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Neural Network SPXL Strategy(NNSS)NNSS acts as a Visual Dashboard for our proprietary backend algorithm, bringing high-performance computing signals directly to your chart. 🤖 The "Black Box" Edge Unlike lagging indicators (RSI, MACD), NNSS utilizes an external Statistical Probability Model. It analyzes market regimes and volatility to generate predictive, high-confidence signals. 🛡️ Risk-First Methodology Designed to outperform Buy & Hold by minimizing drawdowns. Risk-On: Aggressively captures upside trends. Risk-Off: Swiftly moves to CASH (0% Exposure) when systemic risk is detected. 🚀 Key Features T+1 Action Plan: Clearly indicates the required action for the next market open. Dynamic Positioning: Adjusts position sizing (e.g., 100%, 16%, 0%) daily based on model confidence. 🔒 Invite-Only Access This is a private quantitative strategy. To unlock access, please contact me directly via private message. 🤖 Automate This Strategy Precise execution at the T+1 Open is critical. Manual trading often leads to slippage. We recommend StratOne for a 100% hands-free experience. 👉 Start Automating: Search "NNSS" on StratOne.ai. Disclaimer: For informational purposes only. Trading leveraged assets involves risk.
Стратегия Pine Script®
от OneLookQuant
Neural Network SPXL Strategy(Public Visualizer)The NNSS system represents a sophisticated, institutional-grade approach to trading leveraged ETFs (specifically SPXL). This script acts as the **Visual Dashboard** for our proprietary backend algorithm, bringing high-performance computing signals directly to your TradingView chart. **🤖 The "Black Box" Advantage** Unlike standard indicators (RSI, MACD) that lag behind price, NNSS utilizes a complex **Statistical Probability Model** running on external servers. It analyzes market regimes, volatility structures, and historical patterns to generate high-confidence execution signals. **🛡️ Risk-First Methodology** Trading 3x leveraged ETFs requires precision. Our system prioritizes capital preservation: * **Risk-On:** Aggressively captures upside during stable trends. * **Risk-Off:** swiftly moves to **CASH (0% Exposure)** when the model detects elevated systemic risk or statistical anomalies. **🚀 Key Features** * **T+1 Action Plan:** The "T+1 PLAN" label clearly indicates the required action for the *next market open* (Buy, Add, Reduce, or Clear). * **Dynamic Positioning:** The system doesn't just "Buy" or "Sell"; it intelligently adjusts position sizing (e.g., 100%, 16%, 0%) based on the model's confidence level. * **Clarity:** No clutter. Only actionable signals are displayed. * 🟩 **Green Labels:** Accumulation / Holding * 🟥 **Red Labels:** Reduction / Liquidation / Cash Preservation **📊 Performance Goal** The strategy is engineered to deliver a superior **Profit Factor** compared to a standard Buy & Hold approach by minimizing drawdowns during bear markets and corrections. **🔒 Invite-Only Access** This is a private quantitative strategy. The source code is protected to maintain the integrity of our proprietary logic. **👉 How to Get Access** To unlock this strategy and receive daily signal updates, please check the **Signature** below or contact me directly via private message. --- *Disclaimer: This script is for informational purposes only. Trading leveraged assets involves significant risk. Past performance is not indicative of future results.*
Стратегия Pine Script®
от OneLookQuant
4
Swing Strategy Feature Set C [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 C includes concepts beginning with the letter "C" 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: Candle Trend Candlestick Patterns Chande Momentum Oscillator Chandelier Exit Chart Patterns Commodity Channel Index Coppock Curve █   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. 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 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 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 C 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 Candle Trend Filter The candle trend filter is an entry filter that evaluates short-term directional candle behaviour as a state-based trend, defined by transitions between candle colours. A green candle trend begins when a green candle forms following one or more red candles. The trend remains valid while consecutive green candles continue to form. The green candle trend terminates when a red candle forms, completing the sequence. A red candle trend begins when a red candle forms following one or more green candles. The trend remains valid while consecutive red candles continue to form. The red candle trend terminates when a green candle forms, completing the sequence. In the context of the core swing strategy, candle trends and swing confirmation are structurally synchronised but directionally inverted. Swing lows, which trigger long entries, are confirmed only at the termination of red candle trends, when a green candle completes the trough. Conversely, swing highs, which trigger short entries, are confirmed only at the termination of green candle trends, when a red candle completes the peak. As a result, long entries inherently occur following completed red candle trends and short entries inherently occur following completed green candle trends. This makes green candle trends incompatible with long entries and red candle trends incompatible with short entries. The default mode for the candle trend filter is set to "None". If the candle trend filter mode is set to "Green", the filter will return false for long trades. Conversely, if the candle trend filter mode is set to "Red", the filter will return false for short trades. The candle trend count defines the number of consecutive same-colour candles required to form a valid candle trend condition for the filter. The opposing-colour candle that follows is not part of the trend itself, but serves to terminate the trend and confirm its completion. The default candle trend count is set to 3. Users can apply the candle trend filter and adjust trend count via strategy Settings/Inputs/CANDLE TREND FILTER. Candlestick Pattern Filter The candlestick patterns used in this script are the same as those included in my candlestick patterns library and indicator. Link below for library and indicator, respectively: The candlestick pattern filter is an entry filter that validates trade signals based on the presence of a user-selected candlestick pattern. Separate filters are provided for long and short entries. Each filter evaluates only patterns that are directionally compatible with the corresponding core entry condition. Patterns that are structurally incompatible with the core swing logic are evaluated using a one-candle offset. This is necessary where a pattern would otherwise coincide with, or conflict with, the candle used to confirm the core swing high or swing low condition. In these cases, the offset ensures that the candlestick pattern can still be included in the feature set, regardless of its traditional bullish or bearish classification. The default long and short candlestick pattern filter modes are set to "None". Users can apply the candlestick pattern filter via strategy Settings/Inputs/CANDLESTICK PATTERN FILTERS. Chande Momentum Oscillator (CMO) Filters The default CMO inputs are as follows: Source is set to "Close". Length is set to 14. Users can adjust the CMO inputs via strategy Settings/Inputs/CHANDE MOMENTUM OSCILLATOR (CMO).
 The CMO minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply above-equal filter is set to false. Above-equal threshold is set to -100. Apply below-equal filter is set to false. Below-equal threshold is set to 100. The CMO 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 CMO 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 CMO filters and adjust filter parameters via strategy Settings/Inputs/CMO FILTERS. Chandelier Exit (CE) Filters Users can apply up to two independent close above-equal/below filters (see generic filters section above), one for each of the two CE values (long and short). The default mode for the close above-equal/below filters is set to "None". The CE rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined CE value is rejected exclusive of the other one. The default CE rejection filter mode is set to "None". The long CE above-equal/below short CE filter is an entry filter that evaluates the relative positioning of the long and short CE values and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when long CE is greater than or equal to short CE. "Below" returns true when long CE is less than short CE. 
