Crypto Perpetuals, Forex, and Indices. It combines robust trend-following logic with a multi-timeframe momentum filter to catch explosive moves while avoiding choppy "sideways" markets.Unlike many scalping scripts, this strategy is strictly engineered to be Non-Repainting. It uses a custom "Tuple Fix" to ensure that all Multi-Timeframe (MTF) data is pulled from Closed Candles only, guaranteeing that your backtest results match real-time performance.🧠 Core Strategy LogicThe strategy operates on a "Confluence" model, requiring four distinct conditions to align before entering a trade:Trend Direction (HalfTrend):We use the HalfTrend indicator to determine the immediate market bias.Long: Price is above the HalfTrend line (Blue).Short: Price is below the HalfTrend line (Red).Momentum Filter (MTF ADX & DI):A custom Multi-Timeframe ADX engine checks the strength of the trend on a higher timeframe (e.g., 15m or 1H).Rule: The ADX must be above a specific threshold (default 23) to confirm that the market is "Trending" and not "Sleeping."Direction: DI+ must be > DI- for Longs, and DI- > DI+ for Shorts.Macro Trend Filter (MTF EMA):To prevent trading against the major trend, the strategy checks a Higher Timeframe 200 EMA.Longs are only taken if Price > 200 EMA.Shorts are only taken if Price < 200 EMA.Volume Filter:Entries are only valid if the current Volume is above the average Volume (SMA 20), ensuring institutional participation.🛡️ Risk Management (The Engine)This strategy includes a professional-grade risk engine to protect capital:ATR-Based Stop Loss: Dynamic SL set at 1.5x ATR (Adjustable). This adapts to market volatility—wider stops in volatile markets, tighter stops in calm markets.ATR-Based Take Profit: Set at 3.0x ATR (Adjustable) to aim for a high Risk:Reward ratio (1:2 or 1:3).Ratchet Trailing Stop: An intelligent trailing stop that moves only in your favor. Once the price moves significantly, the stop tightens to lock in profits, ensuring winning trades don't turn into losers.⚙️ How to Use (Best Settings)Asset Class: Best for Crypto Perpetuals (BTC, SOL, ETH, XRP, MEME Coins) and Volatile Indices.Timeframe: Optimized for 5-Minute and 15-Minute charts.MTF Settings:If Trading 5m Chart $\rightarrow$ Set ADX to 15m and EMA to 1H.If Trading 15m Chart $\rightarrow$ Set ADX to 1H and EMA to 4H.Note: Always ensure ADX/EMA timeframes are higher than your chart timeframe.🛠️ Technical Note: The "Tuple Fix"Many TradingView strategies repaint because request.security leaks future data when using tuples. This script uses a custom function wrapper (f_adx_shifted) to explicitly request (previous closed bar) data for the ADX tuple calculation. This ensures 100% Backtest Accuracy. ⚠️ DisclaimerThis script is for educational and quantitative analysis purposes only. Past performance does not guarantee future results. Cryptocurrency trading involves high risk and leverage. Always forward-test on paper before deploying real capital.
Estratégia Pine Script®
por abiramsivprasad
LBR Chaos Theory Butterfly Effect Regime Structure Momentum Linda Bradford Raschke's Chaos Theory Regime Momentum Strategy: This strategy identifies regime shifts in market structure using a momentum spread model derived from exponential moving averages and volatility normalization. Core Concept: Markets alternate between expansion and contraction phases. When short-term momentum (Fast EMA) separates decisively from medium-term structure (Slow EMA) and aligns with a higher timeframe trend filter (200 EMA), it signals a potential transition into a directional expansion regime. The strategy trades only when: • Fast EMA crosses Slow EMA (momentum shift) • Price aligns with major trend (200 EMA filter) • ATR volatility exceeds a minimum regime threshold This avoids ranging conditions and reduces low-probability trades. Risk Model: The system uses volatility-adjusted stops based on ATR. Default properties: • Initial Capital: 10,000 • Risk per trade: 2% of equity • Risk-to-Reward: 1:2 • Commission: 0.05% • Slippage: 1 tick • No pyramiding Position size is calculated dynamically using: Position Size = (2% Equity) / Stop Distance This ensures consistent capital preservation and sustainable drawdowns. How to Use: • Designed for trending markets (Forex, Gold, Indices, Crypto) • Use multi-year datasets for proper statistical sample size • Avoid very low liquidity markets This strategy does not predict future prices. It reacts to structural momentum expansion supported by volatility confirmation. Past performance does not guarantee future results.
Estratégia Pine Script®
por uzair2join
SCI EMA-RSI Edge🚀 SCI EMA-RSI Edge Advanced Trend & Momentum Strategy by Speed Coding Infotech SCI EMA-RSI Edge ek highly customizable trend-following strategy hai jo EMA (trend detection) aur RSI (momentum confirmation) ka smart combination use karti hai high-probability trade setups generate karne ke liye. Ye strategy flexible design ki gayi hai taaki trader apne market, timeframe aur risk profile ke hisaab se parameters optimize kar sake. ⸻ 🔥 How It Works ✅ EMA – Trend Filter EMA overall market direction identify karta hai aur false entries ko reduce karta hai. Trend alignment hone par hi trade consider hota hai. ✅ RSI – Momentum & Exit Engine RSI entry confirmation aur exit timing ke liye use hota hai. Overbought / Oversold zones profit booking aur reversal protection me help karte hain. ⸻ ⚙️ Important Note About Parameters 📌 Strategy ke jo default inputs diye gaye hain wo sirf demonstration purpose ke liye hain. Real performance completely depend karta hai: • Market type (Equity / Options / Forex / Crypto) • Timeframe (5min / 15min / 1H / Daily) • Volatility condition • User optimization Users recommended hain ki: ✔️ RSI length adjust kare ✔️ Exit levels optimize kare ✔️ EMA period backtest kare ✔️ Candle range & filters tweak kare Proper backtesting & optimization ke baad strategy significantly better results de sakti hai. ⸻ 🎯 Customizable Inputs • Exit RSI Length (Adjustable for faster/slower exits) • Long Exit RSI Level • Short Exit RSI Level • Trade Direction Control (Long Only / Short Only) • Day Filter • Candle Range • Buffer • Quantity • Webhook Automation Support ⸻ 💡 Best Practice for Better Results ✔️ Trending market me use kare ✔️ Sideways market me filters tight kare ✔️ Higher timeframe trend confirm kare ✔️ Risk management apply kare ⸻ ⚠️ Disclaimer Performance depends on market conditions & parameter optimization. Always backtest before live trading.
Estratégia Pine Script®
por Speed_Coding_infotech
Swing Strategy Feature Set U [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 U includes concepts beginning with the letter "U" 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: Ulcer Index Ultimate Oscillator █   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 U 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 Ulcer Index (UI) Filters The UI indicator defaults are as follows: Source is set to "Close". Length is set to 14. Users can adjust the UI inputs via strategy Settings/Inputs/ULCER INDEX (UI). The UI 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 UI 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 UI filters and adjust filter parameters via strategy Settings/Inputs/UI FILTERS. Ultimate Oscillator (UO) Filters The UO indicator defaults are as follows: Fast length is set to 7. Medium length is set to 14. Slow length is set to 28. Users can adjust the Ultimate Oscillator inputs via strategy Settings/Inputs/ULTIMATE OSCILLATOR (UO). The UO minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply UO above-equal is set to false. UO above-equal threshold is set to 0. Apply UO below-equal is set to false. UO below-equal threshold is set to 100. The UO 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 UO 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 UO filters and adjust filter parameters via strategy Settings/Inputs/UO 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.
