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Voce Eterna - BTC Safe Final🚀 Strategic Trading Framework: The "Peak Reset" Logic We have engineered an advanced trading algorithm tailored for Bitcoin Futures, designed with a core focus on extreme capital protection. The following 10 keywords define the architecture of this strategy: High-Water Mark: The system continuously tracks the maximum equity value achieved, establishing a new baseline for protection at every peak. Capital Preservation: Our primary objective is to safeguard the initial €2,000 investment through rigorous risk controls. Risk Mitigation: Each trade is strictly managed to eliminate catastrophic losses and ensure long-term sustainability. Trend Filtering: By utilizing a 200-period SMA filter, the algorithm operates exclusively during confirmed Bull Market conditions. Trailing Stop: Profit is dynamically followed, allowing the strategy to capture the maximum upside of a trend before exiting. Profit Locking: Once a profit peak is established, the system secures gains by preventing the equity from retracing significantly. Dynamic Exit: Rather than relying on fixed targets, the algorithm exits positions based on real-time market exhaustion and trend decay. Whipsaw Protection: Optimized filters are in place to ignore "noise" and false signals common during sideways market volatility. Automated Reset: An autonomous "kill-switch" triggers if the equity drops below a specific percentage of the peak, halting all operations to save profit. Evidence-Based Backtesting: Rigorous analysis of 2026 data ensures the strategy remains resilient against the high volatility of the crypto market. The mission is clear: we do not aim to beat the market every single day, but rather to survive the downturns in order to thrive during the rallies. 📈🛡️
Estratégia Pine Script®
por abcdddiego
Yzkvng SMC Confirmations & webhookWhat PineScript Does Monitors price action Detects trading signals Sends alert() with JSON data What TradingView Does Shows popup notification Sends HTTP POST to webhook URL Stores in console logs What Your Backend Does Receives the POST request Logs the data Updates database Sends notifications Places trades (if automated) All Three Happen Together When PineScript detects a signal: Instantly: Popup appears on TradingView Instantly: HTTP request sent to backend Simultaneously: Both happen at the same time
Estratégia Pine Script®
por mikecheq5
Momentum Fusion X Strategy (with data filter.)Momentum Fusion X Strategy — Conceptual Overview Momentum Fusion X Strategy is a selectively reactive market-participation system designed to engage only when price behavior exhibits structured directional clarity across multiple internal evaluation layers. Rather than responding to isolated indicators or short-term noise, the strategy operates on a confirmation-based framework where trades are activated only when the broader internal state of the market demonstrates sufficient directional agreement. This approach intentionally prioritizes quality of participation over frequency, allowing the system to remain inactive during uncertain or low-information phases. The strategy has demonstrated its strongest performance characteristics on MIDCAPNIFTY, while remaining structurally adaptable to other instruments and market environments. Structural Philosophy The internal architecture is built around a multi-layered decision model: Directional Consensus Framework Trades are considered only when multiple independent internal components align in the same directional bias. No single condition is capable of triggering a trade independently. Momentum Confirmation Logic Price movement is evaluated in a manner that emphasizes continuation strength rather than short-lived reactions. This helps reduce participation during false breakouts or choppy market behavior. Noise Suppression The system actively filters out ambiguous conditions, remaining flat during periods where directional intent lacks clarity or conviction. This structural discipline ensures consistency and prevents over-trading, particularly on lower timeframes. Trade Behaviour & Execution Trade Initiation Positions are initiated only when internal directional alignment reaches a predefined quality threshold. Partial or conflicting conditions are intentionally ignored. Trade Exit Positions are closed dynamically when internal momentum deteriorates or when directional alignment weakens, helping limit exposure during transitions or reversals. Market Inactivity The strategy may display selective trade participation during backtests. This behavior is intentional and reflects strict filtering logic rather than missed opportunities. Backtesting & Configuration Notes Data Filter: The strategy includes a data filter input, allowing controlled backtesting from a specific start date. Backtest Start Date: Historical evaluation has been conducted starting from 5 August 2025. Initial Capital: Backtests are configured using an initial capital of 10,000. Primary Timeframe: The strategy is intended to be evaluated and used on the 15-minute timeframe for optimal structural behavior. Automation & Execution Support The script includes a built-in Dhan webhook alert system, enabling optional automation of execution workflows. Alerts are synchronized directly with the strategy’s internal execution logic to ensure alignment between backtest results and live alert behavior. Commission and slippage are incorporated into the strategy configuration to provide a more realistic simulation of execution conditions. Commission: 0.01% Slippage: 2 points Intended Usage Context Instrument Focus: MIDCAPNIFTY (best observed performance) Trading Style: Intraday, momentum-based participation Trade Frequency: Selective by design Timeframe: 15-Minute Users are encouraged to apply independent capital allocation, position sizing, and risk controls appropriate to their individual trading plan. Intellectual Property Notice The internal construction, scoring logic, alignment thresholds, and execution conditions are intentionally abstracted. This description explains the conceptual philosophy without exposing implementation details, preserving the originality and intellectual integrity of the strategy. Direct replication of the internal logic is neither implied nor supported by this publication. Disclaimer This strategy is provided strictly for educational, research, and analytical purposes. Market behavior evolves over time, and historical performance does not guarantee future results. Users are responsible for forward testing, execution decisions, and risk management when applying this strategy in live market conditions.
