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1-BTCUSD

Astra X v1 Multi-Timeframe Trend Strategy with ATR TP/SL This strategy is built around trend confirmation across multiple higher timeframes, combined with volatility-based risk management. The main idea is simple: Only trade when multiple timeframes agree on direction, and Let ATR decide take-profit and stop-loss instead of fixed percentages. Strategy Concept Instead of relying on a single indicator or timeframe, Astra X stacks confirmations from 1H to 1D to filter out noise and low-quality trades. It is designed to: Capture medium to long trend moves Reduce overtrading Adapt exits to market volatility Entry Logic (High Level) A trade is triggered when one of several predefined conditions is met. Each condition represents a different trend or momentum structure, such as: EMA crossovers on 6H, 8H, and Daily Trend strength using ADX Momentum confirmation using RSI and TSI Volatility context using Keltner Channels Both long and short signals are supported, depending on the condition. Only one position is allowed at a time. Exit Logic There are two exit layers: ATR-based take profit and stop loss Take profit = ATR × multiplier Stop loss = ATR × multiplier Uses 1H ATR so exits adapt to current volatility Early exit signal If the original entry condition is invalidated The position is closed immediately This helps protect profits when the trend structure breaks early. Risk and Position Sizing Position size is based on account equity Optional leverage support Percentage-based execution model Alert-ready for automation Notes Uses higher timeframe data with lookahead for strategy logic Focused on trend continuation, not scalping Best suited for BTC and high-liquidity markets Final Thoughts Astra X does not aim to predict tops or bottoms. It focuses on aligning with the dominant trend, managing risk dynamically, and letting volatility define exits. Not financial advice. Always backtest before live trading.
Pine Script®策略
由nol-quant提供
BTC Volatility Aligned Momentum EngineTitle BTC Volatility Aligned Momentum Engine Version and compatibility Pine Script v6 All request.security calls use lookahead off Strategy execution uses standard candles only Signals can update intrabar and settle on close. For conservative workflows, evaluate on bar close Summary in one paragraph BTC Volatility Aligned Momentum Engine is a daily first strategy built for liquid crypto, with BTC in mind. It only participates when three independent layers agree: directional state, structural location, and momentum phase. The novelty is not a random stack of indicators, it is a small decision engine that treats momentum as a regime variable and volatility as the unit of risk, so stops and targets scale with the market rather than staying static. Scope and intent Markets. Liquid crypto pairs, then liquid indices and FX as secondary use Timeframes. Intraday through daily. Defaults are tuned for BTC 1D behavior and weekly volatility scaling Purpose. Filter low quality participation by requiring alignment of state, structure, and phase instead of reacting to one signal Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness This is designed as a compact regime filter, not a mashup. Each component solves a different failure mode and the entry requires agreement, not majority voting. Unique concept or fusion. A three layer gate that separates direction from structure and then confirms with momentum phase, while risk is expressed in weekly ATR units What failure mode it addresses. Trend filters often enter during late stage drift or chop. Here, the histogram slope is treated as a phase constraint, meaning entries are biased toward continuation when momentum is still improving in the chosen direction Testability. Inputs map directly to the decision layers, so you can stress test each layer independently without touching the rest Portable yardstick. Weekly ATR is used as a volatility denominator for risk distances, which reduces the common issue of fixed stops becoming too tight in expansion and too wide in contraction Protected scripts. The implementation is kept private to prevent cloning of the execution details, while the full method, assumptions, and reproduction settings are disclosed so users can evaluate it transparently Method overview in plain language Base measures Structural location. Price is evaluated relative to an EMA rail, acting as a simple market structure proxy Directional state. Heikin Ashi candles are used only as a state filter to reduce noisy flips. Execution is still done on standard candles Momentum phase. A MACD style histogram with an Internal HA calculation is computed and compared to its prior value. The model reads this as phase acceleration or deceleration rather than absolute level Volatility unit. Weekly ATR defines the distance unit used for stop and target placement Components State Gate. Heikin Ashi open and close define a bias state. This is not used for prices, only to avoid trading against the immediate directional state Structural Rail. A primary EMA defines whether price is operating above or below the model reference structure Phase Gradient. The histogram slope acts like a gradient test. Longs require improving momentum, shorts require deteriorating momentum. This avoids the classic issue where an oscillator can remain positive while momentum is already fading Weekly Volatility Engine. ATR is sampled on weekly timeframe and used as an adaptive risk ruler. Stops and targets are expressed as ATR multiples rather than fixed points Fusion rule This is a strict gate, not a score. All required conditions must be true. Directional state must agree with the trade direction Price must be on the correct side of the structural rail for longs Momentum phase must be improving for longs and deteriorating for shorts Risk distances use weekly volatility scaling when enabled Signal rule Long entry appears when the HA state is bullish, close is above the primary EMA rail, and the histogram is rising versus the prior bar Short entry appears when the HA state is bearish, price crosses under the short trigger EMA, and the histogram is falling versus the prior bar Long exit appears when close drops below the exit rail EMA Inputs with guidance Execution Control Allowed Direction. Both, Long Only, Short Only. Useful for regime isolation and research without changing the core model Enable ATR Risk Engine. On places ATR stop and target orders. Off disables those orders so you can evaluate pure signal exits Quantum MACD Engine Signal Source. Default close Impulse Length. Typical 8 to 20. Higher means fewer, slower phase changes Inertia Length. Typical 18 to 40. Higher means less sensitivity to short bursts Phase Sync Length. Typical 5 to 14. Higher reduces false phase flips but adds lag Oscillator Kernel and Signal Kernel. EMA reacts faster, SMA is smoother. Mixing kernels changes the histogram texture and can materially change frequency Trend Rails Primary Rail Length. Higher reduces churn and increases trend selectivity Cross Trigger Length. Short side