Estratégia Pine Script®
por theEccentricTrader
Swing Strategy Feature Set T [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 T includes concepts beginning with the letter "T" 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: Tilson Moving Average Trend Trendline Triple Exponential Moving Average (TRIX) True Strength Index █   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. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred indicator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. 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. Moving Average (MA) Double and Triple Trend Filters MA double and triple trend filters are defined as entry filters that evaluate the relative positioning of two or more MA values and invalidate trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when one MA is greater than or equal to another MA. "Below" returns true when one MA is less than another MA. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. 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 T 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 TMA (T3) and TRIX 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 Tilson Moving Average (TMA) Filters As there is no built-in indicator for the TMA (T3) value used in this script, users can build their own TMA (T3) indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Tilson Moving Average (T3)", shorttitle = "TMA (T3)", overlay = true) import TradingView/ta/12 as ta tma_1_source = input.source(title = 'TMA 1 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_1_length = input.int(title = 'TMA 1 Length', defval = 50, minval = 1, group = 'Tilson Moving Average (TMA)') vf_1 = input.float(title = 'TMA 1 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_1_colour = input.color(title = 'TMA 1 Colour', defval = color.green, group = 'Tilson Moving Average (TMA)') tma_2_source = input.source(title = 'TMA 2 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_2_length = input.int(title = 'TMA 2 Length', defval = 100, minval = 1, group = 'Tilson Moving Average (TMA)') vf_2 = input.float(title = 'TMA 2 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_2_colour = input.color(title = 'TMA 2 Colour', defval = color.orange, group = 'Tilson Moving Average (TMA)') tma_3_source = input.source(title = 'TMA 3 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_3_length = input.int(title = 'TMA 3 Length', defval = 200, minval = 1, group = 'Tilson Moving Average (TMA)') vf_3 = input.float(title = 'TMA 3 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_3_colour = input.color(title = 'TMA 3 Colour', defval = color.red, group = 'Tilson Moving Average (TMA)') tma_1 = ta.t3(tma_1_source, tma_1_length, vf_1) tma_2 = ta.t3(tma_2_source, tma_2_length, vf_2) tma_3 = ta.t3(tma_3_source, tma_3_length, vf_3) plot(tma_1, color = tma_1_colour) plot(tma_2, color = tma_2_colour) plot(tma_3, color = tma_3_colour) Users can define up to three independent TMA (T3) series. The defaults are as follows: TMA 1: source = close, length = 50, volume factor = 0.7. TMA 2: source = close, length = 100, volume factor = 0.7. TMA 3: source = close, length = 200, volume factor = 0.7. Users can adjust the TMA inputs via strategy Settings/Inputs/TILSON MOVING AVERAGE (TMA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined TMA (T3). The default mode for all three TMA close above-equal/below filters is set to "None". Users can apply up to three independent TMA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: TMA 1 above-equal/below TMA 2 is set to "None". TMA 2 above-equal/below TMA 3 is set to "None". TMA 1 above-equal/below TMA 3 is set to "None". The TMA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined TMA is rejected exclusive of the other two TMAs. The default mode for the TMA rejection filter is set to "None". Users can apply the TMA filters and adjust filter parameters via strategy Settings/Inputs/TMA FILTERS. Trend Filters The trend filters in this section extend the generic basic and multi-part trend filters by applying the same logical framework to structurally defined peak and trough prices rather than to a continuous time-series. By operating on completed swing structures, these filters introduce an additional structural layer that differentiates between directional continuation and return line behaviour. This structural distinction necessitates the inclusion of return line variations alongside standard uptrend and downtrend conditions. Within this framework, peak-to-peak sequences define upper trend filters and trough-to-trough sequences define lower trend filters. A peak-to-peak upward structural progression is classified as a return line uptrend, while a peak-to-peak downward progression is classified as a downtrend. Conversely, a trough-to-trough upward structural progression is classified as an uptrend, while a trough-to-trough downward progression is classified as a return line downtrend. Upper trends include: Return line uptrends. Downtrends. Lower trends include: Uptrends. Return line downtrends. Below are links to my multi-part trend indicators, which can be used as visual aids for the relevant filter conditions included in this script: The upper and lower trend filter's defaults are as follows: Upper Trend mode is set to "None". Upper Trend count is set to 3. Lower Trend mode is set to "None". Lower Trend count is set to 3. When basic trend modes are selected, the trend count inputs are redundant and have no effect. Users can apply the trend filters via strategy Settings/Inputs/TREND FILTERS. Trendline Filters The trendline value calculations used in this script are based on those included in my trendlines indicator (link below for visual reference). Note that previous trendline values are not factored into the filter logic used in this script, only the most recent peak-to-peak (resistance) and trough-to-trough (support) lines are evaluated. The trendline rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined trendline value is rejected exclusive of the other trendline value. Four rejection modes are available: Support. Resistance. Support-turned-resistance. Resistance-turned-support. These operate asymmetrically depending on trade direction. For long entry conditions, the filter will only evaluate support and resistance-turned-support, both of which require a bullish rejection (i.e. price rejecting upward from the relevant trendline). For short entry conditions, the filter will only evaluate resistance and support-turned-resistance, both of which require a bearish rejection (i.e. price rejecting downward from the relevant trendline). The default trendline rejection filter mode is set to "None". Users can apply the trendline filter via strategy Settings/Inputs/TRENDLINE FILTERS. Triple Exponential Moving Average (TRIX) Filters As there is no built-in indicator for the TRIX values used in this script, users can build their own TRIX indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Triple Exponential Moving Average (TRIX)", shorttitle = "TRIX", overlay = false) import TradingView/ta/12 as ta trix_source = input.source(title = 'TRIX Source', defval = close, group = 'Triple Exponential Moving Average (TRIX)') trix_length = input.int(title = 'TRIX Length', defval = 14, minval = 1, group = 'Triple Exponential Moving Average (TRIX)') trix_signal_length = input.int(title = 'TRIX Signal Length', defval = 9, minval = 1, group = 'Triple Exponential Moving Average (TRIX)') trix_exponential = input.bool(title = 'TRIX Exponential', defval = true, group = 'Triple Exponential Moving Average (TRIX)') trix_colour = input.color(title = 'TRIX Colour', defval = color.yellow, group = 'Triple Exponential Moving Average (TRIX)') trix_sig_colour = input.color(title = 'TRIX Signal Colour', defval = color.blue, group = 'Triple Exponential Moving Average (TRIX)') trix_hist_pos_colour = input.color(title = 'TRIX Histogram Positive Colour', defval = color.rgb(76, 175, 79, 80) , group = 'Triple Exponential Moving Average (TRIX)') trix_neg_colour = input.color(title = 'TRIX Histogram Negative Colour', defval = color.rgb(255, 82, 82, 80), group = 'Triple Exponential Moving Average (TRIX)') = ta.trix(trix_source, trix_length, trix_signal_length, trix_exponential) plot(trix, color = trix_colour) plot(trix_signal, color = trix_sig_colour) plot(trix_hist, color = trix_hist >= 0 ? trix_hist_pos_colour : trix_neg_colour, style = plot.style_columns) The TRIX defaults are as follows: Source is set to "Close". Length is set to 14. Signal length is set to 9. Exponential mode is set to true. Users can adjust the TRIX inputs via strategy Settings/Inputs/TRIPLE EXPONENTIAL MOVING AVERAGE (TRIX). The TRIX above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the TRIX value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the TRIX above-equal/below signal filter is set to "None". The default mode for the TRIX Histogram above-equal/below zero filter (see generic filters section above) is set to "None". The TRIX Histogram 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 TRIX Histogram 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 TRIX filters and adjust filter parameters via strategy Settings/Inputs/TRIX FILTERS. True Strength Index (TSI) Filters The TSI defaults are as follows: Long length is set to 25. Short length is set to 13. Signal length is set to 13. Users can adjust the TSI inputs via strategy Settings/Inputs/TRUE STRENGTH INDEX (TSI). The TSI above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the TSI value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the TSI above-equal/below signal filter is set to "None". The default mode for the TSI above-equal/below zero filter (see generic filters section above) is set to "None". The default mode for the TSI Signal above-equal/below zero filter (see generic filters section above) is set to "None". The TSI 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 TSI Signal 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 TSI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The TSI Signal 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 TSI filters and adjust filter parameters via strategy Settings/Inputs/TSI 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.