Users can apply the CE filters and adjust filter parameters via strategy Settings/Inputs/CE FILTERS. Chart Pattern Filter The chart patterns used in this script are the same as those included in my chart patterns library and indicator. Link below for library and indicator, respectively: The chart pattern filter is an entry filter that validates trade signals based on the presence of a user-selected chart pattern. Separate filters are provided for long and short entries. Each filter evaluates only patterns that are directionally compatible with the corresponding core entry condition. The default long and short chart pattern filter modes are set to "None". Users can apply the chart pattern filter via strategy Settings/Inputs/CHART PATTERN FILTERS. Commodity Channel Index (CCI) Filters The default CCI length is set to 20. Users can adjust the CCI inputs via strategy Settings/Inputs/COMMODITY CHANNEL INDEX (CCI).
 The CCI 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 CCI 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 CCI filters and adjust filter parameters via strategy Settings/Inputs/CCI FILTERS. Coppock Curve (CC) Filters The default CC inputs are as follows: Long CC length is set to 10. Short CC length is set to 14. CC smoothing length is set to 11. Users can adjust the CC inputs via strategy Settings/Inputs/COPPOCK CURVE (CC).
 The CC above-equal/below zero filter is defined as an entry filter that evaluates the CC value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the CC value is greater than or equal to zero. "Below" returns true when the CC value is less than zero. The default CC above-equal/below zero filter mode is set to "None". The CC 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 CC 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 CC filters and adjust filter parameters via strategy Settings/Inputs/CC 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.
Стратегия Pine Script®
от theEccentricTrader
Interest Rate Direction ProbabilityThis script estimates the probability that an interest‑rate series (e.g., Fed Funds Rate, 10‑yr Treasury yield) will move up or down in the next period. It exists as a learning effort in creating TV Strategies. It's probably good for nothing. Then again, I've found 'good for nothing' scripts from others that I've twisted to neat indicator toys so… It uses a simple rolling‑lookback of historical data to count how often a chosen predictor (currently 10‑bar momentum) correctly forecasted the direction of the next move. The resulting probability curves are plotted on the chart, and optional strategy entries can be generated when those probabilities cross user‑defined thresholds. Important: This is a research / back‑testing tool only. Predicting macro‑economic rates is inherently noisy and uncertain; never rely on this script for live trading without extensive validation. What it tries to do: •Historical Probability: Calculates the frequency of correct predictions over a user‑defined lookback window. •Momentum Predictor: Uses 10‑bar momentum (close – SMA) as the primary signal. •Correlation Preview: Correlation between the rate and unemployment (20‑bar) is computed but not yet used in the probability calculation – a placeholder for future extensions. •Plotting: Two curves: green = probability of an up‑move, red = probability of a down‑move. •Strategy Mode: Optional strategy() logic that goes long when prob_up > thresh_up and short when prob_down > thresh_dn. •Customizable Inputs: Rate symbol, unemployment symbol, lookback length, probability thresholds.
Стратегия Pine Script®
от gurple
Voce Eterna Quantistica - FINAL📈 Performance Analysis (Rating: AAA+++) Net P&L (+$59,772.65 USD): This is your pure net gain. You have nearly doubled the initial capital within a single operational cycle. Percentage Return (+75.01%): A performance that outperforms any traditional market index (such as the S&P 500 or Nasdaq) during the same period. Position Size ($79.68K USD): The system allocated nearly all available capital, demonstrating maximum confidence in the current trend. Maximum Favorable Excursion (79.85%): This indicates the system effectively rode the profit trend almost to its absolute peak before recalibrating. 🛡️ What do these metrics mean for your Business? These figures are more than just "trading" results; they are your primary commercial asset. Use them to demonstrate that: The system is volatility-proof: It remained resilient and maintained its trajectory even during market fluctuations. Drawdown integration works: Despite market dips, the net profit remained the dominant force. Scalability: The transition from $100K to nearly $160K (Capital + Profit) occurred seamlessly.
Стратегия Pine Script®
от abcdddiego
Voce Eterna - Diamond Edition1. The Philosophy: "Take It and Bring It Home" Unlike common strategies that wait months to close a single trade, this system is designed with surgical precision: to extract €100 from the market whenever possible. Fixed Target: As soon as the open profit touches or exceeds €100, the algorithm instantly closes the position. Frequency: The system aims to generate dozens of these "micro-withdrawals" (63 or more in a year), creating a compounded and psychologically sustainable return. 2. Technical Architecture: Power and Precision The plan utilizes a high-impact configuration to maximize the probability of success: Real Exposure: Despite an initial capital of €10,000, the code is programmed to move a monetary mass of €50,000 (5x Leverage). This allows small index movements to quickly generate the required €100 profit. Volatility Filter: The robot enters the field only when the ATR (volatilità) is 20% higher than its average, ensuring it operates only when the market is "active" and capable of reaching the target rapidly. Rapid Crossover: It uses the SMA 9 and SMA 21 moving averages to identify the start of an explosive trend. 3. Safety and Protection Capital protection is integrated into every line of code: Emergency Exit: If the trend reverses (crossunder), the system closes everything immediately to limit damage, without waiting for the stop loss. Tick-by-Tick Monitoring: Calculations occur on every single price variation, guaranteeing that the €100 withdrawal happens to the millisecond. 4. Expected Results (2025-2026 Analysis) Based on the visualized history, the plan has demonstrated the ability to beat the traditional market: Total Return: Over 21% net profit accumulated in just over a year. Transparent Management: Thanks to the "Diamond Edition" dashboard, the investor always sees how far they are from the target and how much has already been secured. Conclusion: This is not a gamble; it is an algorithmic ATM. While others hope for the "big score," we withdraw €100 at a time.
Стратегия Pine Script®
от abcdddiego
Voce Eterna - Trailing Fix - 4.0Plan: Trailing Fix 4.0 – Dynamic Profit Capture 1. The Concept: "Dynamic Pursuit" Unlike a fixed target, Trailing Fix 4.0 does not close the trade at a pre-set price. Instead, it "shadows" the price as it climbs. Maximum Extension: The system allows profits to run as long as the market exhibits upward momentum. Peak Protection: If the market reverses course, the system intervenes to lock in the accumulated gains before they evaporate. 2. Technical Execution (Pragmatic Approach) The module operates through three critical phases visible in your performance reports: Activation (Threshold €100): The protection mechanism activates only once the trade reaches a minimum open profit of €100. High-Water Mark Memory: The code constantly records the highest profit point reached during the trade (e.g., €300). "Drop-off" Closure: If the profit falls by a pre-set distance (e.g., €30 or €40) from its peak, the script executes an immediate "Profit Withdrawal" (Ritiro Profitto). 3. Performance Analysis On your charts, this plan is distinguished by its surgical precision: Winning Trades: Operations such as #112 and #113 show the "Ritiro Profitto" signal triggering exactly after a growth peak in the index. Efficiency: This method avoids exiting too early during major trends while ensuring that a sudden reversal doesn't turn a winning trade into a loss. Diamond Integration: On the dashboard, Trailing Fix results contribute directly to reaching the 20% Target, accelerating the maturation of your 15% performance fee. Why include this in the Investor Proposal? Presenting Trailing Fix 4.0 proves to the investor that the software is not "blind" but adapts to market velocity. It serves as pragmatic evidence that the capital is managed with a logic of maximizing yield while minimizing "regret risk".