Estratégia Pine Script®
por algovisionx2
Momentum Fusion X Strategy (with data filter) Momentum Fusion X Strategy — Conceptual Overview Momentum Fusion X Strategy is a selectively reactive market-participation system designed to engage only when price behavior exhibits structured directional clarity across multiple internal evaluation layers. Rather than responding to isolated indicators or short-term noise, the strategy operates on a confirmation-based framework where trades are activated only when the broader internal state of the market demonstrates sufficient directional agreement. This approach intentionally prioritizes quality of participation over frequency, allowing the system to remain inactive during uncertain or low-information phases. The strategy has demonstrated its strongest performance characteristics on MIDCAPNIFTY, while remaining structurally adaptable to other instruments and market environments. Structural Philosophy The internal architecture is built around a multi-layered decision model: Directional Consensus Framework Trades are considered only when multiple independent internal components align in the same directional bias. No single condition is capable of triggering a trade independently. Momentum Confirmation Logic Price movement is evaluated in a manner that emphasizes continuation strength rather than short-lived reactions. This helps reduce participation during false breakouts or choppy market behavior. Noise Suppression The system actively filters out ambiguous conditions, remaining flat during periods where directional intent lacks clarity or conviction. This structural discipline ensures consistency and prevents over-trading, particularly on lower timeframes. Trade Behaviour & Execution Trade Initiation Positions are initiated only when internal directional alignment reaches a predefined quality threshold. Partial or conflicting conditions are intentionally ignored. Trade Exit Positions are closed dynamically when internal momentum deteriorates or when directional alignment weakens, helping limit exposure during transitions or reversals. Market Inactivity The strategy may display selective trade participation during backtests. This behavior is intentional and reflects strict filtering logic rather than missed opportunities. Backtesting & Configuration Notes Data Filter: The strategy includes a data filter input, allowing controlled backtesting from a specific start date. Backtest Start Date: Historical evaluation has been conducted starting from 5 August 2025. Initial Capital: Backtests are configured using an initial capital of 10,000. Primary Timeframe: The strategy is intended to be evaluated and used on the 15-minute timeframe for optimal structural behavior. Automation & Execution Support The script includes a built-in Dhan webhook alert system, enabling optional automation of execution workflows. Alerts are synchronized directly with the strategy’s internal execution logic to ensure alignment between backtest results and live alert behavior. Commission and slippage are incorporated into the strategy configuration to provide a more realistic simulation of execution conditions. Commission: 0.01% Slippage: 2 points Intended Usage Context Instrument Focus: MIDCAPNIFTY (best observed performance) Trading Style: Intraday, momentum-based participation Trade Frequency: Selective by design Timeframe: 15-Minute Users are encouraged to apply independent capital allocation, position sizing, and risk controls appropriate to their individual trading plan. Intellectual Property Notice The internal construction, scoring logic, alignment thresholds, and execution conditions are intentionally abstracted. This description explains the conceptual philosophy without exposing implementation details, preserving the originality and intellectual integrity of the strategy. Direct replication of the internal logic is neither implied nor supported by this publication. Disclaimer This strategy is provided strictly for educational, research, and analytical purposes. Market behavior evolves over time, and historical performance does not guarantee future results. Users are responsible for forward testing, execution decisions, and risk management when applying this strategy in live market conditions.