Estratégia Pine Script®
por theEccentricTrader
X_FINAL_SECURE리페인팅 없고, 과최적화 되지 않았으며, 거래소와 거래 내역도 완벽히 일치합니다. 훌륭한 추세 전략입니다. 추후 유료 전환 예정 되어 있습니다. 누구도 전략을 흉내낼 수 없도록, 코드 보안상 어떤 조건으로 실행되는지도 보호 처리했습니다. 위에 보이는 백테스트는 3배 레버리지 + 100% 진입 시드 + 자가 복리 기준입니다. 셋팅 설명: 1-1 ~ 1-3: 백테스트 기간 설정 또는 자동매매 기간 설정입니다. 전략 시작할때는 1-1을 당일날짜 00:00 으로 맞추고 하셔야 합니다. 1-4: 백테스트에서 적용하는 진입 시드 비중입니다. (실제 진입 시드 비중은 속성에서 설정하세요.) 1-5: 백테스트 기록 보기용 배율 설정입니다. (실제 배율은 본인 거래소에서 설정하세요.) 1-6은 신경 쓰지 않으셔도 됩니다. 나머지 인풋값 설정은 아래 보고 설정하세요 "Use these input settings:" 2-1 =21 ㅡㅡ 2-2 =20 2-3 =1.8 ㅡㅡ 2-4 =1.5 2-5 =29 ㅡㅡ 2-6 =15 2-7 =1.4 ㅡㅡ 2-8=1.2 3-1= v check ㅡㅡ 3-2 = v check 3-3 =5 ㅡㅡ 3-4 =11 3-5 =60 ㅡㅡ 3-6 =30 3-7 =0.28 ㅡㅡ 3-8 =0.68 4-1 = no check 4-4 = v check ㅡㅡ 4-5 =13 ㅡㅡ 4-6 =2.7 5-1 =no check ㅡㅡ 5-2 =check 5-3 =check ㅡㅡ 5-4 =check 5-5 =check ㅡㅡ 5-6 =no check 5-7 =check ㅡㅡ 5-8 =check 6-1 = C ㅡㅡ 6-2 = C 6-3 = 2 ㅡㅡ 6-4 = 2 6-5 = 3.9 ㅡㅡ 6-6 =3.9 6-7 = 2 ㅡㅡ 6-8 =2.1 6-9 = 2 ㅡㅡ 6-0 = 2 t1 = v t2 = v Settings & Usage Guide (English) No repainting, no over-optimization, and trade history matches the exchange perfectly. A high-quality trend strategy. This will transition to paid access in the future. Code is fully secured – execution conditions are protected to prevent any copying or imitation. The backtest shown is based on 3x leverage + 100% entry seed + full compounding. Settings Explanation: 1-1 ~ 1-3: Backtest period and auto-trading period settings. 1-4: Entry seed percentage used in backtest. (Set real entry size in strategy properties.) 1-5: Leverage multiplier for viewing backtest records. (Set actual leverage on your exchange.) 1-6: Ignore – no need to adjust. For the remaining input values, refer to the right side (Author Instructions) and set the numbers accordingly.
Estratégia Pine Script®
por jin147600
RSI & MACD + D/S ZonesOverview This strategy is a hybrid trading system that combines Institutional Supply & Demand concepts with a strict Momentum Validation Engine. Supply & Demand indicators trigger signals the moment price touches a zone, often leading to "catching a falling knife." This script solves that problem by decoupling the "Zone Hit" from the "Trade Entry." It identifies key market structures first but only triggers a trade when momentum (MACD + RSI) explicitly confirms a reversal in the direction of the dominant trend. How It Works 1. The Map: Supply & Demand Zones The script automatically identifies zones based on the "Boring Candle + Explosive Move" pattern. Creation: A zone is formed when a low-volatility "Boring Candle" (base) is followed by a high-volatility "Explosive Candle" (breakout). Consumption: Zones are dynamic. If price wicks into a zone, the zone "shrinks" to reflect consumed orders. If price breaks through completely, the zone is removed. Visuals: Demand Zones: Faint Green (20% Opacity). Supply Zones: Faint Red (20% Opacity). "HIT" Labels: clearly identify when price tests a zone (Green for Demand, Orange for Supply). 2. The Filter: Trend & Safety 200 EMA (Red Line): Acts as the hard trend filter. Longs are only taken above the Red Line. Shorts are only taken below the Red Line. RSI "Safe Zone" (35–65): The script filters out trades where RSI is overbought (>65) or oversold (<35), ensuring entries have room to run. 3. The Trigger: 2-Bar Momentum Confirmation A trade is NOT taken just because a zone is hit. The script waits for a confirmed momentum shift: MACD Logic: It requires two consecutive bars of expanding histogram momentum (e.g., for a Long, the histogram must be Green and rising for 2 bars). Signal Decoupling: The "Buy" or "Sell" signal may appear 1-3 bars after the zone hit, ensuring the bounce is real. --- Visual Guide * 🔵 Buy Label (Sky Blue): A confirmed Long entry (Trend Up + RSI Safe + Momentum Rising). * 🟣 Sell Label (Hot Pink): A confirmed Short entry (Trend Down + RSI Safe + momentum falling). * 🔴 Red Line: The 200 EMA Trend Filter. * 🟢 Green "Hit Demand": Price has touched a valid Demand Zone. * 🟠 Orange "Hit Supply": Price has touched a valid Supply Zone. Settings & Inputs Zone Settings: Adjust `Boring Candle %` to filter which bases are detected. Strategy Settings: `EMA Trend Filter`: Defaults to 200. `RSI Min/Max`: Defaults to 35/65 to avoid extremes. Risk Disclaimer This script is a technical analysis tool. Past performance does not guarantee future results. Always use proper risk management and stop losses when trading real capital.
Estratégia Pine Script®
por abishek_philip24
Crypto Algo Chakra by Pooja🔥 Crypto Algo Chakra by Pooja — Advanced Trading System Crypto Algo Chakra is not just a traditional indicator or basic strategy — it is a complete rule-based trading system designed to assist traders with structured decision making. This system integrates entry logic, risk management, dynamic stop loss, trailing logic, and target calculation into a single unified framework. The goal is to provide a systematic trading environment that can support discretionary traders as well as automation workflows. The system focuses on structure confirmation, trend filtering, and adaptive risk control rather than simple signal generation. ⚙️ Core Concept The trading system is built around a multi-layered filtering model where signals are validated through trend alignment and confirmation filters. Instead of relying on a single indicator, Crypto Algo Chakra combines multiple conditions to reduce false signals and improve structural clarity. All major components are optional and fully controlled by user inputs. 📈 Entry Engine 🔹 3 EMA Structure Protection Fast EMA Slow EMA Trend EMA (200 EMA optional filter) Entry signals are generated based on EMA crossover logic with optional trend structure confirmation to avoid counter-trend entries. 🔹 Fake Breakout Filters (Optional) To reduce low-quality signals, the system includes: ADX strength filter RSI momentum filter Supertrend directional confirmation These filters help identify potential trend continuation environments. 🛑 Stop Loss System Flexible risk control options: Swing-based Stop Loss (structure aware) Candle-based Stop Loss (dynamic recent price levels) Minimum risk distance protection is included to avoid unrealistic trade sizing. 🔁 Advanced Trailing Stop Loss Engine Multiple trailing methodologies available: Candle Wise trailing Swing Wise trailing Structure Break trailing Pivot Wise trailing Trailing activates only after defined structural conditions to prevent premature exits. 🎯 Target System Two independent target calculation methods: Risk : Reward based targets Pivot-based targets (multi-level extension supported) Users can choose between close-based or wick-based target triggering. 🔄 Trend Reversal Protection The system includes automatic trend flip handling: Exit current trade when opposite structure appears Optional delayed re-entry logic Entry protection maintained after reversal 📍 Support & Resistance Integration Traditional Pivot Points are included for: Dynamic support and resistance reference Target and trailing calculations Structural context ⏰ Force Exit Protection Optional session-based exit system designed for intraday traders to avoid holding positions beyond specified time. 🔔 Algo Ready Alert System Built-in alerts designed for automation workflows: Entry alerts Stop loss exits Trailing stop exits Target hits Trend reversal exits Force exit events Alerts are structured to support external automation platforms. 🧩 Built-in Indicators 3 EMA System Supertrend Pivot Support & Resistance All modules are optional and fully customizable. ⭐ Why This System is Unique Unlike traditional signal indicators, Crypto Algo Chakra focuses on complete trade lifecycle management. Key design principles include: Multi-layer confirmation instead of single-condition signals Modular risk management and trailing systems Structural trend validation Adaptive pivot integration Automation-friendly architecture The system is intended to provide a structured framework rather than predictive guarantees. 🔒 Why Invite-Only Access This trading system is published as invite-only to maintain controlled distribution, ensure proper usage understanding, and allow structured user onboarding. The system contains multiple configurable modules such as entry filters, risk management logic, trailing stop mechanisms, and algorithm-ready alert conditions. Controlled access helps prevent misuse, confusion from incorrect settings, and maintains system stability for users who understand its framework. Invite-only access does NOT imply guaranteed results or exclusive trading advantages. The purpose is structured distribution and support. ⚠️ Disclaimer This tool is designed for educational and informational purposes only. It does not provide financial advice or guarantee performance or profitability. Market conditions vary, and users should conduct independent analysis and risk management before making trading decisions. Past performance does not indicate future results.