sensitivity. Lower increases short triggers, higher filters them Exit Rail Length. Controls long exit responsiveness Volatility Risk Engine ATR Sample Length. Weekly ATR smoothing. Higher stabilizes risk unit Loss Guard ATR Mult. Stop distance in volatility units. Typical 1.0 to 3.0 Profit Guard ATR Mult. Target distance in volatility units. Typical 1.0 to 4.0 Usage recipes BTC daily core Chart BTC 1D Allowed Direction Both ATR Risk Engine On Defaults for rails and MACD engine Directional research Allowed Direction Long Only, then Short Only Keep everything else unchanged and compare drawdown behavior across regimes Lower frequency swing Increase Primary Rail Length Increase Phase Sync Length Use a slightly higher Profit Guard ATR Mult while keeping stop conservative Properties visible in this publication Initial capital 10000 Order sizing percent of equity with value 5 Pyramiding 1 Commission 0.1 percent per side, round turn is two sides Slippage 10 ticks Process orders on close ON Bar magnifier ON Recalculate after order is filled OFF Calc on every tick OFF All request.security calls use lookahead off Realism and responsible publication No performance claims. Past results do not imply future results BTC can gap and liquidity can thin. Slippage and fills vary by venue and regime If both stop and target can be hit within one bar, TradingView engine sequencing applies. Interpret single bar outcomes cautiously This strategy is designed for standard candles and does not claim realistic execution on non standard chart types Honest limitations and failure modes Fast volatility shocks can invalidate weekly ATR as a risk ruler for several bars Choppy ranges can produce alternating state and phase signals, increasing churn Short logic is structurally different from long logic by design, so symmetry should not be assumed across all regimes Parameter changes can materially alter behavior. Treat this as a framework and test on out of sample windows Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs. Strategy notice Orders are simulated by the TradingView engine on standard candles. request.security uses lookahead off everywhere. Non standard chart types are not supported for strategies. Entries and exits Entry logic. Long when directional state is bullish, price is above the primary EMA rail, and momentum phase is improving. Short when directional state is bearish, price crosses under the short trigger EMA, and momentum phase is deteriorating Exit logic. Long exits when price drops below the exit rail. ATR stops and targets can be enabled or disabled via inputs Risk model. Weekly ATR multiple stop and take profit when enabled Tie handling. If stop and target are both hit in the same bar, TradingView bar resolution rules apply under the chosen magnifier settings
Pine Script®策略
由exlux提供
BTC 4H Sharpe ratio: 1.57Backtesting Data Conclusions: Backtesting Period: March 3, 2020 – February 4, 2026 Initial Capital: 1000 USDT Net Profit: +157,717.59 USDT (approximately +15,771.76%) Buy & Hold Return: +9,590.26 USDT (approximately +959.03%) → The strategy significantly outperformed buy & hold (during the same period). Maximum Equity Drawdown: 6,671.78 USDT (7.94%) → The drawdown level is relatively mild for this type of high-frequency/scalping strategy, indicating that the overall equity curve is relatively smooth. Profit Factor: 2.083 Sharpe Ratio: 1.547 Total Trades: 1446 Win Rate: 83.75% (1211 profitable trades / 235 losing trades) Net Profit from Long Positions: +76,605.15; Net Profit from Short Positions: +81,112.45 → Profitable on both long and short positions, with a slightly larger contribution from short positions. Suggested Trading Timeframe: 4H BTC Sharpe Ratio Test: 1.5747 ETH Sharpe Ratio Test: 1.0 SOL Sharpe Ratio Test: 1.093 XRP Sharpe Ratio Test: 1.11 Suggested Leverage: 4-5x Trading Instruments: BTC, ETH, SOL, XRP
Pine Script®策略
由w919339492提供
4
CTAY Hive Worker 3.3 ProfessionalCTAY Hive Worker 3.3 Professional Intelligent DCA Strategy for Structured, Rule-Based Trading The CTAY Hive Worker 3.3 Professional is an advanced TradingView strategy designed for systematic, transparent, and fully deterministic trading. It combines RSI-based logic, multi-timeframe analysis, and sophisticated DCA and budget management to deliver controlled and reproducible trading behavior. This strategy is built for traders who value clarity, consistency, and risk awareness over black-box automation — both in backtesting and live operation. Key Features: Intelligent RSI-Based Entries • Configurable RSI entry logic • Optional Median-RSI filtering to reduce market noise • Supports both rebound-based and trend-continuation setups Multi-Timeframe Architecture (MTF) • Independent timeframes for entries, filters, and trend evaluation • Automatic validation to prevent indicators from running below chart timeframe • Full synchronization between chart, strategy logic, and alerts Advanced DCA Management • Multi-level safety orders with linear or geometric spacing • Clear separation of base investment, DCA budget, and reinvest budgets • Dynamic safeguards to prevent over-allocation Reinvest & Capital Flow Logic • Optional reinvestment of profits • Separate handling of bot capital, order reinvestment, and savings • Full transparency of all internal capital movements Exit & Take-Profit Logic • Fixed Take-Profit • Optional Trailing Take-Profit • Cycle-based exit logic for clean and traceable trade closures Trend & Market Filters • Optional trend filters (e.g. SuperTrend) • Independent logic for uptrend and downtrend phases • Helps avoid trades against dominant market conditions Deterministic Strategy Design • 100% reproducible behavior across backtests, replay mode, and live trading • No asynchronous side effects • Ideal for systematic analysis and optimization Extensive Visualization & Debug Information • Investment, profit, and status plots • Detailed tables for trades, cycles, and statistics • All relevant internal states visible directly on the chart Alert & Automation Ready • Designed for TradingView alert integration • Compatible with external automation platforms (e.g. API-based broker execution) ⸻ Who Is CTAY Hive Worker For? • Advanced traders focused on structured DCA strategies • Users who require reliable backtests and deterministic live behavior • Educational and seminar environments where transparency matters more than black-box automation ⸻ Important Notice – Limited Demo Version This script is a limited demo version of CTAY Hive Worker 3.3 Professional. Certain features and configuration options are restricted and provided for demonstration and evaluation purposes only. This strategy is intended solely for educational, analytical, and demonstration use and does not constitute financial, investment, or tax advice. ⸻ More Information For further information about CTAY Hive Worker licenses, training content, and background materials, please contact: • Email: demo@ctay.io • YouTube: CTAY – Crypto Trading Academy www.youtube.com
Pine Script®策略
由HarlekinSimplex提供
1
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.