Стратегия Pine Script®
от abcdddiego
BTC OT Quant Alpha: Institutional Trend Hunter based on Optimal Core Philosophy: This is not your average RSI or MACD mashup. BTC OT introduces a Nobel-level mathematical framework—Optimal Transport Theory—to treat Bitcoin's price action as a problem of probability distribution transport. Instead of predicting price, it calculates the Wasserstein Distance between short-term price distributions and long-term baselines to precisely identify shifts in "Market Regimes." Key Features: The Mathematical Edge: Moving beyond lagging traditional indicators, it captures trend initiations directly in probability space. This is a quantitative method often used by hedge funds, now available on TradingView. 4H Swing Hunter: Specifically fine-tuned for the Bitcoin 4-Hour (4H) timeframe. It ignores intraday noise and refuses to "HODL" blindly through bear markets. It targets only the most profitable impulsive waves. Trend Shield: A unique "EMA Dual-Verification Mechanism." Even if an OT signal triggers, the strategy refuses to open a trade if the price is below the key Trend Shield. This perfectly filters out "dead cat bounces" and bull traps in bear markets. No Repainting: Strictly executed with process_orders_on_close=true. The backtest results you see are the real signals generated. What you see is what you get—no repainting, ever. Performance (2016-2026 Backtest): Total Return: > 40,000% (400x Return, significantly outperforming Buy & Hold) Max Drawdown: < 50% (Exceptional risk control for a volatile asset like BTC) Profit Factor: > 1.45 Win Rate: ~38% (Typical of robust trend-following strategies: Cut losses short, let profits run. We don't chase win rate; we chase high Risk/Reward ratios.) Risk Warning: This strategy is not a "money printer." There will be periods of consecutive stop-losses (whipsaws). This is the "premium" paid to catch the massive trends. It is recommended to allocate only 10%-20% of your total capital. 核心理念： 这不是一个普通的 RSI 或 MACD 拼接指标。 BTC OT 引入了前沿数学工具——最优传输理论 (Optimal Transport Theory)，将比特币的价格波动视为概率分布的“能量传输”问题。 它不预测价格，而是通过计算短期分布与长期基准分布之间的 Wasserstein 距离，精准识别“市场体制 (Market Regime)”的突变。 策略亮点： 数学降维打击： 摒弃滞后的传统指标，直接在概率空间捕捉趋势的起始点。这是对冲基金级别的量化手段，首次下沉到 TradingView 脚本中。 4小时波段猎手 (4H Swing Hunter)： 专为 BTC 4小时 (4H) 周期深度调校。它过滤了日内的随机噪音，拒绝了死拿不动的迟钝，只吃鱼身最肥美的主升浪。 趋势盾牌 (Trend Shield)： 独创的“EMA 双重验证机制”。即使 OT 信号触发，如果价格位于关键均线盾牌之下，策略会拒绝开单。这完美过滤了熊市中的诱多反弹和“死猫跳”。 绝无重绘 (No Repainting)： 基于 process_orders_on_close=true 严格执行。您看到的回测就是真实的信号。所见即所得，绝无马后炮。 历史表现 (2016-2026 回测数据)： 总回报 (Total Return): > 40,000% (400倍收益，大幅跑赢买入持有) 最大回撤 (Max Drawdown): < 50% (在 BTC 这种高波动资产中，这是极佳的风控表现) 盈利因子 (Profit Factor): > 1.45 胜率 (Win Rate): ~38% (趋势策略的典型特征：截断亏损，让利润奔跑。我们不追求高胜率，只追求极高的盈亏比) cn.tradingview.com 风险提示： 本策略非“圣杯”，会有连续止损 (Whipsaw) 的时期。这是捕捉大趋势必须支付的“保险费”。建议仅使用总资金的 10%-20% 进行配置。 如何获取权限： 本脚本为**“仅限邀请 (Invite-Only)”**的私有策略。 订阅方式： 终身买断制 / 年度订阅 联系邮箱： liequanche@gmail.com 邮件标题： TradingView ID + 申请 BTC OT 策略
Стратегия Pine Script®
от liequanche
SPY 200SMA +4% Entry -3% Exit TQQQ/QLD/GLDM THREE PHASE STRATEGYWanted to take a look at all of the individual trades and provide a series of options to balance performance and risk. This post is expanding on my previous one - www.reddit.com Here is the data and the backtesting splitting the strategy into three primary phases with multiple options and exact trade dates to help people easily backtest other combinations - docs.google.com (Three Tabs with the three phases) If you just want my personal recommendations this would be what I will be using - PHASE 1 (Strategy BUY signal triggers when SPY price crosses +4% over the SPY 200SMA) = 100% TQQQ If trade lasts 366 days (Long Term Cap Gains) go to PHASE 2 If SPY price crosses below -3% SPY 200SMA go to PHASE 3 PHASE 2 (PHASE 1 lasts 366 days) = Deleverage and diversify into 50% QLD & 50% GLDM PHASE 3 (Strategy SELL signal triggers when SPY price crosses -3% below the SPY 200SMA) = Defensive posture with 50% SGOV & 50% GLDM As market degrades start selling SGOV and buying QQQ until 50% QQQ & 50% GLDM TradingView Script for the THREE PHASE STRATEGY (imgur.com): // @version= 5 strategy("SPY 200SMA +4% Entry -3% Exit Strategy",      overlay=true,      default_qty_type=strategy.percent_of_equity,      default_qty_value=100) // === Inputs === smaLength      = input.int(200, title="SMA Period", minval=1) entryThreshold = input.float(0.04, title="Entry Threshold (%)", step=0.01) exitThreshold  = input.float(0.03, title="Exit Threshold (%)", step=0.01) startYear      = input.int(1995, "Start Year") startMonth     = input.int(1, "Start Month") startDay       = input.int(1, "Start Day") // === Time filter === startTime    = timestamp(startYear, startMonth, startDay, 0, 0) isAfterStart = time >= startTime // === Calculations === sma200         = ta.sma(close, smaLength) upperThreshold = sma200 * (1 + entryThreshold) lowerThreshold = sma200 * (1 - exitThreshold) // === Strategy Logic === enterLong = close > upperThreshold exitLong  = close < lowerThreshold if isAfterStart     if enterLong and strategy.position_size == 0         strategy.entry("Buy", strategy.long)     if exitLong and strategy.position_size > 0         strategy.close("Buy") // === 366-Day Marker Logic (Uninterrupted) === var int targetTime = na // 1. Capture entry time only when a brand new