Estratégia Pine Script®
por financegurupooja
Intraday Momentum Signals This is an advanced divergence detection strategy designed to identify potential market reversals by analyzing the relationship between price action and momentum oscillator patterns. The strategy automatically detects divergence signals and executes trades based on configurable parameters. ⚠️ CRITICAL DISCLAIMER READ THIS CAREFULLY BEFORE USING THIS STRATEGY: This is NOT Financial Advice ❌ This is NOT a buy signal generator ❌ This is NOT a sell signal recommendation ❌ This is NOT investment advice ❌ This is NOT a guaranteed profit system ❌ This is NOT a substitute for professional financial guidance Educational Purpose Only ✅ This tool is for educational and research purposes ONLY ✅ Provided for technical analysis learning ✅ Intended for strategy backtesting and study ✅ Use at your own risk and responsibility Your Responsibility 🔍 DO YOUR OWN RESEARCH before making any trading decisions 🔍 VALIDATE all signals independently 🔍 BACKTEST thoroughly on historical data 🔍 PAPER TRADE before risking real capital 🔍 CONSULT a licensed financial advisor or SEBI-registered professional 🔍 UNDERSTAND the risks involved in trading Risk Warning ⚠️ Trading involves substantial risk of loss ⚠️ You can lose your entire capital ⚠️ Past performance does NOT guarantee future results ⚠️ No strategy works 100% of the time ⚠️ Market conditions constantly change ⚠️ Never risk money you cannot afford to lose Legal Notice By using this strategy, you acknowledge that: You are solely responsible for your trading decisions The creator assumes no liability for your losses You will not hold anyone responsible for outcomes You understand this is not personalized advice You agree to trade at your own discretion and risk 🎯 Best Use Cases This strategy is primarily designed for intraday trading and works optimally on shorter timeframes: Recommended Timeframes ✅ 3-minute charts - Ultra-short scalping (High risk, requires constant monitoring) ✅ 5-minute charts - MOST RECOMMENDED for intraday ✅ 15-minute charts - Balanced intraday approach ✅ 30-minute charts - Swing intraday positions ⚠️ 1-hour charts - Fewer signals but potentially higher quality NOT Recommended For ❌ Daily or weekly timeframes ❌ Long-term investing ❌ Position trading ❌ Swing trading (multi-day holds) Why Intraday? The divergence detection logic is specifically optimized for intraday price movements and momentum oscillations that occur within a single trading session. 🔧 Core Features 1. Divergence Detection Engine The strategy identifies four types of divergence patterns: Regular Bullish (UP) - Price makes lower lows while oscillator makes higher lows (potential reversal up) Hidden Bullish (L+) - Price makes higher lows while oscillator makes lower lows (trend continuation) Regular Bearish (DN) - Price makes higher highs while oscillator makes lower highs (potential reversal down) Hidden Bearish (S+) - Price makes lower highs while oscillator makes higher highs (trend continuation) 2. Configurable Parameters Oscillator Settings: Period Length (default: 9) - Controls sensitivity Source (default: close price) - Can use OHLC Lookback Right/Left - Pivot detection sensitivity Lookback Range (5-60) - Time window for divergence comparison Exit Strategy: Take Profit Level (default: 80) - Oscillator level for profit booking Stop Loss Options: ATR-based, Percentage-based, or None Trailing Stop Loss - Dynamic risk management Visual Controls: Toggle each divergence type on/off Customizable dashboard position (4 corners) Clear visual signals on oscillator panel 3. Risk Management System The strategy includes three stop-loss mechanisms: A) ATR Trailing Stop (Recommended for volatile markets) Dynamically adjusts based on market volatility Uses Average True Range multiplier Trails as position moves in profit B) Percentage Stop (Fixed risk) Set percentage from entry price Simple and predictable Good for consistent position sizing C) Manual Exit (Signal-based only) Exits on oscillator threshold Exits on counter-divergence signal No automatic stop loss 4. Performance Dashboard Real-time comprehensive statistics: MetricDescriptionTotal TradesNumber of completed tradesWin RatePercentage of profitable tradesWinning TradesCount of profitable positionsLosing TradesCount of loss-making positionsNet ProfitTotal profit/loss in currencyProfit FactorGross profit ÷ Gross lossAvg WinAverage winning trade amountAvg LossAverage losing trade amountLargest WinBest single trade profitLargest LossWorst single trade loss Color Coding: 🟢 Green - Positive/Good metrics (Win rate >60%, PF >2) 🟠 Orange - Neutral metrics (Win rate 50-60%, PF 1-2) 🔴 Red - Negative/Poor metrics (Win rate <50%, PF <1) 📈 How The Strategy Works Signal Generation Process Continuous Monitoring Strategy scans every bar for pivot points Compares current pivot with historical pivots Checks for divergence between price and oscillator Entry Trigger Valid divergence pattern detected Lookback range conditions met Automatic long position opened Entry price and stops calculated Position Management Selected stop-loss mechanism activated Trailing stop updates on each bar (if enabled) Take-profit level monitored Exit Execution Oscillator crosses take-profit threshold, OR Opposite divergence signal appears, OR Stop-loss triggered Performance Logging Trade recorded in statistics Dashboard updated in real-time Profit/loss calculated and displayed ⚙️ Recommended Settings for Intraday 🕐 For 3-Minute Charts (Scalping) Period: 9-12 Lookback Range: 5-40 bars Take Profit Level: 80-85 Stop Loss: 2-3% OR ATR (14, 2.5x) Use Case: Rapid entries/exits, high frequency, requires constant attention 🕔 For 5-Minute Charts (MOST POPULAR) Period: 9-14 Lookback Range: 5-60 bars Take Profit Level: 75-80 Stop Loss: 3-5% OR ATR (14, 3.5x) Use Case: Balanced risk/reward, good signal frequency, manageable monitoring 🕒 For 15-Minute Charts (Swing Intraday) Period: 9-14 Lookback Range: 5-60 bars Take Profit Level: 70-80 Stop Loss: 4-6% OR ATR (14, 3.5x) Use Case: Fewer but higher quality signals, less screen time 🕧 For 30-Minute Charts Period: 12-14 Lookback Range: 5-60 bars Take Profit Level: 70-75 Stop Loss: 5-7% OR ATR (14, 4.0x) Use Case: Extended intraday positions, better for part-time traders 📝 Important Usage Notes Strategy Configuration ✅ Works in both indicator and strategy modes ✅ Pyramiding: Up to 2 concurrent positions allowed ✅ Default capital: ₹100,000 (customizable) ✅ Fixed quantity: 2 units per trade (customizable) ✅ Currency: INR (can be changed) Visual Signals Visual divergence signals plotted on oscillator panel (not price chart) Entry/exit labels show profit/loss for each closed trade Lines and shapes clearly mark divergence points Dashboard provides at-a-glance performance overview Limitations ⚠️ Divergences are lagging by nature (require confirmed pivots) ⚠️ Not all divergences result in reversals ⚠️ False signals increase in choppy/ranging markets ⚠️ Requires minimum volatility to function properly ⚠️ Performance degrades in strong trending markets (for counter-trend setups) 🎨 Visual Elements Explained Oscillator Panel Blue solid line - Main momentum oscillator (0-100 range) Dotted line at 70 - Overbought threshold Dotted line at 30 - Oversold threshold Dotted line at 50 - Centerline (bullish above, bearish below) Shaded background - Visual reference zone Divergence Markers Blue solid dots/lines - Regular bullish divergence Light blue dots/lines - Hidden bullish divergence Red solid dots/lines - Regular bearish divergence Orange dots/lines - Hidden bearish divergence Labels "UP" label - Long entry on regular bullish divergence "L+" label - Long entry on hidden bullish divergence "DN" label - Potential exit/reversal (bearish divergence) "S+" label - Potential exit/reversal (hidden bearish) ⚡ Performance Optimization Tips Before Going Live Backtest Extensively Test on at least 6-12 months of historical data Use different market conditions (trending, ranging, volatile) Check performance across multiple instruments Paper Trade First Practice on demo account for minimum 1 month Validate signals manually before trusting automation Understand why trades win or lose Optimize Parameters Adjust lookback ranges for your specific market Fine-tune take-profit levels based on average moves Test different stop-loss methods Monitor win rate - aim for >50% minimum Risk Management Never risk more than 1-2% of capital per trade Use position sizing based on stop distance Set maximum daily loss limits Keep a trading journal During Live Trading ✅ Monitor market conditions (trending vs ranging) ✅ Avoid trading during major news events ✅ Respect your stop losses - never remove them ✅ Take partial profits if trade moves significantly ✅ Review and adapt based on actual performance Red Flags to Watch 🚩 Win rate suddenly drops below 40% 🚩 Profit factor falls below 1.0 🚩 Average loss exceeds average win 🚩 Consecutive losing streak (5+ trades) 🚩 Strategy stops generating signals If you see these signs: Stop trading, re-evaluate parameters, check market conditions, or consider if market character has changed. 