Pine Script®策略
由ycloudyu提供
Mutanabby_AI | ONEUSDT_MR1 ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce. Backtested Period: June 2019 – December 2025 (~6 years) Performance Summary | Metric | Value | |--------|-------| | Net Profit | +417.68% | | Win Rate | 74.68% | | Profit Factor | 4.019 | | Total Trades | 237 | | Sharpe Ratio | 0.364 | | Sortino Ratio | 1.917 | | Max Drawdown | 51.08% | | Avg Win | +3.14% | | Avg Loss | -2.30% | | Buy & Hold Return | -80.44% | Strategy Logic : Entry Conditions (Long Only): The strategy seeks confluence of three conditions that identify exhausted selling: 1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall) 2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing) 3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred) When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted. Exit Conditions: - Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength) - Trailing Stop: 11x ATR trailing stop that locks in profits as price rises Risk Management - Position Sizing:Fixed position based on account equity divided by entry price - Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains - Pyramiding:Up to 4 orders allowed (can scale into winning positions) - **Commission:** 0.1% per trade (realistic exchange fees included) Important Disclaimers ⚠️ This is NOT financial advice. - Past performance does not guarantee future results - Backtest results may contain look-ahead bias or curve-fitting - Real trading involves slippage, liquidity issues, and execution delays - This strategy is optimized for ONEUSDT specifically — results may differ on other pairs - Always test before risking real capital Recommended Usage - Timeframe:*1H (as designed) - Pair: ONEUSDT (Binance) - Account Size: Ensure sufficient capital to survive max drawdown Source Code Feedback Welcome I'm sharing this strategy freely for educational purposes. Please: - Drop a comment with your backtesting results any you analysis - Share any modifications that improve performance - Let me know if you spot any issues in the logic Happy trading As a quant trader, do you think this strategy will survive in live trading? Yes or No? And why? I want to hear from you guys
Pine Script®策略
由Mutanabby_AI提供
1
STRATEGY 1 │ Red Dragon │ Model 1 │ [Titans_Invest]The Red Dragon Model 1 is a fully automated trading strategy designed to operate BTC/USDT.P on the 4-hour chart with precision, stability, and consistency. It was built to deliver reliable behavior even during strong market movements, maintaining operational discipline and avoiding abrupt variations that could interfere with the trader’s decision-making. Its core is based on a professionally engineered logical structure that combines trend filters, confirmation criteria, and balanced risk management. Every component was designed to work in an integrated way, eliminating noise, avoiding unnecessary trades, and protecting capital in critical moments. There are no secret mechanisms or hidden logic: everything is built to be objective, clean, and efficient. Even though it is based on professional quantitative engineering, Red Dragon Model 1 remains extremely simple to operate. All logic is clearly displayed and fully accessible within TradingView itself, making it easy to understand for both beginners and experienced traders. The structure is organized so that any user can quickly view entry conditions, exit criteria, additional filters, adjustable parameters, and the full mechanics behind the strategy’s behavior. In addition, the architecture was built to minimize unnecessary complexity. Parameters are straightforward, intuitive, and operate in a balanced way without requiring deep adjustments or advanced knowledge. Traders have full freedom to analyze the strategy, understand the logic, and make personal adaptations if desired—always with total transparency inside TradingView. The strategy was also designed to deliver consistent operational behavior over the long term. Its confirmation criteria reduce impulsive trades; its filters isolate noise; and its overall logic prioritizes high-quality entries in structured market movements. The goal is to provide a stable, clear, and repeatable flow—essential characteristics for any medium-term quantitative approach. Combining clarity, professional structure, and ease of use, Red Dragon Model 1 offers a solid foundation both for users who want a ready-to-use automated strategy and for those looking to study quantitative models in greater depth. This entire project was built with extreme dedication, backed by more than 14,000 hours of hands-on experience in Pine Script, continuously refining patterns, techniques, and structures until reaching its current level of maturity. Every line of code reflects this long process of improvement, resulting in a strategy that unites professional engineering, transparency, accessibility, and reliable execution. 🔶 MAIN FEATURES • Fully automated and robust: Operates without manual intervention, ideal for traders seeking consistency and stability. It delivers reliable performance even in volatile markets thanks to the solid quantitative engineering behind the system. • Multiple layers of confirmation: Combines 10 key technical indicators with 15 adaptive filters to avoid false signals. It only triggers entries when all trend, market strength, and contextual criteria align. • Configurable and adaptable filters: Each of the 15 filters can be enabled, disabled, or adjusted by the user, allowing the creation of personalized statistical models for different assets and timeframes. This flexibility gives full freedom to optimize the strategy according to individual preferences. • Clear and accessible logic: All entry and exit conditions are explicitly shown within the TradingView parameters. The strategy has no hidden components—any user can quickly analyze and understand each part of the system. • Integrated exclusive tools: Includes complete backtest tables (desktop and mobile versions) with annualized statistics, along with real-time entry conditions displayed directly on the chart. These tools help monitor the strategy across devices and track performance and risk metrics. • No repaint: All signals are static and do not change after being plotted. This ensures the trader can trust every entry shown without worrying about indicators rewriting past values. 