Estratégia Pine Script®
por algovisionx2
Quantum X Strategy (with Alert)Quantum X Strategy — Expanded Description Quantum X Strategy is a carefully structured market-participation framework designed to initiate trades only when strong directional alignment is detected across multiple independent market dimensions. Unlike reactive or single-indicator systems, this strategy evaluates the broader market context to ensure participation only under conditions with a higher probability of meaningful directional movement. Random or partial signals are ignored, with the system prioritizing structured, high-quality opportunities over trade frequency. Structural Design The strategy’s decision-making process is based on a multi-dimensional analysis of price behavior: Directional Alignment: Multiple independent market behaviors are evaluated collectively to determine bullish or bearish intent. Weighted Contribution: Each component contributes independently to an internal alignment score. Trades are considered only when the combined state reaches a meaningful threshold. Quality Filtering: Low-quality, ambiguous, or unstable conditions are filtered out to reduce exposure during uncertain market phases. This structure ensures that no single condition can trigger a trade on its own, maintaining discipline, consistency, and robustness in execution. Trade Dynamics Trade Activation: Trades are initiated only when internal alignment reaches a significant level of directional consensus. Partial or weak signals are ignored. Trade Closure & Reversal: Positions are dynamically closed when alignment weakens or when a directional bias reversal is detected. The system is designed to reverse positions rather than stack trades. Market Inactivity: During periods of indecision, low volatility, or insufficient directional clarity, the strategy remains inactive to avoid overtrading. Backtesting Context The strategy is restricted to post-January 2025 market data to ensure relevance to current volatility structures and market behavior. Older regimes are intentionally excluded to maintain realistic and contemporary performance evaluation. Intended Use Instrument: MIDCAPNIFTY Futures Timeframe: 15-Minute Application: Intraday trading and short-term directional participation Position Size: 1 lot (120 quantity) Initial Capital (Backtest Reference): ₹10,000 Risk Management: Designed to be used alongside independent stop-loss, position sizing, and capital allocation rules defined by the user Strict adherence to the system’s signals is recommended. Manual overrides may compromise the integrity of the framework. Dhan In-Built Execution (Usage Summary) This strategy supports alert-based automated execution via Dhan, using TradingView webhooks. TradingView generates alerts only Order execution is handled externally via Dhan’s system TradingView does not place trades directly Futures Quantity Logic (Important) MIDCAPNIFTY 1 lot = 120 quantity Because the strategy uses reversal logic: If you want to trade 1 lot, set quantity = 2 One quantity is used to exit the existing position The second quantity creates the new reversed position Contract Symbol Mapping Current month: MIDCPNIFTY1! Next month: MIDCPNIFTY2! Far month: MIDCPNIFTY3! To trade a different expiry, simply replace the symbol in the input field accordingly. Intellectual Property Notice The internal scoring model, alignment logic, weighting structure, and activation thresholds are intentionally abstracted to protect the originality and intellectual property of the strategy. This prevents direct replication while still allowing conceptual understanding for evaluation and moderation. Disclaimer This strategy is provided strictly for educational, research, and backtesting purposes only. Market conditions change over time, and past performance does not guarantee future results. Users are solely responsible for forward testing, capital deployment, risk control, and compliance with broker and platform rules before using the strategy in live environments. Moderator-Friendly Expanded Summary Instrument & Timeframe: MIDCAPNIFTY, 15-Minute Start Date: January 2025 onward Position Size: 1 lot (120 quantity) Initial Capital: ₹10,000 Commission & Slippage: 0.01% commission, 2-point slippage Trade Logic: Multi-dimensional internal alignment model Trade Activation: Only when strong directional consensus is achieved Trade Closure: Alignment deterioration or trend bias reversal Market Inactivity: Passive during low-information or ambiguous phases Execution: Alert-based, via third-party (Dhan) webhook system Risk Management: User-defined stop-loss and capital allocation required IP Protection: Internal logic abstracted Purpose: Educational, research, and demonstration use only
Estratégia Pine Script®
por algovisionx2