position starts if strategy.position_size > 0 and strategy.position_size == 0     targetTime := time + (366 * 24 * 60 * 60 * 1000) // 2. IMPORTANT: If position is closed or a sell signal hits, reset the timer to "na" if strategy.position_size == 0     targetTime := na // 3. Trigger only if we are still in the trade and hit the timestamp isAnniversary = not na(targetTime) and time >= targetTime and time < targetTime // === Visuals === p_sma   = plot(sma200, title="200 SMA", color=color.rgb(255, 0, 242)) p_upper = plot(upperThreshold, title="Entry Threshold (+4%)", color=color.rgb(0, 200, 0)) p_lower = plot(lowerThreshold, title="Exit Threshold (-3%)", color=color.rgb(255, 0, 0)) fill(p_sma, p_upper, color=color.new(color.green, 80), title="Entry Zone") // Draw marker only if 366 days passed without a sell if isAnniversary     label.new(bar_index, high, "366 DAYS - PHASE 2", style=label.style_label_down, color=color.yellow, textcolor=color.black, size=size.small) // === Entry/Exit Labels === newOpen  = strategy.position_size > 0 and strategy.position_size == 0 newClose = strategy.position_size == 0 and strategy.position_size > 0 if newOpen     label.new(x=bar_index, y=low * 0.97, text="BUY - PHASE 1", xloc=xloc.bar_index, yloc=yloc.price, color=color.lime, style=label.style_label_up, textcolor=color.black, size=size.small) if newClose     label.new(x=bar_index, y=high * 1.03, text="SELL - PHASE 3", xloc=xloc.bar_index, yloc=yloc.price, color=color.red, style=label.style_label_down, textcolor=color.white, size=size.small) 200 SMA SPY Trading Range Bands Script: // @version= 5 indicator("200 SMA SPY Trading Range Bands", overlay=true) // === Settings === smaLength = input.int(200, title="SMA Length") mult1      = input.float(1.09, title="Multiplier 1 (9% Over)") mult2      = input.float(1.15, title="Multiplier 2 (15% Over)") // === Calculations === smaValue = ta.sma(close, smaLength) line9Over = smaValue * mult1 line15Over = smaValue * mult2 // === Plotting === plot(smaValue, title="200 SMA", color=color.gray, linewidth=1, style=plot.style_linebr) plot(line9Over, title="9% Over 200 SMA", color=color.rgb(255, 145, 0), linewidth=1) plot(line15Over, title="15% Over 200 SMA", color=color.rgb(38, 1, 1), linewidth=2)
Стратегия Pine Script®
от freefighter07
Swing Strategy Feature Set B [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 B includes concepts beginning with the letter "B" 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: Balance of Power Bollinger Bands █   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 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. 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. 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. 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. █   FEATURE SET B 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 Balance of Power (BOP) Filters Minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply above-equal filter is set to false. Above-equal threshold is set to -1. Apply below-equal filter is set to false. Below-equal threshold is set to 1. The BOP 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 BOP trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Due to the way BOP is calculated and the structure of the core entry conditions, basic uptrend and basic downtrend modes are intentionally omitted for the BOP trend filter, as they would be trivially satisfied for long and short entries respectively. Consequently, downtrend evaluation is redundant for long trades and uptrend evaluation is redundant for short trades. Users can apply the BOP filters and adjust filter parameters via strategy Settings/Inputs/BALANCE OF POWER (BOP) FILTERS. Bollinger Bands (BB) Filters The default BB inputs are as follows: Source is set to "Close". Length is set to 20. Standard deviation is set to 2. Users can adjust the BB inputs via strategy Settings/Inputs/BOLLINGER BANDS (BB). The BB bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the upper and lower BB is expanding or contracting over a configurable lookback period. The default BB bandwidth increasing/decreasing filter mode is set to "None". Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each BB (upper, middle, lower). The default mode for all three close above-equal/below BB filters is set to "None". The BB rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined BB is rejected exclusive of the other two BBs. The default BB rejection filter mode is set to "None". 
Users can apply the BB filters and adjust filter parameters via strategy Settings/Inputs/BB 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.
Стратегия Pine Script®
от theEccentricTrader