🔷 ENTRY CONDITIONS & RISK MANAGEMENT Red Dragon Model 1 triggers buy (long) or sell (short) signals only when all configured conditions are satisfied. For example: • Volume: • The system only trades when current volume exceeds the volume moving average multiplied by a user-defined factor, indicating meaningful market participation. • RSI: • Confirms bullish bias when RSI crosses above its moving average, and bearish bias when crossing below. • ADX: • Enters long when +DI is above –DI with ADX above a defined threshold, indicating directional strength to the upside (and the opposite conditions for shorts). • Other indicators (MACD, SAR, Ichimoku, Support/Resistance, etc.) Each one must confirm the expected direction before a final signal is allowed. When all bullish criteria are met simultaneously, the system enters Long; when all criteria indicate a bearish environment, the system enters Short. In addition, the strategy uses fixed Take Profit and Stop Loss targets for risk control: Currently: TP around 1.5% and SL around 2.0% per trade, ensuring consistent and transparent risk management on every position. ⚙️ INDICATORS __________________________________________________________   1) 🔊 Volume: Avoids trading on flat charts.   2) 🍟 MACD: Tracks momentum through moving averages.   3) 🧲 RSI: Indicates overbought or oversold conditions.   4) 🅰️ ADX: Measures trend strength and potential entry points.   5) 🥊 SAR: Identifies changes in price direction.   6) ☁️ Cloud: Accurately detects changes in market trends.   7) 🌡️ R/F: Improves trend visualization and helps avoid pitfalls.   8) 📐 S/R: Fixed support and resistance levels.   9)╭╯MA: Moving Averages. 10) 🔮 LR: Forecasting using Linear Regression. __________________________________________________________ 🟢 ENTRY CONDITIONS 🔴 __________________________________________________________ IF all conditions are 🟢 = 📈 Long IF all conditions are 🔴 = 📉 Short __________________________________________________________ 🚨 CURRENT TRIGGER SIGNAL 🚨 __________________________________________________________ 🔊 Volume 🟢 LONG  = (volume) > (MA_volume) * (Volume Mult) 🔴 SHORT = (volume) > (MA_volume) * (Volume Mult) 🧲 RSI 🟢 LONG  = (RSI) > (RSI_MA) 🔴 SHORT = (RSI) < (RSI_MA) 🟢 ALL ENTRY CONDITIONS AVAILABLE 🔴 __________________________________________________________ 🔊 Volume 🟢 LONG  = (volume) > (MA_volume) * (Volume Mult) 🔴 SHORT = (volume) > (MA_volume) * (Volume Mult) 🔊 Volume 🟢 LONG  = (volume) > (MA_volume) * (Volume Mult) and (close) > (open) 🔴 SHORT = (volume) > (MA_volume) * (Volume Mult) and (close) < (open) 🍟 MACD 🟢 LONG  = (MACD) > (Signal Smoothing) 🔴 SHORT = (MACD) < (Signal Smoothing) 🧲 RSI 🟢 LONG  = (RSI) < (Upper) 🔴 SHORT = (RSI) > (Lower) 🧲 RSI 🟢 LONG  = (RSI) > (RSI_MA) 🔴 SHORT = (RSI) < (RSI_MA) 🅰️ ADX 🟢 LONG  = (+DI) > (-DI) and (ADX) > (Treshold) 🔴 SHORT = (+DI) < (-DI) and (ADX) > (Treshold) 🥊 SAR 🟢 LONG  = (close) > (SAR) 🔴 SHORT = (close) < (SAR) ☁️ Cloud 🟢 LONG  = (Cloud A) > (Cloud B) 🔴 SHORT = (Cloud A) < (Cloud B) ☁️ Cloud 🟢 LONG  = (Kama) > (Kama ) 🔴 SHORT = (Kama) < (Kama ) 🌡️ R/F 🟢 LONG  = (high) > (UP Range)      and (upward)     > (0) 🔴 SHORT = (low) < (DOWN Range) and (downward) > (0) 🌡️ R/F 🟢 LONG  = (high) > (UP Range) 🔴 SHORT = (low) < (DOWN Range) 📐 S/R 🟢 LONG  = (close) > (Resistance) 🔴 SHORT = (close) < (Support) ╭╯MA2️⃣ 🟢 LONG  = (Cyan Bar MA2️⃣) 🔴 SHORT = (Red Bar MA2️⃣) ╭╯MA2️⃣ 🟢 LONG  = (close) > (MA2️⃣) 🔴 SHORT = (close) < (MA2️⃣) ╭╯MA2️⃣ 🟢 LONG  = (Positive MA2️⃣) 🔴 SHORT = (Negative MA2️⃣) __________________________________________________________ 🎯 TP / SL 🛑 __________________________________________________________ 🎯 TP: 1.5 ％ 🛑 SL:  2.0 ％ __________________________________________________________ 🪄 UNIQUE FEATURES OF THIS STRATEGY ____________________________________ 1)   𝄜  Table Backtest for Mobile. 2)   𝄜  Table Backtest for Computer. 3)   𝄜  Table Backtest for Computer & Annual Performance. 4)   𝄜  Live Entry Conditions. 1)   𝄜  Table Backtest for Mobile. 2)   𝄜  Table Backtest for Computer. 3)   𝄜  Table Backtest for Computer & Annual Performance. 4)   𝄜  Live Entry Conditions. _____________________________ 𝄜  BACKTEST / PERFORMANCE 𝄜 _____________________________ • Net Profit: +634.47%, Maximum Drawdown: -18.44%. 🪙 PAIR / TIMEFRAME ⏳ 🪙 PAIR: BINANCE:BTCUSDT.P ⏳ TIME: 4 hours (240m) ✅ ON ☑️ OFF ✅ LONG ✅ SHORT 🎯 TP / SL 🛑 🎯 TP: 1.5 (％) 🛑 SL:  2.0 (％) ⚙️ CAPITAL MANAGEMENT 💸 Initial Capital: 10000 $ (TradingView) 💲 Order Size:      10 ％     (Of Equity) 🚀 Leverage:        10 x       (Exchange) 💩 Commission:    0.03 ％  (Exchange) 📆 BACKTEST 🗓️ Start: Setember 24, 2019 🗓️ End:   November 21, 2025 🗓️ Days:  2250 🗓️ Yers:   6.17 🗓️ Bars:  13502 📊 PERFORMANCE 💲 Net Profit:                 + 63446.89 $ 🟢 Net Profit:                 + 634.47 ％ 💲 DrawDown Maximum: - 10727.48 $ 🔴 DrawDown Maximum: - 18.44 ％ 🟢 Total Closed Trades:     1042 🟡 Percent Profitable:       63.92 ％ 🟡 Profit Factor:               1.247 💲 Avg Trade:                 + 60.89 $ ⏱️ Avg # Bars in Trades 🕯️ Avg # Bars: 4 ⏳ Avg # Hrs:  15 ✔️ Trades Winning: 666 ❌ Trades Losing:    376 ✔️ Maximum Consecutive Wins:   11 ❌ Maximum Consecutive Losses: 7 📺 Live Performance : br.tradingview.com • Use this strategy on the recommended pair and timeframe above to replicate the tested results. • Feel free to experiment and explore other settings, assets, and timeframes.