🔬 Research & Development Suggestions Since you must DO YOUR OWN RESEARCH, here are areas to explore: Parameter Optimization Test different oscillator periods for your instrument Experiment with lookback ranges Find optimal take-profit levels through data analysis Compare ATR vs percentage stops Market Selection Which stocks/indices show best results? Does it work better in certain sectors? Intraday vs specific session times (opening, closing) Combination Strategies Add volume filters Combine with trend indicators Use support/resistance confirmation Add fundamental filters for stock selection Risk Improvements Implement time-based exits (close before market close) Add volatility filters Create different parameter sets for different market conditions 📚 Educational Resources To properly understand and research this strategy: Study divergence trading concepts thoroughly Learn about momentum oscillators and their behavior Understand pivot points and how they form Research market psychology behind reversals Learn proper position sizing and risk management Study technical analysis fundamentals Recommended Learning Path: Technical Analysis basics Oscillator indicators deep dive Divergence patterns and their reliability Backtesting methodologies Risk and money management Trading psychology ✋ Final Reminder BEFORE YOU CLICK "BUY" OR "SELL": ✅ Have you backtested this thoroughly? ✅ Have you paper traded for at least 1 month? ✅ Do you understand WHY each signal triggers? ✅ Have you calculated your position size properly? ✅ Have you set your stop loss? ✅ Can you afford to lose this money completely? ✅ Have you consulted a financial professional? ✅ Are you trading with a clear, calm mind? If you answered NO to any of these - DO NOT TRADE YET. 📞 Support & Responsibility This strategy code is provided "as-is" No warranty or guarantee of any kind User assumes all responsibility and risk Past results do not predict future performance Creator is not liable for any trading losses Trading is risky. Most traders lose money. Trade responsibly or not at all.
Estratégia Pine Script®
por RatMutant001
1MF Buy The Dip - StrategyThis is the indicator "1MF Buy The Dip - Levels" but made a strategy so you can backtest the usage on each levels. There are 2 ways to enter: BY QUANTITY If Use Shares option is enabled, the amount of shares to open on each level will come from the values above. If it's disabled, then it will use whatever settings you did on the Properties Tab. The strategy works the following way: @10% discount - a position is open, targeting the previous high @25% discount - another position is open to price average, targeting the same highs. @50% discount & %70% discount, other positions will be opened, targeting the same highs. The volume of these positions will depend on the Shares Levels you defined (if Use Shares option is enabled), otherwise, on whatever settings you have setup on the Properties tab (percentage, amount, or shares itself). It's a Buy the Dip and hold, so there's no stop loss as its expected to be an investing strategy instead of a trading strategy. The look back bars amount is defaulted on 21, which represents 21 days on the daily timeframe (1-month = 30 days high), and from it will start calculating the discount down. You can play with those numbers to see which one is the best efficient for each stock historically. Any question, leave it below.
Estratégia Pine Script®
por jonathan_1mf
Liquidity Day Strategy V1Title: Liquidity Day Strategy V1 Overview Liquidity Day Strategy V1 is a professional-grade trading tool built on the principles of Institutional Liquidity. It automatically identifies and highlights the Previous Day's High (PDH) and Previous Day's Low (PDL) as critical "Walls of Liquidity." These levels are widely used by institutional traders for stop-hunting or as breakout triggers. This script combines precise price-action levels with Session Visualization, allowing traders to see exactly when and where liquidity is being captured during the Asia, London, and New York market windows. Key Features Bold Liquidity Markers: Automatically plots thick, neon-colored lines for PDH and PDL, ensuring you never miss a key daily level. Session Backgrounds: Visual overlays for Asia, London, and New York sessions to help you trade during peak volatility. Each session can be toggled on/off independently. Built-in Strategy Engine: Includes a backtesting module to track performance, Win Rate, and Drawdown directly on your chart. Dynamic Alert System: Real-time notifications for both "Buy Side" and "Sell Side" breakouts, including live price data in the alerts. Input Settings & Risk Management To ensure consistency across different assets (Gold, Forex, or Crypto), this strategy uses Percentage-Based risk management: Take Profit (%): Sets your target gain. Adjust this based on the asset's average daily range (ADR). Stop Loss (%): Defines your maximum risk per trade to protect your capital. Session Visibility: Fully customizable colors and toggles for each trading session to keep your chart as clean or as detailed as you prefer. Line Styles: Adjustable thickness and color for liquidity levels to suit any chart theme (Dark/Light). How to Trade Breakout Confirmation: The strategy triggers a Long entry when the price closes above the PDH and a Short entry when it closes below the PDL. Session Context: Look for breakouts occurring during the London or NY Open for higher probability moves. Risk Calibration: Use the Strategy Tester to find the optimal TP/SL ratio for your specific timeframe. Disclaimer This script is provided for educational and informational purposes only. Trading financial markets involves significant risk of loss. Past performance, whether real or simulated, is not a guarantee of future results. Always practice proper risk management.
Estratégia Pine Script®
por GodeyeThelasthope
Mindicator - NQ 1Min ScalperMindicator – NQ 1-Min Scalper Model Type: Intraday continuation / liquidity-based scalping Market: NQ Futures Timeframe: 1 Minute 🔎 Core Concept The strategy looks for: Liquidity Sweep Price takes out the previous bar’s high or low and closes back inside — signaling a stop hunt. Displacement Move The candle body must exceed a percentage of ATR, confirming real momentum. Fair Value Gap (FVG) A 3-candle imbalance forms, showing aggressive institutional movement. Higher Timeframe Bias Trades are only taken in the direction of the 5-minute 50 EMA. ⏰ Session Filter Trades only during the defined New York session window, avoiding low-liquidity periods. 📈 Entry & Risk Model Longs: After a downside sweep + bullish displacement + bullish FVG + bullish 5m EMA bias Shorts: After an upside sweep + bearish displacement + bearish FVG + bearish 5m EMA bias Stop Loss: Signal candle high/low Take Profit: Fixed Risk-Reward multiple (default 0.5R) Max Trades: 2 longs and 2 shorts per session 🎯 Strategy Characteristics Fast intraday scalper Structure-based entries Trend-aligned continuation model Strict session discipline Designed for NY volatility conditions This is a liquidity-engineered scalping system that combines stop hunts, momentum confirmation, and imbalance continuation within a controlled session framework.