Trend Aware Smart Strategy (ADX Filter)📘 第一部分：策略核心逻辑解析 这个策略不是传统的“死扛马丁”，它有一个“大脑”（ADX 指标），会根据市场温度改变行为。 1. 两种运行模式（自动切换） • 🌊 震荡整理模式 (Normal Mode) • 触发条件：市场无明显趋势 (ADX < 25)。 • 行为：只要跌了 1.5% 且 RSI 稍微超卖 (<35)，就开始补仓。 • 目的：在横盘震荡中快速低买高卖，赚取波段利润，资金利用率高。 • 🚨 单边暴跌模式 (Crash Mode) • 触发条件：空头力量极强，大瀑布来了 (ADX > 25 且 DI- > DI+)。 • 行为：立刻启动防御。补仓间距自动扩大到 3%~5%，且 RSI 必须极度恐慌 (<20) 才出手。 • 目的：不接第一把飞刀。防止在半山腰把子弹打光，确保接到真正的底部。 2. 逃顶止盈 • 逻辑：当 RSI > 75 且价格突破布林带上轨时，视为行情过热。 • 动作：如果此时账户总体盈利，直接全仓止盈，落袋为安 ⚙️ 第二部分：参数详解与设置建议 在 TradingView 的策略设置界面中，你需要按照以下逻辑进行调整，以确保策略处于最佳防御状态。 A. 💰 核心资金设置 (Money Management) 这部分决定了你的账户能活多久，是风控的基石。 • 模拟杠杆倍数 (Leverage)：建议设置为 3.0 到 5.0。 • 请注意，这个参数主要用于面板上的盈亏计算显示。但在实盘操作中，为了安全起见，绝对不要超过 5 倍杠杆。 • 首单保证金 (Base Margin)：建议严格控制在 总本金的 1%。 • 例如你有 1000 美金，首单就只开 10 美金。起步一定要轻，因为马丁策略的资金大头都在后面的补仓里。 • 马丁补仓倍率 (Martingale Multiplier)：推荐设置为 1.2 到 1.3。 • 这意味着每次补仓的金额只比上一单多一点点（温和递增）。千万不要设置为 2.0（翻倍投），那会让你的资金在几次补仓后迅速耗尽。 • 最大补仓次数 (Max Adds)：建议设置为 8 到 10 次。 • 这是你的“子弹库”。设置 8 次补仓，配合上面的倍率，足够覆盖市场约 40%-50% 的极端跌幅。 B. 🧠 趋势感知设置 (The Brain) 这部分决定了策略有多“聪明”，能否识别暴跌。 • ADX 阈值 (ADX Threshold)：推荐设置为 25。 • 这是判断“震荡”还是“单边”的分界线。数值越高，触发防御模式越难。25 是一个经典的趋势分界值。 • 单边防御系数 (Trend Multiplier)：这是最核心的风控参数，建议设置为 2.0 到 2.5。 • 它的意思是：当系统检测到暴跌时，补仓的间距要扩大多少倍？如果你设为 2.0，原本跌 1.5% 就买的，现在要跌 3.0% 才肯买。这能有效防止在暴跌途中过早接飞刀。 • RSI 阈值设定： • 震荡市 RSI：建议设为 35。在普通行情下，稍微跌一点（超卖）就开始建仓套利。 • 单边市 RSI (恐慌阈值)：建议降至 20。在暴跌模式下，必须等到市场极度恐慌、指标严重超卖时才出手抄底。 • 震荡市最小间距 (Min Drop)：建议设为 1.5% 到 2.0%。 • 这是为了防止在同一个价格附近重复买入。只有价格至少跌了这么多，系统才会开始检测是否需要补仓。 🎮 第三部分：实战玩法与风控指南 1. 资金配置作业 (以 1000U 本金为例) 这是为了保证 不爆仓、不深套 的稳健配置： • 交易对：ETH/USDT 或 BTC/USDT (严禁操作山寨币/Meme币)。 • 时间周期：15分钟图 (15m) (最适合 ADX 过滤震荡和趋势)。 • 首单：10 U (1%)。 • 补仓倍数：1.2。 • 最大补仓：8 次。 • 杠杆：3x (最高不要超过 5x)。 2. 如何看懂 UI 仪表盘 (Dashboard) 代码右上角的面板是你驾驶策略的仪表盘： • 市场状态： • 🌊 震荡整理：安心睡觉，策略在帮你刷单。 • 🚨 单边暴跌：警惕。此时策略会停止频繁买入，你会发现很久才成交一单，这是正常的防御表现。 • 下次补仓需： • 显示 跌 3.0% & RSI < 20：说明策略正在等待暴跌到位，不要手动干预去买，相信策略的耐心。 • 浮动盈亏： • 如果是 绿色：随时可以手动平仓吃肉。 • 如果是 红色：只要不超过 -20% (200U)，都属于安全范围。 3. “装死”与“逃生”技巧 • 情况一：被套 10% 左右 • 操作：什么都不用做。等待 RSI 触及 75 或价格反弹，策略会自动止盈。 • 情况二：遇到史诗级黑天鹅 (如 ETH 一天跌 30%) • 操作：观察面板上的 “浮动盈亏”。如果接近你心理承受极限 (如 -300U)，且市场还没有止跌迹象，可以手动点击 TradingView 的 "Close All Positions" 认赔离场，保住剩下的本金。 • 但在本策略逻辑下：由于暴跌时它会拉大补仓间距（防御系数），通常能抗住 40%-50% 的跌幅而不爆仓。 4. 进阶：如何扩大利润？ 如果你发现策略太保守，几个月都没怎么亏钱但赚得少，可以微调： • 将 震荡市 RSI 阈值 从 35 提高到 40 (增加出手频率)。 • 将 震荡市最小间距 从 1.5% 降低到 1.0% (更密集的网格)。 • 前提：必须保持 ADX 和 单边防御系数 不变，确保暴跌时的安全底裤还在。 📝 总结 这个脚本是一个 “聪明”的网格马丁。 • 它的优点：在 80% 的震荡行情里赚钱，在 20% 的暴跌行情里少亏或抄到底部。 • 它的底线：不要在高位梭哈，不要开高倍杠杆。严格执行 1% 首仓 + 3倍杠杆，这套策略能成为你非常稳定的现金流工具。 ### 📝 Strategy Introduction This script is an advanced Martingale strategy equipped with a "Trend-Aware" brain using the **ADX (Average Directional Index)**. Unlike traditional Martingale strategies that blindly buy during a crash, this script distinguishes between **Sideways Markets** and **Trend Crashes**, automatically switching between "Offensive" and "Defensive" modes to protect your capital. ### 🧠 Core Logic **1. 🌊 Sideways Mode (Normal)** * **Condition:** ADX < 25 (Market has no strong trend). * **Behavior:** The strategy trades actively with smaller grid spacing and higher RSI thresholds to capture profits from volatility. **2. 🚨 Crash Mode (Defensive)** * **Condition:** ADX > 25 (Strong trend detected) AND Bearish momentum. * **Behavior:** A defensive mechanism is triggered. The grid spacing (drop requirement) is automatically widened by a factor (e.g., 2.0x), and the RSI threshold is lowered (e.g., < 20). * **Goal:** To avoid catching falling knives too early and aim for the true market bottom. ### 🎨 Key Features * **Professional Dashboard:** A UI panel displaying real-time leverage, PnL (USDT & %), Market Status (Sideways/Crash), and the next buy condition. * **Smart Take Profit:** Uses RSI Overbought + Bollinger Bands Upper Breakout to exit positions dynamically at the top. ### 🛡️ Risk Management (Crucial) To use this strategy safely, please strictly follow these settings: 1. **Initial Capital:** Use only **1%** of your total account for the first order. 2. **Leverage:** Keep it under **3x - 5x**. 3. **Multiplier:** Recommended **1.2 - 1.3** (Do not use 2.0). --- ### ⚠️ Disclaimer This script is for quantitative research and educational purposes only. Martingale strategies involve high risk, especially in extreme market conditions. Please backtest thoroughly and use at your own risk. ----------------------------------------- (以下为中文说明 / Chinese Translation) **策略简介** 这是一个拥有趋势感知能力的智能马丁策略。通过 ADX 指标，它能识别“震荡”与“暴跌”，拒绝在单边下跌中过早接飞刀。 **核心逻辑** 1. **震荡模式**：当 ADX < 25 时，采用小间距积极套利。 2. **暴跌模式**：当 ADX > 25 且行情剧烈下跌时，触发防御机制，自动拉大补仓间距，只在极值位抄底。 **风控建议** 请严格遵守：首仓仅投入 1% 本金，杠杆不超过 5 倍。
Стратегия Pine Script®
от dartf5
Etherium 4H backtester&strategy&signal ALPHAThis is a comprehensive 4-hour trend-following strategy designed specifically for Ethereum (ETHUSDT), optimized for long-term growth and drawdown protection. 1. Hybrid Trend Filter: Combines Trend Magic (CCI+ATR) and ZLSMA (Zero-Lag LSMA) to identify the true market direction with minimal lag. 2. Volatility Squeeze: Uses TTM Squeeze logic (Bollinger Bands inside Keltner Channels) to enter trades only when volatility expands. 3. Daily Regime Filter: Checks the Daily 200 EMA to ensure trades align with the macro trend (Longs only in Bull markets, Shorts only in Bear markets). 1. Dynamic Stop Loss: Utilizes a "Smart" Stop Loss system that automatically selects the tighter stop between ATR Chandelier and Recent Swing High/Low. 2. Equity Guard: A unique feature that reduces position size by 50% when the current equity falls below its moving average, protecting the account during drawdown periods. 1. Timeframe: 4 Hours (Recommended) 2. Symbol: ETHUSDT.P (Binance/Bybit Perpetual) 3. Settings: All parameters (Risk, Filters, SL Mode) are fully customizable in the settings menu. This script does not guarantee future profits. Past performance is not indicative of future results. Use at your own risk. To access this script, please check the link in my signature or profile status.