Pine Script®策略
由Titans_Invest提供
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy Summary Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts. Scope and intent • Markets: large cap equities and ETFs, index futures, major FX, liquid crypto • Timeframes: one minute to daily • Default demo: BTC on 60 minute • Purpose: faster yet calmer PSAR that resists chop and improves short discipline • Limits: this is a strategy that places simulated orders on standard candles Originality and usefulness • Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias • Addresses false flips in low volatility and weak downtrends • All controls are exposed in Inputs for testability • Yardstick: ATR normalizes drift so settings port across symbols • Open source. No links. No solicitation Method overview Components • Adaptive AF: base step plus boost factor times logistic strength • Trail inertia: one sided blend that keeps the SAR monotone • Flip hysteresis: price must clear SAR by a buffer times ATR • Volatility gate: ATR over its mean must exceed a ratio • Bear bias for shorts: price below EMA of length 91 with negative slope window 54 • Cooldown bars optional after any entry • Visual SAR smoothing is cosmetic and does not drive orders Fusion rule Entry requires the internal flip plus all enabled gates. No weighted scores. Signal rule • Long when trend flips up and close is above SAR plus buffer times ATR and gates pass • Short when trend flips down and close is below SAR minus buffer times ATR and gates pass • Exit uses SAR as stop and optional ATR take profit per side Inputs with guidance Reactor Engine • Start AF 0.02. Lower slows new trends. Higher reacts quicker • Max AF 1. Typical 0.2 to 1. Caps acceleration • Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends • Strength window 18. Typical 10 to 40. Drift estimation window • ATR length 16. Typical 10 to 30. Volatility unit • Strength gain 4.5. Typical 2 to 6. Steepness of logistic • Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic • Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises • AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth • Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail • Allow Long, Allow Short toggles Trade Filters • Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips • Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars • Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes • Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness Risk • TP long ATR 1.0. Set to zero to disable • TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts Usage recipes Intraday trend focus Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime. Intraday mean reversion focus Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated. Swing continuation Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts. Properties visible in this publication Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls. Realism and responsible publication No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles. Honest limitations and failure modes High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips. Open source reuse and credits Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors. Strategy notice Orders are simulated on standard candles. No lookahead. Entries and exits Long: flip up plus ATR buffer and all gates true Short: flip down plus ATR buffer and gates true with bear bias when enabled Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry Tie handling: stop first if both stop and target could fill in one bar
Pine Script®策略
由exlux提供
Quantum Flux Universal Strategy Summary in one paragraph Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version. Scope and intent • Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto • Timeframes. One minute to daily • Default demo used in the publication. QQQ on one hour • Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps. • What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise. • Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state. • Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols. Method overview in plain language The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction. Base measures • Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale. • Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop. • Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves. Components • Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner. • Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends. • Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response. • Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance. • Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot. Fusion rule • Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent. • The blend power input scales the driver mix. Zero means fixed spans. One means full driver control. • Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes. Signal rule • Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one. • Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one. • When polarity flips from plus to minus, the strategy closes any long and enters a short. • When flux crosses above the guide, the strategy closes any short. What you will see on the chart • White polarity plot around the zero line • A dotted reference line at zero named Zen • Green background tint for positive polarity and red background tint for negative polarity • Strategy long and short markers placed by the TradingView engine at entry and at close conditions • No table in this version to keep the visual clean and portable Inputs with guidance Setup • Price source. Default ohlc4. Stable for noisy symbols. • Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive. • Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price. Logic • Guide span. Typical range 4 to 12. A small guide smooths without eating turns. • Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing. • Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work. • Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise. • Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve. • Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak. • Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong. • Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline. • Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols. • Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs. Filters • Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends. • Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping. • Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version. Alerts • This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows. Strategy has been currently adapted for the QQQ asset with 30/60min timeframe. For other assets may require new optimization Properties visible in this publication • Initial capital 25000 • Base currency Default • Default order size method percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Honest limitations and failure modes • Past results do not guarantee future outcomes • Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency • Gap heavy symbols may benefit from the MAD Z normalization • Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context • Session time is the exchange time of the chart • If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference Open source reuse and credits • None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank • Method and fusion are original in construction and disclosure Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs. Strategy add on block Strategy notice Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used. Entries and exits • Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero • Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short • Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed • Tie handling. Not applicable in this version because there are no fixed stops or targets Position sizing • Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice Properties used on the published chart • Initial capital 25000 • Base currency Default • Default order size percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Dataset and sample size • Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour • Trade count in sample 324 on the example chart Release notes template for future updates Version 1.1. • Add alertcondition lines for long, short, and exit short • Add optional table with component readouts • Add optional stop model with a distance unit expressed as ATR or a percent of price Notes. Backward compatibility Yes. Inputs migrated Yes.
Pine Script®策略
由exlux提供
Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice. 0. Publication mode and rationale This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible. Why Protected The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users. Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results. 1. What the strategy does in one paragraph Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity. Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor. Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal. 2. Why it is original and useful It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance. The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise. Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants. Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates. The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about. 3. Plain language overview of the math Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural. Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases. Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one. Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow. Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band. 4. Entries, exits, and position sizing Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs. Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate. Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active. Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn. Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts. 5. Inputs quick guide with recommended ranges Every input has a tooltip in the script. The same guidance appears here for fast reading. Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing. Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55. Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more. Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence. Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical. Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets. Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts. Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more. Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes. AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes. Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70. Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20. Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2. Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts. Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior. Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits. Background heat opacity . Cosmetic. Set to taste. Zero disables it. 6. Properties used on the published chart The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results. Initial capital 100000 Base currency USD Order size 2 percent of equity coming from our risk management inputs. Pyramiding 0 Commission 0.05 percent Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research. Recalculate after order is filled off. On every tick off. Using bar magnifier on. On bar close on. Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1. 7. Visual elements and alerts The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan. 8. How to reproduce the example Open a BTCUSD daily chart with regular candles. Add the strategy and load the defaults that match the values above. Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on. Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown. 9. Practical tuning recipes Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions. Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar. Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday. Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions. Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it. 10. Strengths and limitations Strengths Self scaling unit through AAR makes the tool portable across markets and timeframes. Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align. Adaptive centering reduces structural bias at the score level which helps during regime flips. Limitations In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable. Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate. Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research. The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases. 11. Realism and responsible publication No promises or projections of performance are made. Past results never guarantee future outcomes. Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange. Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model. Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size. Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders. 12. Suggested research workflow Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history. Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value. Try one higher timeframe blend with a modest weight. Large weights can drown the signal. Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop. Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy. Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods. 13. How to read the HUD and heat map The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty. 14. Frequently asked questions Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch. Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly. Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off. Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown. Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing. Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context. 15. Concepts glossary AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops. Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity. Geometric mean growth . Rate that preserves the effect of compounding over many bars. Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound. Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale. Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew. 16. Educational notice and risk statement Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results. 17. Final notes for readers and moderators The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments. Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence. Thank you for your time to read all of this
Pine Script®策略
由exlux提供
TrendIsYourFriend Strategy (SPY,IWM,VYM,XLK,SPXL,BTC,GOLD,VT...)Personal disclaimer Don’t trust this strategy. Don’t trust any other model either just because of its author or a backtest curve. Overfitting is an easy trap, and beginners often fall into it. This script isn’t meant to impress you. It’s meant to survive reality. If it does, maybe it will raise questions and you’ll remember it. Legal disclaimer Educational purposes only. Not financial advice. Past performance is not indicative of future results. Strategy description Long-only, trend-based logic with two entry types (trend continuation or excess-move reversion), dynamic stop-losses, and a VIX filter to avoid turbulent markets. Minimal number of parameters with enough trades to support robustness. For backtest, each trade is sized at $10,000 flat (no compounding, to focus on raw model quality and the regularity of its results over time). Fees = $0 (neutral choice, as brokers differ). Slippage = $0, deliberate choice: most entries occur on higher timeframes, and some assets start their history on charts at very low prices, which would otherwise distort results. What makes this script original Beyond a classical trend calculation, both excess-move entries and dynamic stop-loss exits also rely on trend logic. Except for the VIX filter, everything comes from trend functions, with very few parameters. Pre-configurations are fixed in the code, allowing sincere performance tracking across a dozen cases over the medium to long term. Allowed SPY (ARCA) — 2-hour chart: S&P 500 ETF, most liquid equity benchmark IWM (ARCA) — Daily chart: Russell 2000 ETF, US small caps VYM (ARCA) — Daily chart: Vanguard High Dividend Yield ETF XLK (ARCA) — Daily chart: Technology Select Sector SPDR SPXL (ARCA) — Daily chart: 3× leveraged S&P 500 ETF BTCUSD (COINBASE) — 4-hour chart: Bitcoin vs USD GOLD (TVC) — Daily chart: Gold spot price VT (ARCA) — Daily chart: Vanguard Total World Stock ETF PG (NYSE) — Daily chart: Procter & Gamble Co. CQQQ (ARCA) — Daily chart: Invesco China Technology ETF EWC (ARCA) — Daily chart: iShares MSCI Canada ETF EWJ (ARCA) — Daily chart: iShares MSCI Japan ETF How to use and form an opinion on it Works only on the pairs above. Feel free to modify the input parameters (slippage, fees, order size, margins, …) to see how the model behaves under your own conditions Compare it with a simple Buy & Hold (requires an order size of 100% equity). You may also want to look at its time-in-market — the share of time your capital is actually at risk. Finally, let me INSIST on this : let it run live for months before forming an opinion! Share your thoughts in the comments 🚀 if you’d like to discuss its live performance.