ETH Scalping Bot V2 (Aggressive)⚠️ BACKTEST DATA NOTICE Due to TradingView's 1-minute bar limit, the Strategy Tester below only shows the last 7-14 days of data. The +7,107% profit is based on Deep Backtesting (3 Years). 👉 To see the FULL 3-Year Report: Please check the screenshot on my Whop page or the link below This is a custom automated strategy designed for Ethereum (ETH) scalping on lower timeframes (1m/5m). It is built to capture volatility while strictly managing risk using a dual-mode logic. █ Strategy Concept This script combines Trend-Following indicators with Momentum Oscillators to identify high-probability entry points. 1. Trend Filter: Uses EMA and volatility bands to filter out chop/noise. 2. Entry Logic: Enters trades only when momentum confirms the trend direction. 3. Exit Logic: Dynamic take-profit and stop-loss levels based on market volatility (ATR). █ Key Features • NO Repainting: All signals are confirmed on 'Bar Close'. The backtest results match live execution. • Dual Modes Included: - Aggressive Mode: Compounding logic for maximizing growth. - Safe Mode: Fixed risk management for capital preservation. • Risk Management: Includes a daily drawdown limit and automated crash protection. █ How to Use 1. Apply this strategy to the ETHUSDT chart. 2. Choose your mode in the settings (Aggressive or Safe). 3. Set up alerts for automation (compatible with 3Commas/Whop). ------------------------------------------------------------- ------------------------------------------------------------- 🔒 HOW TO GET ACCESS This is an Invite-Only script. To get access to this strategy, please check the link in my or below. 👇 (Access is managed via Whop subscription for instant authorization.) -------------------------------------------------------------
Estratégia Pine Script®
por iloveseoha0822
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.
Estratégia Pine Script®
por jac888178
4
Momentum Fusion X StrategyMomentum Fusion X Strategy — Conceptual Overview Momentum Fusion X Strategy is a selectively reactive market-participation system designed to engage only when price behavior exhibits structured directional clarity across multiple internal evaluation layers. Rather than responding to isolated indicators or short-term noise, the strategy operates on a confirmation-based framework where trades are activated only when the broader internal state of the market demonstrates sufficient directional agreement. This approach intentionally prioritizes quality of participation over frequency, allowing the system to remain inactive during uncertain or low-information phases. The strategy has demonstrated its strongest performance characteristics on MIDCAPNIFTY, while remaining structurally adaptable to other instruments and market environments. Structural Philosophy The internal architecture is built around a multi-layered decision model: Directional Consensus Framework Trades are considered only when multiple independent internal components align in the same directional bias. No single condition is capable of triggering a trade independently. Momentum Confirmation Logic Price movement is evaluated in a manner that emphasizes continuation strength rather than short-lived reactions. This helps reduce participation during false breakouts or choppy market behavior. Noise Suppression The system actively filters out ambiguous conditions, remaining flat during periods where directional intent lacks clarity or conviction. This structural discipline ensures consistency and prevents over-trading, particularly on lower timeframes. Trade Behaviour & Execution Trade Initiation Positions are initiated only when internal directional alignment reaches a predefined quality threshold. Partial or conflicting conditions are intentionally ignored. Trade Exit Positions are closed dynamically when internal momentum deteriorates or when directional alignment weakens, helping limit exposure during transitions or reversals. Market Inactivity On a 1-minute timeframe, the strategy may show fewer trades in backtests. This is by design and reflects strict filtering rather than missed opportunities, especially given the limited historical depth of 1-minute candle data. Automation & Execution Support The script includes a built-in Dhan webhook alert system, allowing traders to automate execution workflows if desired. Alerts are aligned directly with the strategy’s internal execution logic to maintain consistency between backtest behavior and live alert triggers. Commission and slippage are factored into the strategy configuration to provide a more realistic simulation of execution conditions. Commission: 0.01% Slippage: 2 points Intended Usage Context Timeframe: 1-Minute Performance Note: Best observed on MIDCAPNIFTY, while remaining adaptable across markets Trading Style: Intraday, momentum-based participation Trade Frequency: Selective by design (lower frequency on lower timeframes) Users are encouraged to apply independent capital allocation, position sizing, and risk controls appropriate to their trading plan. Intellectual Property Notice The internal construction, scoring logic, alignment thresholds, and execution conditions are intentionally abstracted. This description explains the conceptual philosophy without exposing implementation details, preserving the originality and intellectual integrity of the strategy. Direct replication of the internal logic is neither implied nor supported by this publication. Disclaimer This strategy is provided strictly for educational, research, and analytical purposes. Market behavior evolves over time, and historical performance does not guarantee future results. Users are responsible for forward testing, execution decisions, and risk management when applying this strategy in live market conditions.