Estratégia Pine Script®
por hoang15241
NQ 1M BB Reversal (London + NY Only)Strategy Summary This strategy trades NQ futures on the 1-minute timeframe using a Bollinger Band extreme reversal model. It is built around one core idea: When price stretches to statistically extreme levels (3 standard deviations from the mean), it is likely to revert. 🔎 Core Logic Bollinger Bands Length: 17 Standard Deviation: 3 Long Entry: When price closes at or below the lower band Short Entry: When price closes at or above the upper band Stop Loss: 10 ticks Take Profit: 20 ticks Risk-to-Reward: 1:2 ⏰ Session Filter Trades are only taken during: London Session New York Session Asia session is excluded to avoid low-liquidity and grinding conditions. 📊 Strategy Characteristics Mean-reversion based Designed for high-volatility sessions Tight risk control Moderate trade frequency (~3–5 per day typical) Performs best in rotational or range conditions May struggle during strong trend expansion days 🎯 Edge Profile With optimized settings: Win rate ~52% Profit Factor ~1.9+ Controlled drawdown Positive expectancy per trade
Estratégia Pine Script®
por hoang15241
ORB SESSIONS## ORB SESSIONS — Multi-Session Opening Range Breakout + Retest Strategy **ORB SESSIONS** is a multi-session Opening Range Breakout (ORB) strategy built for intraday trading across the **New York, Asia, and London** sessions, with optional overlays (PDH/PDL, session levels, FVGs) and an optional higher-timeframe bias dashboard. It is designed to standardize ORB execution with configurable **breakout vs retest** entry logic, **R-multiple targets**, optional **trailing-to-TP behavior**, and a **prop-firm “flat window”** to force risk compliance. --- ## Core concept For each enabled session, the script: 1. Builds an **opening range** (high/low, optional midline) during a configurable ORB window. 2. Trades breakouts from that range using the selected **Entry Mode**: * **Breakout**: enter on a confirmed close through the ORB boundary. * **Retest Zone**: after breakout, wait for a wick back to the broken level. * **Retest Midpoint**: after breakout, wait for a wick back to the ORB midpoint. 3. Manages risk via session-specific **Stop Loss methods** and up to **3 take-profits** expressed as **R:R multiples**. 4. Optionally uses a **trailing stop** mechanic that “arms” after price moves **N ticks beyond a TP**, then trails the stop to that TP level. 5. Optionally **re-arms** after a trade closes (with max trades/session, exit-type filter, direction filter, cooldown bars, and “bars inside ORB” requirements). --- ## What’s included ### Trading modules (per session) * **Session 1: New York ORB** (enable, direction filter, ORB start/duration, session end, flatten at end, SL method, TP R:R and quantities). * **Session 2: Asia ORB** (same structure). * **Session 3: London ORB** (same structure). ### Filters & controls * **Timezone selector** (all session times interpret in this timezone). * **Day-of-week filter** (enable/disable specific weekdays). * **Prop Firm Flat Window**: optionally flatten/block new entries during a specified time window. ### Visual overlays (optional) * Historical ORB lines, optional midlines, labels. * PDH/PDL, Asian/London/NY session overlays, and Fair Value Gaps (FVG) display. --- ## Recommended directions for use 1. **Apply to an intraday chart** (commonly 1m–15m). 2. Open **Settings → Global Settings**: * Set **Timezone** to match your intended session definitions. 3. Open **Trade Settings (All Sessions)**: * Choose **Entry Mode** (Breakout vs Retest Zone vs Retest Midpoint). * Set **Contracts** and whether to show SL/TP visuals. 4. Configure each session you want to trade: * Enable/disable sessions, choose direction (long/short/both), set ORB start + duration, and define session end/flatten behavior. 5. Configure exits: * Pick an SL method (Midpoint / Opposite Side / Fixed Points) and set TP R:R levels and TP quantities per session. 6. Optional: turn on **Trailing Stop** and/or **Re-Arm**: * Trailing: arms after N ticks beyond TP, then trails stop to TP. * Re-arm: control max trades/session, cooldown bars, and re-arm conditions. --- ## Alerts (automation-ready) This script is designed to run with **a single TradingView alert** that triggers only when the strategy actually fills orders. **Create ONE alert** and set: * **Condition**: this strategy * **Trigger**: **Order fills only** * **Message**: `{{strategy.order.alert_message}}` The script attaches an order-specific alert payload at fill time (Buy/Sell/Exit), so your automation receives exactly what the strategy executed. --- ## Notes / expectations * ORB behavior depends on how you define each session’s ORB window and the chart’s liquidity/volatility; optimize ORB duration + SL method + TP R:R per market. * If you enable **Prop Firm Flat Window**, entries are blocked and positions can be forced flat during that period (use this to comply with rules). Note : description written by ChatGPT
Estratégia Pine Script®
por VONKAR
Linda Bradford Raschke Perspective Shift Knot Infinite CycleLinda Bradford Raschke 's Proprietary Perspective Shift Strategy: A highly selective trend-following strategy drawing from knot theory's algebraic trick—where infinite structures over integers become finite over Laurent polynomials. Linear EMAs capture "endless" price trends, while log-transformed EMAs provide a compressed "shifted" view to confirm entries, reducing false signals in exponential moves. Signals require strong trend confirmation (high ADX >35) and directional momentum (DI bias) for entries. Enter long on bullish EMA crossovers confirmed by log alignment and trend strength; short on bearish. Extremely strict filtering results in very few trades but low drawdown and high reward potential on surviving signals. Ideal for XAUUSD on 45-minute timeframe. Always combine with proper risk management—aim for 1-2% risk per trade. The mathematical concept viewing the first homology group of a knot's infinite cyclic cover as a module that appears infinitely generated over the integers but becomes finitely generated with torsion when considered as a module over the Laurent polynomial ring — originates from the work of James Waddell Alexander II.
Estratégia Pine Script®
por uzair2join
Martingale DCA Grid Bot Simulator with Compounding V4.1Simulates a DCA Martingale grid bot for backtesting purposes, with an option to compound earnings by every number of months. This bot uses the same order size for the initial order as it does for the first grid buy. Several popular crypto grid bots function this way. **This is a work in progress. Backtesting results will vary based on chosen timeframe and calculation options. Check results yourself to verify a level of accuracy you're comfortable with.** Remember to set pyramiding to at least your number of grids +1 (default is 15 for up to 14 grids) For high value coins like bitcoin, you will have to drastically reduce your "Min Qty Threshold" in the options pages, especially for small accounts. This ensures the bot can buy in small enough quantities for your initial order and first grids to make sense. The simulation will not be accurate or could completely break without this setting low enough. Simply lower this value until results stabilize. The bot will give best results with the bar magnifier enabled. Otherwise, lower timeframes should give more accurate results at the expense of shorter time in the market.