Pine Script®策略
由Email-Trader提供
8
Signalgo Strategy ISignalgo Strategy I: Technical Overview Signalgo Strategy I is a systematically engineered TradingView strategy script designed to automate, test, and manage trend-following trades using multi-timeframe price/volume logic, volatility-based targets, and multi-layered exit management. This summary covers its operational structure, user inputs, entry and exit methodology, unique technical features, and practical application. Core Logic and Workflow Multi-Timeframe Data Synthesis User-Defined Timeframe: The user chooses a timeframe (e.g., 1H, 4H, 1D, etc.), on which all strategy signals are based. Cross-Timeframe Inputs: The strategy imports closing price, volume, and Average True Range (ATR) for the selected interval, independently from the chart’s native timeframe, enabling robust multi-timeframe analysis. Price Change & Volume Ratio: It calculates the percent change of price per bar and computes a volume ratio by comparing current volume to its 20-bar moving average—enabling detection of true “event” moves vs. normal market noise. Hype Filtering Anti-Hype Mechanism: An entry is automatically filtered out if abnormal high volume occurs without corresponding price movement, commonly observed during manipulation or announcement periods. This helps isolate genuine market-driven momentum. User Inputs Select Timeframe: Choose which interval drives signal generation. Backtest Start Date: Specify from which date historical signals are included in the strategy (for precise backtests). Take-Profit/Stop-Loss Configuration: Internally, risk levels are set as multiples of ATR and allow for three discrete profit targets. Entry Logic Trade Signal Criteria: Price change magnitude in the current bar must exceed a fixed sensitivity threshold. Volume for the bar must be significantly elevated compared to average, indicating meaningful participation. Anti-hype check must not be triggered. Bullish/Bearish Determination: If all conditions are met and price change direction is positive, a long signal triggers. If negative, a short signal triggers. Signal Debouncing: Ensures a signal triggers only when a new condition emerges, avoiding duplicate entries on flat or choppy bars. State Management: The script tracks whether an active long or short is open to avoid overlapping entries and to facilitate clean reversals. Exit Strategy Take-Profits: Three distinct profit targets (TP1, TP2, TP3) are calculated as fixed multiples of the ATR-based stop loss, adapting dynamically to volatility. Reversals: If a buy signal appears while a short is open (or vice versa), the existing trade is closed and reversed in a single step. Time-Based Exit: If, 49 bars after entry, the trade is in-profit but hasn’t reached TP1, it exits to avoid stagnation risk. Adverse Move Exit: The position is force-closed if it suffers a 10% reversal from entry, acting as a catastrophic stop. Visual Feedback: Each TP/SL/exit is plotted as a clear, color-coded line on the chart; no hidden logic is used. Alerts: Built-in TradingView alert conditions allow automated notification for both entries and strategic exits. Distinguishing Features vs. Traditional MA Strategies Event-Based, Not Just Slope-Based: While classic moving average strategies enter trades on MA crossovers or slope changes, Signalgo Strategy I demands high-magnitude price and volume confirmation on the chosen timeframe. Volume Filtering: Very few MA strategies independently filter for meaningful volume spikes. Real Market Event Focus: The anti-hype filter differentiates organic market trends from manipulated “high-volume, no-move” sessions. Three-Layer Exit Logic: Instead of a single trailing stop or fixed RR, this script manages three profit targets, time-based closures, and hard adverse thresholds. Multi-Timeframe, Not Chart-Dependent: The “main” analytical interval can be set independently from the current chart, allowing for in-depth cross-timeframe backtests and system runs. Reversal Handling: Automatic handling of signal reversals closes and flips positions precisely, reducing slippage and manual error. Persistent State Tracking: Maintains variables tracking entry price, trade status, and target/stop levels independently of chart context. Trading Application Strategy Sandbox: Designed for robust backtesting, allowing users to simulate performance across historical data for any major asset or interval. Active Risk Management: Trades are consistently managed for both fixed interval “stall” and significant loss, not just via trailing stops or fixed-day closes. Alert Driven: Can power algorithmic trading bots or notify discretionary traders the moment a qualifying market event occurs.