Стратегия Pine Script®
от GODSTARY
Speed Coding BTC Pro SystemSpeed Coding BTC Pro System is an advanced TradingView automation strategy designed for Bitcoin trading. It sends Buy/Sell signals automatically from TradingView to your exchange or trading bot using Webhook API integration. To activate automation, the client only needs to fill in the following 4 inputs: ⸻ 1) Apikey The Apikey is your unique security key used to authorize and connect the strategy with your automation system or trading bot. ✅ What to enter: • Paste the API Key provided by your trading bridge / bot / automation panel. ⚠️ Important: • Do not share your API key with anyone. • Incorrect API key will stop order execution. ⸻ 2) Symbol The Symbol defines which trading pair or instrument the automation will trade. ✅ Examples (depends on exchange format): • BTCUSDT • BTCUSD • BTCUSDT.P • XBTUSD 📌 Note: Always enter the exact symbol name supported by your exchange or automation bridge. ⸻ 3) Strategy Tag The Strategy Tag is a label used to identify this strategy’s signals inside your automation system. It helps manage multiple strategies or multiple client accounts easily. ✅ Recommended Tags: • SC_BTC_PRO • SPEED_BTC_SYSTEM • SCALP_BTC_PRO • SPEEDCODING_BTC 📌 Best Practice: Keep the same tag for one client to maintain clean tracking. ⸻ 4) Qty The Qty defines the order size or trade quantity. ✅ Example: • 0.01 BTC (as shown in your settings) ⚠️ Note: Quantity depends on account balance and exchange minimum order rules. ✅ How Automation Works 1. The strategy generates a Buy/Sell or Long/Short signal on TradingView 2. TradingView sends the signal through Webhook Alert 3. Your connected bot/bridge receives the message 4. Orders are placed automatically on the exchange ⸻ ✅ Client Safety Recommendations • Always test in Demo/Paper Trading first • Confirm correct Symbol and Qty before live trading • Run one test alert to verify webhook connection
Стратегия Pine Script®
от Speed_Coding_infotech
Gennie_V8_ProGennie V8 Pro is a premium trend-following strategy designed specifically for Crypto Perpetual markets. It utilizes institutional-grade data points to identify high-probability setups through price action and order flow confluence. Key Features: Institutional Order Flow: Combines FVG (Fair Value Gap) and CVD (Cumulative Volume Delta) to track big player movements. OI Momentum Filter: Analyzes Open Interest growth to ensure trend validity and avoid "liquidation traps." Volatility-Adaptive Exit: Uses ATR (Average True Range) for stop-loss calculation, adapting to market conditions. Smart Risk Management: Features a two-stage Take Profit (TP) system with an automated Break-Even (BE) trigger after TP1 is reached. Strict No-Repaint Execution: This strategy is built with process_orders_on_close = true. Signals are calculated at the bar close and executed on the next bar open. Backtest results are 100% realistic and reliable for live trading.
Стратегия Pine Script®
от jac888178
4
Swing Strategy Feature Set A [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 A includes concepts beginning with the letter "A" 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: Accumulation/Distribution Arnaud Legoux Moving Average Aroon Average True Range Awesome 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 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. 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. 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. 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. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred oscillator 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. █   FEATURE SET A 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 Accumulation/Distribution (AD) Filters The AD 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 AD 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 AD filters and adjust filter parameters via strategy Settings/Inputs/Accumulation/Distribution (AD) Filters. Arnaud Legoux Moving Average (ALMA) Filters Users can define up to three independent ALMA series. The defaults are as follows: ALMA 1: source = close, length = 50, offset = 0.85, sigma = 6.0, floor = false. ALMA 2: source = close, length = 100, offset = 0.85, sigma = 6.0, floor = false. ALMA 3: source = close, length = 200, offset = 0.85, sigma = 6.0, floor = false. Users can adjust ALMA inputs via strategy Settings/Inputs/Arnaud Legoux Moving Average (ALMA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined ALMA. The default mode for all three ALMA close above-equal/below filters is set to "None". Users can apply up to three independent ALMA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: ALMA 1 above-equal/below ALMA 2 is set to "None". ALMA 2 above-equal/below ALMA 3 is set to "None". ALMA 1 above-equal/below ALMA 3 is set to "None". The ALMA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined ALMA is rejected exclusive of the other two ALMAs. The default ALMA rejection filter mode is set to "None". 
Users can apply the ALMA filters and adjust filter parameters via strategy Settings/Inputs/ALMA Filters. Aroon Filters The default Aroon length is set to 14. Users can adjust the Aroon length via strategy Settings/Inputs/Aroon.
 Minimum and maximum boundary filters (see generic filters section above) are included for both Aroon up and Aroon down values, the defaults are as follows: Apply Aroon up above-equal is set to false Aroon up above-equal threshold is set to 0%. Apply Aroon up below is set to false Aroon up below threshold is set to 100%. Apply Aroon down above-equal is set to false Aroon down above-equal threshold is set to 0%. Apply Aroon down below is set to false Aroon down below threshold is set to 100%. Users can apply the Aroon filters and adjust filter parameters via strategy Settings/Inputs/Aroon Filters. Average True Range (ATR) Filters The default ATR length is set to 14. Users can adjust the ATR length via strategy Settings/Inputs/Average True Range (ATR).
 The risk range above-equal/below ATR filter is defined as an entry filter that evaluates the trade's risk range (evaluated independently for long and short risk ranges) relative to ATR and invalidates trade signals that do not satisfy the user-defined directional condition. The default risk range above-equal/below ATR filter mode is set to "None". The ATR 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 ATR 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 ATR filters and adjust filter parameters via strategy Settings/Inputs/ATR Filters. Awesome Oscillator (AO) Filters The default AO inputs are as follows: Source is set to hl2. Short length is set to 5 Long length is set to 34. Users can adjust the AO inputs via strategy Settings/Inputs/Awesome Oscillator (AO).