Estratégia Pine Script®
por happydappyman
Uni Trend Catcher ~ CharonQuant⏳ 𝓤𝓷𝓲 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ ~ 𝓒𝓱𝓪𝓻𝓸𝓷𝓠𝓾𝓪𝓷 Markets trend. Not all the time. Not cleanly. But when they do, that is where the real money is made. ⏳ 𝓤𝓷𝓲 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ is built on one core philosophy: ride the market's momentum, step aside when it fades. No prediction. No overfitting. Just structured, robust trend participation across any asset class. This is a long-only strategy designed for traders who understand a simple truth: capital preservation first, profits follow. Core Concept: Universal Trend Following This system is engineered to adapt. Stocks. Forex. Crypto. Commodities. Indices. The logic dynamically adjusts parameters per asset based on volatility and price behavior, allowing it to remain effective across different markets and timeframes. Whether you trade daily charts or intraday swings, the framework adapts to the environment. The goal is not just good backtest numbers. The goal is effective trading and strategic placement. How It Works The strategy aggregates 5 powerful trend-following indicators with different calculations. Each component measures trend from a different angle, volatility, structure, strength, direction, and confirmation. Rather than relying on a single signal, the system synthesizes these inputs into a unified trend decision engine. Entry Logic Enters long only during confirmed bullish trends Requires alignment across the majority of the indicators Dynamically adjusts to asset volatility and behavior Exit Logic Exits to cash when trends weaken or turn bearish No shorting. Keeps traders positioned on the right side of structural strength Clear trend system: Long in bullish trends. Cash in bearish conditions. This structure is what allows traders to stay protected in any condition without overcomplicating execution. Key Strengths Long-only strategy Adaptive to all assets and timeframes Rigorously backtested and forward-tested in real conditions Robust risk management reduces drawdowns Capital preservation prioritized over chasing metrics The risk framework is built for real-world trading success. Drawdowns are managed through disciplined exits rather than hope-based holding. Why It Matters This strategy helps you: Ride medium-term trending moves Reduce emotional trading decisions Stay engaged in bull markets Stay safe in bear markets Unlock multi-asset trend power in one unified system Deploy capital across diversified portfolios with structured logic It is designed for traders who want consistent trend participation without indicator overload. Final Word ⏳ 𝓤𝓷𝓲 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ is not flashy. It is not over-engineered. It is a powerful, no-nonsense framework built to ride the market’s momentum and step aside when conditions shift. If you are serious about structured trend participation across markets, this is your edge. Simple rules. Adaptive logic. Capital preservation first. Unlock the discipline. Unlock the consistency. Unlock the trend.
Estratégia Pine Script®
por CharonQuant
2
SOL Trend Catcher ~ CharonQuant⏳ 𝓢𝓞𝓛 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ ~ 𝓒𝓱𝓪𝓻𝓸𝓷𝓠𝓾𝓪𝓷𝓽 ⏳ 𝓢𝓞𝓛 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ is a Trend Following algorithm designed specifically to capture Solana’s sustained directional moves on the daily timeframe. How It Works: At its core, this strategy uses structured confirmation through diversification. It aggregates 5 trend following indicators, each built with different calculations. These include moving averages, for loop implementations, supertrend logic, and other complementary trend-following components. Each indicator independently evaluates SOL’s price structure. The system then applies a voting mechanism. If the majority of indicators generate a long signal, the strategy initiates a long position. If the majority generate a short signal, it triggers a short position. This majority vote framework ensures trades are not based on a single data point. Instead, entries and exits require alignment across multiple models, providing strong validation before capital is deployed. Testing & Robustness: The strategy is a robust algorithm that has been backtested and forward tested. Historical testing confirms the structural logic across different Solana market phases, while forward testing validates consistent behavior in live market conditions. The focus is systematic trend participation rather than short-term prediction. Key Features: • Aggregation of 5 diverse trend following indicators • Majority-based voting system for confirmation • Integrated moving averages and supertrend components • Programmatic for loop implementations for structural consistency • Backtested and forward tested for reliability Important Usage Notes: This strategy is uniquely developed for SOL on the 1D chart. Solana’s volatility profile and daily trend structure are specifically calibrated into the model. For intended behavior and validation logic to remain intact, it must be used exclusively on SOL and the 1D timeframe. Concluding Remarks: ⏳ 𝓢𝓞𝓛 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ ~ 𝓒𝓱𝓪𝓻𝓸𝓷𝓠𝓾𝓪𝓷𝓽 provides traders with a disciplined, rules-based framework for navigating Solana’s powerful and often volatile trend cycles. By requiring multi-indicator agreement before acting, the strategy promotes structured participation in sustained moves rather than reactive trading. For traders operating in fast-moving altcoin markets, this system offers clarity, confirmation, and a systematic way to capture Solana trends with greater consistency and control.
Estratégia Pine Script®
por CharonQuant
ETH Trend Catcher ~ CharonQuant⏳ 𝓔𝓣𝓗 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ ~ 𝓒𝓱𝓪𝓻𝓸𝓷𝓠𝓾𝓪𝓷𝓽 ⏳ 𝓔𝓣𝓗 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ is a Trend Following algorithm engineered specifically to identify and confirm Ethereum’s primary directional moves on the daily chart. How It Works: This strategy is built on structured confirmation, not impulse. It aggregates 6 trend following indicators, each using different calculations. These include forecasting models, root mean square deviation and volatility measurements, ATR, moving averages, supertrend logic, and other complementary trend tools. Each component independently evaluates Ethereum’s price behavior. When the majority of these indicators generate a long signal, the strategy initiates a long position. When the majority produce a short signal, it triggers a short position. This majority-based aggregation acts as a built-in filter. Rather than reacting to a single signal, the system waits for alignment across multiple models. The result is stronger validation for trade entries and exits, reducing exposure to isolated false signals. Testing & Robustness: The strategy is a robust algorithm that has been backtested and forward tested. Historical testing ensures that the structure performs consistently across different market conditions, while forward testing validates that the logic remains stable in live environments. The focus is durability and systematic execution, not curve-fitting to a single market phase. Key Features: • Aggregation of 6 independent trend following indicators • Majority-based confirmation for long and short entries • Volatility-aware components such as ATR and root mean square deviation • Integrated forecasting and supertrend logic • Backtested and forward tested for structural reliability Important Usage Notes: This strategy is uniquely developed for ETH on the 1D chart. Ethereum’s volatility profile, liquidity structure, and daily trend rhythm are specifically calibrated into this model. For intended performance, it must be used exclusively on ETH and the 1D timeframe. Concluding Remarks: ⏳ 𝓔𝓣𝓗 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ provides traders with a systematic framework for capturing Ethereum’s sustained directional moves. By requiring multi-indicator agreement before entering positions, it promotes disciplined participation rather than reactive trading. For traders seeking structured exposure to Ethereum’s major daily trends, this strategy offers clarity, confirmation, and a rules-based approach designed to follow momentum where it truly matters.
Estratégia Pine Script®
por CharonQuant
BTC Trend Catcher ~ CharonQuant⏳ 𝓑𝓣𝓒 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ ~ 𝓒𝓱𝓪𝓻𝓸𝓷𝓠𝓾𝓪𝓷𝓽 ⏳ 𝓑𝓣𝓒 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ is a Trend Following algorithm engineered with one clear purpose: identify high-probability trend direction on BTC and act only when alignment is strong. How It Works: At its core, this strategy is built on confirmation through aggregation. Instead of relying on a single indicator, it combines 6 trend following indicators, each with their different calculations. These include regression analysis, moving averages, root mean square deviation and volatility metrics, for loop logic, supertrend calculations, and additional complementary components. When the majority of these indicators generate a long signal, the strategy initiates a long position. When the majority produce a short signal, it triggers a short position. This majority voting mechanism filters out noise and avoids impulsive entries. Trades are executed only when multiple models agree, creating strong validation for both entries and exits. Testing & Reliability: The strategy is a robust algorithm that has been backtested and forward tested. Historical simulations validate its structural integrity, while forward testing confirms its behavior in live market conditions. Key Features: • Aggregation of 6 independent trend following models • Built-in validation for both entries and exits • Designed specifically for BTC • Backtested and forward tested for robustness Important Usage Notes: This strategy is uniquely developed for BTC on the 1D chart. Bitcoin on the daily timeframe has a specific rhythm, volatility profile, and structural behavior. The algorithm is calibrated precisely for that environment. For optimal performance, it must be used exactly as intended: BTC, 1D timeframe. Concluding Remarks: ⏳ 𝓑𝓣𝓒 𝓣𝓻𝓮𝓷𝓭 𝓒𝓪𝓽𝓬𝓱𝓮𝓻 ⏳ offers traders a systematic way to capture Bitcoin’s major trends while filtering out lower-probability noise. By combining multiple trend models into a unified decision engine, it provides structured confirmation rather than emotional reaction. For traders focused on riding sustained BTC moves on the daily chart, this strategy delivers clarity, discipline, and a data-driven framework for navigating Bitcoin’s powerful trends.