Estratégia Pine Script®
por algovisionx2
EMA Pullback & Dual Crossover Pro Strategy,EMA Pullback & Dual Crossover Pro Strategy, (EMA 20 / 50 / 200 Trend-Based System) 🔍 Strategy Overview The EMA Pullback & Dual Crossover Pro Strategy is a trend-following and trend-reversal trading system designed to capture high-probability entries while filtering out low-quality trades during market noise. The strategy combines: Trend continuation trades using EMA 20/50 pullbacks Major trend reversal trades using EMA 20/200 crossovers A smart EMA 200 trend filter is applied only to pullback trades, ensuring trades align with the dominant market direction. This hybrid approach allows the strategy to perform well in: Strong trending markets Early trend reversals Controlled pullback environments 📐 Indicators Used Indicator Purpose EMA 20 Fast momentum & entry timing EMA 50 Pullback structure EMA 200 Long-term trend direction 🧠 Strategy Logic Breakdown 1️⃣ Trend Definition (EMA 200) The EMA 200 defines the dominant market trend: Bullish Trend → Price above EMA 200 Bearish Trend → Price below EMA 200 This trend filter is only applied to EMA 20/50 trades. 2️⃣ EMA 20 / 50 Pullback Trades (Trend Continuation) These trades capture pullbacks within an existing trend. 🔼 BUY Conditions (20/50 Pullback) EMA 20 crosses above EMA 50 Price is above EMA 200 Close confirms above EMA 20 Trade triggers after confirmation bars 🔽 SELL Conditions (20/50 Pullback) EMA 20 crosses below EMA 50 Price is below EMA 200 Close confirms below EMA 20 Trade triggers after confirmation bars 🛑 Counter-trend 20/50 trades are blocked automatically. 3️⃣ EMA 20 / 200 Crossover Trades (Trend Reversal) These trades capture major market reversals and breakouts. 🔼 BUY Conditions (20/200 Crossover) EMA 20 crosses above EMA 200 Close confirms above EMA 20 🔽 SELL Conditions (20/200 Crossover) EMA 20 crosses below EMA 200 Close confirms below EMA 20 🚀 These trades are not trend-filtered to allow early participation in new trends. ⏱ Confirmation Logic To reduce false signals: Entries are triggered only after confirmation bars Price must close in the direction of the trade Prevents wick-based and noise-induced entries ⚙️ Strategy Settings Parameter Description EMA 20 / 50 / 200 Adjustable lengths Confirmation Bars Signal validation Enable 20/50 Trades Toggle pullback trades Enable 20/200 Trades Toggle reversal trades EMA 200 Trend Filter Applies to 20/50 only 🎯 Trade Types Summary Trade Type Purpose Trend Filter EMA 20/50 Trend continuation (pullback) ✅ Yes EMA 20/200 Trend reversal / breakout ❌ No 📊 Best Use Cases Markets: XAUUSD, Indices, Major Forex Pairs Timeframes: M5, M15, H1 Market Conditions: Trending & breakout environments ⚠️ Risk Disclaimer This strategy is designed for systematic trading and should be used with: Proper risk management Fixed position sizing Stop-loss rules defined by the trader Backtesting and forward testing are strongly recommended before live deployment. 🧩 Final Notes This strategy is structured like a professional institutional system: One engine captures trend pullbacks One engine captures trend shifts Noise is filtered using EMA structure and confirmations It is not a scalping bot, but a trend-aligned trading framework suitable for disciplined traders.