 The AO calculations used in this script will vary from those used in the built-in TradingView indicator if the user adjusts the default settings. That is because the built-in TradingView indicator uses fixed parameters, while this script allows users to select their own source, short length and long length. Users can build their own AO indicator with custom parameters in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Awesome Oscillator", shorttitle = "AO", overlay = false) import TradingView/ta/12 as ta ao_source = input.source(defval = hl2, title = "AO Source", group = "Awesome Oscillator (AO)") ao_short_length = input.int(defval = 5, title = "AO Short Length", minval = 1, group = "Awesome Oscillator (AO)") ao_long_length = input.int(defval = 34, title = "AO Long Length", minval = 1, group = "Awesome Oscillator (AO)") ao = ta.ao(ao_source, ao_short_length, ao_long_length) diff = ao - ao plot(ao, "AO", color = diff <= 0 ? #F44336 : #009688, style = plot.style_columns) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The default AO above-equal/below zero filter mode is set to "None". The AO 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 AO 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 AO filters and adjust filter parameters via strategy Settings/Inputs/AO 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.
Стратегия Pine Script®
от theEccentricTrader
Pitchfork Long Strat x Mizar🎯 Advanced DCA Strategy with Nadaraya-Watson Envelope for Mizar Integration This strategy combines the sophisticated Nadaraya-Watson kernel regression indicator with an intelligent DCA (Dollar Cost Averaging) system, specifically designed for automated trading via Mizar webhooks. ═══════════════════════════════════════════════════════════ 📊 KEY FEATURES ✓ Nadaraya-Watson Envelope Indicator - Adaptive regression bands that follow price trends - ATR-based dynamic upper/lower bands - Customizable lookback windows and weighting ✓ Intelligent DCA System - Exponential scaling of price thresholds (default 1.9x per level) - Exponential scaling of order sizes (default 1.6x per level) - Up to 20 configurable safety orders - Minimum bars between orders to avoid overtrading - Tracks average entry price across all orders ✓ Flexible Stop Loss Options - Percentage-based stop loss - ATR-based dynamic stop loss - Always calculated from average entry price ✓ Optional Trailing Buy - Separate settings for initial entry and DCA orders - Helps capture better entry prices during pullbacks ✓ Full Mizar Integration - Pre-configured webhook messages for all actions - Automatic base asset extraction from ticker - Separate TP settings for backtesting vs. live trading - Supports open position, activate safety orders, edit TP, and close position ✓ Professional Backtesting - Real-time position tracking with visual entry/exit labels - Info table showing avg entry, TP, SL, and P&L - Tracks average bars in winning trades for optimization - Commission-inclusive (0.06% default) ═══════════════════════════════════════════════════════════ 🎲 HOW IT WORKS ENTRY SIGNAL: - Triggers when price crosses above the lower Nadaraya-Watson band - First order: Fixed size (default $10 USDT) - Subsequent DCA orders: Exponentially scaled based on your settings DCA LOGIC: - Each safety order requires price to drop by an exponentially growing percentage - Example with 2.1% base deviation and 1.9x scale: • Order 1: Initial entry • Order 2: -2.1% from Order 1 • Order 3: -3.99% from Order 2 (2.1% × 1.9) • Order 4: -7.58% from Order 3 (2.1% × 1.9²) • And so on... EXIT SIGNALS: - Take Profit: Fixed percentage above average entry - Stop Loss: Percentage or ATR-based below average entry ═══════════════════════════════════════════════════════════ ⚙️ RECOMMENDED SETTINGS For BTC/ETH (Lower Volatility): - DCA Price Deviation: 2.0-2.5% - DCA Step Scale: 1.8-2.0 - DCA Volume Scale: 1.5-1.7 - Max Safety Orders: 4-6 - Stop Loss: 30-40% For Altcoins (Higher Volatility): - DCA Price Deviation: 2.5-3.5% - DCA Step Scale: 1.9-2.2 - DCA Volume Scale: 1.6-1.9 - Max Safety Orders: 5-8 - Stop Loss: 40-60% ═══════════════════════════════════════════════════════════ 🔗 MIZAR SETUP 1. Create a DCA bot on Mizar 2. Copy your Bot ID and API Key 3. Enter them in the "Mizar Webhook" settings 4. Set your Quote Asset (USDC/USDT) 5. Create alert with webhook URL: api.mizar.com 6. Set alert message to {{strategy.order.alert_message}} 7. Make sure "Webhook URL" option is checked ═══════════════════════════════════════════════════════════ ⚠️ IMPORTANT NOTES - This is a LONG ONLY strategy - Always backtest on your specific asset/timeframe before going live - Start with conservative settings and adjust based on results - Monitor your "Avg Bars in Winning Trades" to optimize entry/exit - The strategy calculates all percentages from your average entry price - Recommended timeframes: 15m, 1h, 4h (avoid < 5m due to noise) ═══════════════════════════════════════════════════════════ 📈 IDEAL FOR - Cryptocurrency spot trading - Medium to long-term position building - Automated trading via Mizar - Bull market accumulation strategies - Traders who want to average into positions systematically ═══════════════════════════════════════════════════════════ 💡 TIPS FOR SUCCESS 1. Use higher timeframes for more reliable signals 2. Adjust ATR multiplier based on asset volatility 3. Keep total position size (all DCA orders) within risk tolerance 4. Monitor the "Position Value" in the info table 5. Consider market conditions when setting TP/SL levels ═══════════════════════════════════════════════════════════ Created by Pitchfork| Modified for Mizar DCA Integration For questions or support, please comment below! #Mizar #DCA #NadarayaWatson #CryptoStrategy #AutomatedTrading
Стратегия Pine Script®
от baslambo
PRO Investing - AlphaCentauri D |SLV|PRO Investing – AlphaCentauri D | SLV | 1. Summary and Core Concept AlphaCentauri is a quantitative backtesting strategy engineered specifically for SLV (iShares Silver Trust ETF) on the Daily (1D) timeframe. Its objective is to systematically extract alpha by identifying statistically significant trading opportunities through rigorous time-series analysis. Rather than relying on conventional technical indicators, the strategy focuses on the structural behavior of price action, targeting market conditions that have historically preceded sustained directional trends in the silver market. 2. The Analytical Process: How It Works AlphaCentauri employs a multi-stage quantitative framework designed to isolate high-probability trading environments. It combines statistical pattern recognition with confirmation logic applied directly to SLV price data. Structural Pattern Recognition The engine analyzes historical SLV price series to detect recurring structural formations, geometric configurations, and cyclical behaviors that tend to emerge ahead of persistent trend development in silver prices. Signal Validation and Execution Trade signals are generated only when multiple independent analytical layers align. Structural conditions must be confirmed by secondary quantitative checks before a position is initiated. This disciplined approach keeps the strategy flat during non-trending or volatile regimes and engages exposure only when quantitative confidence is high. 3. How to Use This Strategy Timeframe and Asset Specificity AlphaCentauri has been designed, tested, and optimized exclusively for SLV on the Daily (1D) timeframe. Its logic is not intended for other assets or intraday timeframes and may produce unreliable results if applied outside its intended scope. On-Chart Transparency All historical trade entries and exits are plotted directly on the chart, providing full transparency for performance evaluation, drawdown analysis, and regime assessment across different market conditions. 4. Risk Management: The Strategy’s Foundation Risk management is embedded at the core of AlphaCentauri’s design and is fully reflected in both execution logic and backtesting parameters, in alignment with TradingView’s standards for realistic and responsible strategy publication. Dynamic Stop-Loss and Position Sizing Each trade employs a dynamically calculated stop-loss based on recent market volatility. Position size is automatically adjusted to target a predefined risk percentage per trade. During periods of elevated volatility, the maximum potential loss on a single position may approach, but is designed not to exceed 7% of total account equity. Under normal market conditions, realized risk typically remains well below this limit. Realistic Backtesting Parameters Initial Capital: $100,000 Commission: $5.00 per order to reflect realistic transaction costs 5. Disclaimer For institutional research and quantitative strategy validation only. This is not investment advice. Trading silver via SLV involves material risk, including precious metal price volatility, liquidity shifts, and macroeconomic events. Past performance does not guarantee future results. All live deployment and capital allocation decisions remain the sole responsibility of the user or institution.