Estratégia Pine Script®
por CharonQuant
MASU+ v7.2 (NW+ELM+BOS)# MASU+ v7.2 — Institutional Multi-Strategy Framework (NW + ELM + BOS) ## Overview MASU+ v7.2 is an advanced multi-strategy trading system that combines institutional-grade Smart Money Concepts (SMC), machine learning signal filtering, and adaptive risk management into a single unified framework. The strategy is designed for intraday and swing trading across forex, indices, and commodities. The core philosophy is **high-confluence entries only** — every trade must pass through multiple independent filters before execution, ensuring that only the strongest setups are taken. --- ## Key Components ### 1. Nadaraya-Watson Kernel Ribbon An 8-line non-parametric regression ribbon built on a Fibonacci bandwidth grid (3, 5, 8, 13, 21, 34, 55, 89). The ribbon acts as a dynamic trend filter with three operating modes: - **Strict** — all 8 lines must be perfectly ordered - **Relaxed** — a configurable threshold of ordered pairs (default 6/7) - **Expansion** — ribbon width is increasing in the trend direction The bandwidth can operate in **Fixed** or **Adaptive** mode. In Adaptive mode, bandwidth auto-scales based on ATR-normalized volatility, making the ribbon more responsive in volatile conditions and smoother in calm markets. ### 2. ELM Neural Filter (Extreme Learning Machine) A lightweight online-learning neural network that trains in real time on 7 normalized features: - RSI, Rate of Change, Distance from EMA 200, ADX, NW Kernel Slope, Ribbon Order Score, and Relative Volume The ELM predicts price direction over a configurable lookahead window (default: 5 bars) and outputs a probability score (0–1). Key v7.2 improvements include: - **Weight decay regularization** to prevent parameter drift - **Real-time accuracy calibration** — the ELM tracks its own prediction accuracy and adjusts its voting weight accordingly. An ELM with <50% accuracy effectively gets silenced. - The ELM can act as a soft vote (bonus confluence), a hard blocker, or influence position sizing — all configurable. ### 3. Smart Money Concepts (SMC) Full institutional order flow toolkit: - **Order Blocks** — bullish/bearish engulfing patterns with body-to-range ratio filtering - **Fair Value Gaps (FVG)** — imbalance detection with ATR-scaled minimum size - **Liquidity Sweeps** — stop hunt detection at recent swing highs/lows - **Break of Structure (BOS)** — pivot-based market structure tracking - **Demand/Supply Zones** — impulse-based zones that auto-expire when violated ### 4. BOS Immediate Entry (v7.2) A dedicated scalp-style entry that fires **immediately** when a Break of Structure is detected — no confirmation bars required. Features: - **TP = 0.75 × ATR** — tight scalp target for quick profit capture - **Aggressive trailing** — activates at just 0.1 × ATR from entry with a 0.15 × ATR offset - **Full confluence gate** — BOS entries require the same high confluence score (≥ 7.0) as all other entries, preventing low-quality breakout chasing ### 5. Multi-Timeframe (MTF) Filter Higher timeframe EMA alignment check (default: 4H). Both fast and slow EMAs on the higher timeframe must agree with the trade direction, and price must be on the correct side of the fast EMA. ### 6. Order Flow Analysis - **VWAP** with 3 standard deviation bands (±1σ, ±2σ, ±3σ) - **Cumulative Volume Delta (CVD)** — divergence detection between price and volume delta - **Volume Profile POC** — Point of Control visualization --- ## Confluence Engine (v7.2) Every entry — whether trend-following, breakout, mean-reversion, or BOS — must achieve a **minimum weighted confluence score of 7.0** (out of a maximum 7.5 with default weights). Each filter contributes a configurable weight: | Filter | Default Weight | |---|---| | MTF Alignment | 2.0 | | NW Ribbon | 1.5 | | ELM AI | 1.0 (calibration-adjusted) | | Order Flow | 1.0 | | Smart Money | 1.0 | | ADX Trend Strength | 0.5 | | NW Slope Direction | 0.5 | | **Total** | **7.5** | With the default threshold of 7.0, nearly all filters must agree before a trade is placed. This dramatically reduces noise trades and false signals. --- ## Risk Management ### Volatility Regime Adaptation The strategy classifies the market into 4 regimes and adapts SL/TP accordingly: | Regime | SL Mult | TP Mult | |---|---|---| | High Vol + Trending | 1.5× ATR | 2.5× ATR | | High Vol + Ranging | 1.2× ATR | 1.8× ATR | | Low Vol + Trending | 1.5× ATR | 2.5× ATR | | Low Vol + Ranging | 1.0× ATR | 1.5× ATR | ### Trailing Stop Configurable trailing stop that activates at 25% of the TP distance (default) with a tight 0.2 × ATR offset. Designed to lock in profits early while giving trades room to breathe. ### Kelly Criterion Sizing Position size is dynamically calculated using the Kelly formula based on real-time win rate and win/loss ratio, capped at 25% to prevent over-leverage. ### Quality-Based Sizing Signal confluence score directly affects position size: high-quality setups get full allocation, moderate setups get 80%, and weaker setups get 60%. ### Equity Guard Automatic circuit breaker that pauses trading after a configurable number of consecutive losses (default: 5) or when drawdown exceeds a threshold (default: 15%). Resumes after a cooldown period to prevent emotional revenge trading. ### Cost-Aware Filter Estimates total round-trip cost (spread + commission) and blocks entries where ATR is too small relative to trading costs. Prevents churning in low-volatility environments. --- ## Entry Types 1. **Trend Following** — EMA crossover + volume spike + bullish/bearish trend confirmation 2. **Breakout** — New high/low break + volume spike + EMA filter alignment 3. **Mean Reversion** — Bollinger Band extreme + RSI oversold/overbought + ranging regime 4. **BOS Scalp** — Immediate entry on Break of Structure with tight TP and aggressive trailing All entries require: session filter ✓ | confluence ≥ 7.0 ✓ | R:R check ✓ | cost filter ✓ | equity guard clear ✓ | ELM not blocking ✓ --- ## Dashboard A comprehensive real-time institutional dashboard displays: - Multi-timeframe trend alignment (15M / 1H / 4H) - NW Ribbon state and bandwidth scale - ELM AI probability, accuracy, and confidence weight - Volatility regime classification - Order flow and Smart Money signals - Confluence score with quality rating - Adapted SL/TP levels with regime multipliers - Kelly position sizing - Equity guard status with drawdown tracking - BOS entry status - Session detection (London / New York / Asia / Overlap) - Active demand/supply zone count --- ## What's New in v7.2 - **Confluence threshold raised to 7.0** for all entry types — only the highest-conviction trades are taken - **BOS immediate entry** — no confirmation bar delay; enters on the breakout candle itself - **BOS TP = 0.75 × ATR** — tighter scalp target optimized for quick captures with trailing doing the heavy lifting - **Unified confluence gate** — BOS entries now use the same min_confluence_score as standard entries (no separate hardcoded threshold) --- ## Recommended Settings - **Timeframe:** 1H (primary), with 4H MTF filter - **Session:** 09:00–22:00 (covers London + New York) - **Assets:** Forex majors, Gold (XAUUSD), US indices (NAS100, SPX500) - **Account:** Works with standard lot sizing; commission and spread inputs should be adjusted to your broker --- ## Disclaimer This strategy is provided for educational and research purposes. Past performance does not guarantee future results. Always backtest thoroughly and trade with proper risk management. The ELM neural component learns in real time and its accuracy varies across market conditions.
Estratégia Pine Script®
por Mark_Novak