Pine Script®策略
由signalgo提供
RCI 2 Dashboards ✅ Strategy: RCI 2 Dashboards BY Sonu JAIN This advanced strategy is built around the Rank Correlation Index (RCI), a unique momentum oscillator, and combines it with a comprehensive suite of powerful indicators to identify high-probability trading opportunities. The strategy’s core strength lies in its ability to filter signals using up to 12 different conditions for both long and short trades. To make the decision-making process clear and intuitive, the strategy features two dynamic, customizable dashboards right on your chart. The first dashboard gives you a live, detailed breakdown of which conditions are met, while the second provides a real-time overview of the strategy’s performance. How It Works The strategy generates entry signals based on RCI crossovers and crossunders. These signals are then filtered by a customizable combination of other indicators to confirm the trade. Long Entry: The RCI crosses over its moving average. All enabled long-side filters are met. Short Entry: The RCI crosses under its moving average. All enabled short-side filters are met. Key Features RCI Crossover Logic: The core of the strategy is an RCI crossover/crossunder with a customizable moving average (MA). You can choose from SMA, EMA, SMMA (RMA), WMA, or VWMA. 12 Optional Filters: This strategy goes far beyond a simple RCI signal. You can enable or disable a wide range of filters to refine your entries. These include: Trend: Supertrend, Parabolic SAR (SAR), and Vortex Indicator. Volatility: Keltner Channels (KC) and Bollinger Bands (BB). Momentum: Woodies CCI, Money Flow Index (MFI), and Relative Strength Index (RSI). Volume: On-Balance Volume (OBV) and simple Volume analysis. Directional Strength: Average Directional Index (ADX). Timing: A time-of-day filter to trade only during specific market hours. Dual Dashboards: Detailed Condition Dashboard: This dashboard shows you exactly which of the 12 filters are currently met with a simple ✓ or ✗. This provides instant clarity on why a trade is or isn't being considered. Performance Dashboard: This dashboard displays key performance metrics in real-time, including net profit, win rate, profit factor, max drawdown, and current/max winning and losing streaks. It also provides details on the most recent trade, such as entry, stop-loss, and exit prices. Customizable Stop Loss: The strategy includes a fixed percentage-based stop loss for both long and short positions, which you can easily configure in the settings. Trade Direction Control: You can choose to trade "Long Only," "Short Only," or "Long & Short," giving you complete control over your trading bias. This strategy is a powerful tool for traders who want to build a robust, multi-filtered system. The included dashboards make it an excellent educational tool for understanding how different indicators work together to form a complete trading plan. You can use it to backtest and optimize your own unique combination of indicators to find the perfect setup for your market and timeframe.
Pine Script®策略
由tvp2005tvp提供
1
Auto Intelligence Selective Moving Average(AI/MA)# 🤖 Auto Intelligence Moving Average Strategy (AI/MA) **AI/MA** is a state-adaptive moving average crossover strategy designed to **maximize returns from golden cross / death cross logic** by intelligently switching between different MA types and parameters based on market conditions. --- ## 🎯 Objective To build a moving average crossover strategy that: - **Adapts dynamically** to market regimes (trend vs range, rising vs falling) - **Switches intelligently** between SMA, EMA, RMA, and HMA - **Maximizes cumulative return** under realistic backtesting --- ## 🧪 materials amd methods - **MA Types Considered**: SMA, EMA, RMA, HMA - **Parameter Ranges**: Periods from 5 to 40 - **Market Conditions Classification**: - Based on the slope of a central SMA(20) line - And the relative position of price to the central line - Resulting in 4 regimes: A (Bull), B (Pullback), C (Rebound), D (Bear) - **Optimization Dataset**: - **Bybit BTCUSDT.P** - **1-hour candles** - **2024 full-year** - **Search Process**: - **Random search**: 200 parameter combinations - Evaluated by: - `Cumulative PnL` - `Sharpe Ratio` - `Max Drawdown` - `R² of linear regression on cumulative PnL` - **Implementation**: - Optimization performed in **Python (Pandas + Matplotlib + Optuna-like logic)** - Final parameters ported to **Pine Script (v5)** for TradingView backtesting --- ## 📈 Performance Highlights (on optimization set) | Timeframe | Return (%) | Notes | |-----------|------------|----------------------------| | 6H | +1731% | Strongest performance | | 1D | +1691% | Excellent trend capture | | 12H | +1438% | Balance of trend/range | | 5min | +27.3% | Even survives scalping | | 1min | +9.34% | Robust against noise | - Leverage: 100x - Position size: 100% - Fees: 0.055% - Margin calls: **none** 🎯 --- ## 🛠 Technology Stack - `Python` for data handling and optimization - `Pine Script v5` for implementation and visualization - Fully state-aware strategy, modular and extendable --- ## ✨ Final Words This strategy is **not curve-fitted**, **not over-parameterized**, and has been validated across multiple timeframes. If you're a fan of dynamic, intelligent technical systems, feel free to use and expand it. 💡 The future of simple-yet-smart trading begins here.
Pine Script®策略
由chikaharu提供
6
Momentum Long + Short Strategy (BTC 3H)Momentum Long + Short Strategy (BTC 3H) 🔍 How It Works, Step by Step Detect the Trend (📈/📉) Calculate two moving averages (100-period and 500-period), either EMA or SMA. For longs, we require MA100 > MA500 (uptrend). For shorts, we block entries if MA100 exceeds MA500 by more than a set percentage (to avoid fading a powerful uptrend). Apply Momentum Filters (⚡️) RSI Filter: Measures recent strength—only allow longs when RSI crosses above its smoothed average, and shorts when RSI dips below the oversold threshold. ADX Filter: Gauges trend strength—ensures we only enter when a meaningful trend exists (optional). ATR Filter: Confirms volatility—avoids choppy, low-volatility conditions by requiring ATR to exceed its smoothed value (optional). Confirm Entry Conditions (✅) Long Entry: Price is above both MAs Trend alignment & optional filters pass ✅ Short Entry: Price is below both MAs and below the lower Bollinger Band RSI is sufficiently oversold Trend-blocker & ATR filter pass ✅ Position Sizing & Risk (💰) Each trade uses 100 % of account equity by default. One pyramid addition allowed, so you can scale in if the move continues. Commission and slippage assumptions built in for realistic backtests. Stops & Exits (🛑) Long Stop-Loss: e.g. 3 % below entry. Long Auto-Exit: If price falls back under the 500-period MA. Short Stop-Loss: e.g. 3 % above entry. Short Take-Profit: e.g. 4 % below entry. 🎨 Why It’s Powerful & Customizable Modular Filters: Turn on/off RSI, ADX, ATR filters to suit different market regimes. Adjustable Thresholds: Fine-tune stop-loss %, take-profit %, RSI lengths, MA gaps and more. Multi-Timeframe Potential: Although coded for 3 h BTC, you can adapt it to stocks, forex or other cryptos—just recalibrate! Backtest Fine-Tuned: Default settings were optimized via backtesting on historical BTC data—but they’re not guarantees of future performance. ⚠️ Warning & Disclaimer This strategy is for educational purposes only and designed for a toy fund. Crypto markets are highly volatile—you can lose 100 % of your capital. It is not a predictive “holy grail” but a rules-based framework using past data. The parameters have been fine-tuned on historical data and are not valid for future trades without fresh calibration. Always practice with paper-trading first, use proper risk management, and do your own research before risking real money. 🚨🔒 Good luck exploring and experimenting! 🚀📊