Стратегия Pine Script®
от PRO-Investing
PRO Investing - AlphaCentauri D |WEAT|PRO Investing – AlphaCentauri D | WEAT | 1. Summary and Core Concept AlphaCentauri is a quantitative backtesting strategy engineered specifically for the Teucrium Wheat Fund (WEAT) on the Daily (1D) timeframe. Its objective is to systematically extract alpha by identifying statistically significant trading opportunities through rigorous time-series analysis applied to agricultural commodity price dynamics. Rather than relying on conventional technical indicators, the strategy focuses on the structural behavior of price action, targeting market conditions that have historically preceded sustained directional trends in wheat prices and related futures exposure. 2. The Analytical Process: How It Works AlphaCentauri employs a multi-stage quantitative framework designed to isolate high-probability trading environments. It combines statistical pattern recognition with confirmation logic applied directly to WEAT price data. Structural Pattern Recognition The core engine analyzes historical WEAT price series to detect recurring structural formations, geometric configurations, and cyclical behaviors that tend to emerge ahead of persistent trend development in agricultural commodities, particularly during supply, demand, and weather-driven regime shifts. Signal Validation and Execution Trade signals are generated only when multiple independent analytical layers align. Structural conditions must be confirmed by secondary quantitative checks before a position is initiated. This disciplined approach keeps the strategy flat during range-bound or noisy regimes and engages exposure only when quantitative confidence is high. 3. How to Use This Strategy Timeframe and Asset Specificity AlphaCentauri has been designed, tested, and optimized exclusively for WEAT on the Daily (1D) timeframe. Its logic is not intended for other assets or intraday timeframes and may produce unreliable results if applied outside its intended scope. On-Chart Transparency All historical trade entries and exits are plotted directly on the chart, providing full transparency for performance evaluation, drawdown analysis, and regime assessment across different commodity market environments. 4. Risk Management: The Strategy’s Foundation Risk management is embedded at the core of AlphaCentauri’s design and is fully reflected in both execution logic and backtesting parameters, in alignment with TradingView’s standards for realistic and responsible strategy publication. Dynamic Stop-Loss and Position Sizing Each trade employs a dynamically calculated stop-loss based on recent market volatility. Position size is automatically adjusted to target a predefined risk percentage per trade. During periods of elevated volatility, the maximum potential loss on a single position may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, realized risk typically remains well below this limit. Realistic Backtesting Parameters Initial Capital: $100,000 Commission: $5.00 per order to reflect realistic transaction costs 5. Disclaimer For institutional research and quantitative strategy validation only. This is not investment advice. Trading commodity-linked ETFs involves material risk, including futures curve effects, weather-driven supply shocks, geopolitical disruptions, and volatility regime changes. Past performance does not guarantee future results. All live deployment and capital allocation decisions remain the sole responsibility of the user or institution.
Стратегия Pine Script®
от PRO-Investing
PRO Investing - AlphaCentauri D |ILF|PRO Investing – AlphaCentauri D | ILF | 1. Summary and Core Concept AlphaCentauri is a quantitative backtesting strategy engineered specifically for the iShares Latin America 40 ETF (ILF) on the Daily (1D) timeframe. Its objective is to systematically extract alpha by identifying statistically significant trading opportunities through rigorous time-series analysis. Rather than relying on traditional technical indicators, the strategy focuses on the structural behavior of price action, targeting market conditions that have historically preceded sustained directional trends across major Latin American equity markets. 2. The Analytical Process: How It Works AlphaCentauri employs a multi-stage quantitative framework designed to isolate high-probability trading environments. It combines statistical pattern recognition with confirmation logic applied directly to ILF price data. Structural Pattern Recognition The core engine analyzes historical ILF price series to detect recurring structural formations, geometric configurations, and cyclical behaviors that tend to emerge ahead of persistent trend development in Latin American equities. Signal Validation and Execution Trade signals are generated only when multiple independent analytical layers align. Structural conditions must be confirmed by secondary quantitative checks before a position is initiated. This disciplined approach keeps the strategy flat during non-directional, unstable, or politically driven regimes and engages exposure only when quantitative confidence is high. 3. How to Use This Strategy Timeframe and Asset Specificity AlphaCentauri has been designed, tested, and optimized exclusively for ILF on the Daily (1D) timeframe. Its logic is not intended for other ETFs, assets, or intraday timeframes and may produce unreliable results if applied outside its intended scope. On-Chart Transparency All historical trade entries and exits are plotted directly on the chart, providing full transparency for performance evaluation, drawdown analysis, and regime assessment across varying macro and regional market conditions. 4. Risk Management: The Strategy’s Foundation Risk management is embedded at the core of AlphaCentauri’s design and is fully reflected in both execution logic and backtesting parameters, in alignment with TradingView’s standards for realistic and responsible strategy publication. Dynamic Stop-Loss and Position Sizing Each trade employs a dynamically calculated stop-loss based on recent market volatility. Position size is automatically adjusted to target a predefined risk percentage per trade. During periods of elevated volatility or macro stress, the maximum potential loss on a single position may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, realized risk typically remains well below this limit. Realistic Backtesting Parameters Initial Capital: $100,000 Commission: $5.00 per order to reflect realistic transaction costs 5. Disclaimer For institutional research and quantitative strategy validation only. This is not investment advice. Trading emerging market and regional equity ETFs involves material risk, including political risk, currency volatility, liquidity constraints, and regime shifts. Past performance does not guarantee future results. All live deployment and capital allocation decisions remain the sole responsibility of the user or institution.
Стратегия Pine Script®
от PRO-Investing
Logit Alpha Ranker For BTCThe ORLA Ranker is a "Fat-Tail" strategy. It is designed to ignore noise and only participate in high-probability, high-conviction trends. Its ability to achieve a 3.8+ Profit Factor on BTC suggests that the Logit model effectively filters out the volatility "churn" that kills most retail trend-following scripts. Efficiency: The strategy is highly selective, with only 66 trades over nearly a decade. This low frequency minimizes commission drag and slippage.
Стратегия Pine Script®
от ycloudyu