Pine Script®策略
由noobztrader101提供
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis. ⚙️ Core Strategy Components 1️⃣ Average Directional Index (ADX) Calculation The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI): +DI (Positive Directional Index): Measures upward price movement. -DI (Negative Directional Index): Measures downward price movement. ADX Value: Higher values indicate stronger trends, regardless of direction. This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends. 2️⃣ SMA Filter (Optional Trend Confirmation) The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled: ✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length). ✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries. This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability. 📌 Trade Logic & Conditions 🔹 Long Entry Conditions A buy signal is triggered when: ✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend. ✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier. 🔻 Exit Conditions A position is closed when: ✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening. By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes. 📏 Trade Visualization & Tracking Trade Markers "Buy" label (▲) appears when a long position is opened. "Close" label (▼) appears when a position is exited. Trade History Boxes Green if a trade is profitable. Red if a trade closes at a loss. Trend Tracking Lines Horizontal lines mark entry and exit prices. A filled trade box visually represents trade duration and profitability. These elements provide clear visual insights into trade execution and performance. ⚡ How to Use This Strategy 1️⃣ Apply the script to a BTC chart in TradingView. 2️⃣ Adjust ADX entry/exit levels based on trend sensitivity. 3️⃣ Enable or disable the SMA filter for trend confirmation. 4️⃣ Backtest performance to analyze historical trade execution. 5️⃣ Monitor trade markers and history boxes for real-time trend insights. This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
Pine Script®策略
由PineIndicators提供
2
Swing High/Low Pivots Strategy [LV]The Swing High/Low Pivots Strategy was developed as a counter-momentum trading tool. The strategy is suitable for any market and the default values used in the input settings menu are set for Bitcoin (best on 15min). These values, expressed in minimum ticks (or pips if symbol is Forex) make this tool perfectly adaptable to every symbol and/or timeframe. Check tooltips in the settings menu for more details about every user input. STRTEGY ENTRY & EXIT MECHANISMS: Trades Entry based on the detection of swing highs and lows for short and long entries respectively, validated by: - Limit orders placed after each new pivot level confirmation - Moving averages trend filter (if enabled) - No active trade currently open Trades Exit when the price reaches take-profit or stop-loss level as defined in the settings menu. A double entry/second take-profit level can be enabled for partial exits, with dynamic stop-loss adjustment for the remaining position. Enhanced Trade Precision: By limiting entries to confirmed swing high (HH, LH) or swing low (HL, LL) pivot points, the strategy ensures that trades occur at levels of significant price reversals. This precision reduces the likelihood of entering trades in the midst of a trend or during uncertain price action. Risk Management Optimization: The strategy incorporates clearly defined stop-loss (SL) and take-profit (TP) levels derived from the pivot points. This structured approach minimizes potential losses while locking in profits, which is critical for consistent performance in volatile markets. Trend Filtering for Better Entry: The use of a configurable moving average filter adds a layer of trend validation. This prevents entering trades against the dominant market trend, increasing the probability of success for each trade. Avoidance of Noise: The lookback period (length parameter) confirms pivots only after a set number of bars, effectively filtering out market noise and ensuring that entries are based on reliable, well-defined price movements. Adaptability Across Markets: The strategy is versatile and can be applied across different markets (Forex, stocks, crypto) due to its dynamic use of ticks and pips converters. It adapts seamlessly to varying price scales and asset types. Dual Quantity Entries: The original and optionnal double-entry mechanism allows traders to capture both short-term and extended profits by scaling out of positions. This adaptive approach caters to varying risk appetites and market conditions. Clear Visualization: The plotted pivot points, entry limits, SL, and TP levels provide visual clarity, making it easy for traders to track the strategy's behavior and make informed decisions. Automated Execution with Alerts: Integrated alerts for both entries and exits ensure timely actions without the need for constant market monitoring, enhancing efficiency. Configurable alert messages are suitable for API use. Any feedback, comments, or suggestions for improvement are always welcome. Hope you enjoy!
Pine Script®策略
由LucasVivien提供
14
HFT V.2 EnhancedTitle: HFT V.2 Enhanced - ATR Dynamic Stop-Loss & Take-Profit Description: The HFT V.2 Enhanced strategy is designed for high-frequency trading with dynamic trade management and robust entry/exit logic. This strategy uses simple moving averages (SMA) for trend identification and the relative strength index (RSI) for momentum confirmation. In this enhanced version, the strategy also incorporates dynamic stop-loss and take-profit levels based on the Average True Range (ATR), offering better adaptability to market volatility. Features: Moving Average Crossover: Uses a fast and slow SMA to capture trend reversals and generate trade entries. RSI Confirmation: Ensures momentum is in the direction of the trade by incorporating the RSI threshold for both long and short entries. Dynamic Stop-Loss and Take-Profit: Stop-loss and take-profit levels are calculated based on the ATR, allowing the strategy to adjust its exit points according to market volatility. This helps manage risk more effectively and capture larger trends. Auto-Close Opposing Positions: Automatically closes any open long positions when a short entry is triggered, and vice versa. Once-Per-Bar Execution: Ensures that a position is entered only once per bar, avoiding multiple trades within the same bar. Parameters: Fast MA Length: Defines the length of the fast-moving average. Slow MA Length: Defines the length of the slow-moving average. RSI Length: Sets the period for the RSI indicator. RSI Threshold: Controls the RSI level for confirming momentum (50 by default). ATR Length: Determines the period for the ATR calculation. ATR Multiplier for Stop-Loss/Take-Profit: Adjusts the sensitivity of the stop-loss and take-profit levels based on ATR. How it Works: Long Entry: The strategy opens a long trade when the fast SMA crosses above the slow SMA, and the RSI is above the user-defined threshold. A dynamic stop-loss is placed below the entry price, and a take-profit target is set based on ATR. Short Entry: The strategy opens a short trade when the fast SMA crosses below the slow SMA, and the RSI is below the inverse threshold. A stop-loss is placed above the entry price, and a take-profit target is set using ATR. Risk Management: The strategy adapts to changing market conditions by dynamically adjusting its stop-loss and take-profit levels, ensuring it remains responsive to market volatility. This script is ideal for traders looking for a high-frequency strategy with advanced trade management, including dynamic exits and volatility-based risk management. Disclaimer: Always backtest and optimize the parameters to fit your trading style and risk tolerance before using the strategy in live trading.
Pine Script®策略
由daoforex4you提供
8