Estratégia Pine Script®
por Nielesh
Sentiment Trader v4.1 StrategySentiment Trader v4.1 Strategy — How to use Purpose: A rules-based BTC/ETH daily strategy that combines multiple market regime inputs (trend zones, funding conditions, SOPR, and BPS-style signals) to plot clear Long / Short entries and trailing-stop based exits. 1) Required setup (important) Preset : Select your market via the Strategy input: BTC 1D → requires BITSTAMP:BTCUSD ETH 1D → requires BITSTAMP:ETHUSD Timeframe : 1D (Daily) . Chart type : Standard candles or line (avoid non-standard chart types). If you select the wrong symbol / timeframe / chart type, the script shows an on-chart warning message and signals may be missing. 2) What you see on the chart Long : blue triangle below the candle. Short : pink/red triangle above the candle. Long Close : X marker (exit) after a long position. Short Close : X marker (exit) after a short position. Trailing Stop lines : TSL Long (aqua): trailing stop reference for long positions TSL Short (red): trailing stop reference for short positions 3) Practical usage (simple) Start with the correct setup (symbol + Daily + standard chart). Treat signals as a system : avoid mixing entries/exits with unrelated intraday signals (this is designed for daily regimes). Use risk management : position sizing, max drawdown rules, and (if trading manually) your own execution discipline. 4) Backtesting period (built-in) Customize strategy tool for a specific time period : limits entries to your chosen start/end dates. Tip : Avoid TradingView “deep backtesting” for this script — it can cut off previously collected data and distort signal calculation. 5) Data dependencies This strategy references external series such as GLASSNODE:* and CRYPTOCAP:USDT.D . If your TradingView plan/exchange access does not provide these series, results may differ or parts may not work. 6) Alerts + automation note (important) TradingView’s Terms of Use state that TradingView market data (including charts, alerts, and webhooks) is licensed for display-only use and prohibits non-display usage , including automated trading / automated order generation and similar machine-driven processing. Please review the current policy text before using alerts with any third-party tooling: tradingview.com/policies . If you want a free walkthrough on understanding the signals and setting up alerts/notifications, you can visit our website: algoros.ai Notes / expectations This is not financial advice. Past performance is not indicative of future results.
Estratégia Pine Script®
por algoros
Trend Reversal X StrategyTrend Reversal X Strategy Trend Reversal X Strategy is a directional participation framework that engages only when price demonstrates sustained, validated directional movement. Unlike reactive or time-based systems that respond to every minor fluctuation, this strategy evaluates internal price behavior to ensure trades occur only under conditions likely to reflect meaningful market commitment. Random or weak fluctuations are ignored, emphasizing quality directional opportunities over trade frequency. Structural Design The framework interprets market movement through discrete directional states rather than raw time-based changes: Directional Progression: Price is analyzed to confirm consistent movement in one direction, ensuring minor counter-moves do not trigger entries. State Confirmation: Each step is internally evaluated, and trades are initiated only when directional progression reaches a meaningful threshold. Quality Filtering: The system avoids ambiguous setups, reducing the likelihood of entering trades in low-conviction or erratic conditions. This ensures no single minor movement can initiate a trade, maintaining disciplined and consistent execution. Trade Dynamics Trade Activation: Trades are triggered only when price demonstrates confirmed directional progression over consecutive evaluation states. Partial or sporadic movements are ignored. Trade Closure: Positions close when directional progression weakens or opposing movement dominates. This ensures that exposure is limited to periods of strong directional clarity. Market Inactivity: The system remains passive during low volatility, indecision, or ambiguous market conditions, minimizing unnecessary risk and overtrading. Backtesting Context Strategy execution is restricted to October 2022 onward, reflecting current market directional patterns and volatility. Older market regimes, which may not align with present-day conditions, are intentionally excluded. This provides a realistic and relevant evaluation of performance. Intended Use Instruments: Liquid indices (example: MIDCAPNIFTY) Timeframe: 15-Minute Application: Intraday and short-term directional observation Risk Management: Users should apply independent position sizing, capital allocation, and stop-loss rules Strict adherence to signals is recommended to preserve model integrity. Intellectual Property Notice Internal evaluation methodology, state thresholds, and activation logic are abstracted to protect originality. Conceptual framework is visible, but internal mechanics are intentionally obfuscated, preventing mechanical replication. Disclaimer This strategy is provided for educational, research, and demonstration purposes only. Market conditions evolve, and past performance does not guarantee future results. Users are responsible for forward-testing and applying appropriate capital and risk management before live execution. 🔹 Moderator-Friendly Expanded Summary Instrument & Timeframe: Liquid indices (example: MIDCAPNIFTY), 15-Minute Start Date: October 2022 onward Position Size: 1 lot / fixed quantity Initial Capital: ₹100,000 Commission & Slippage: 0.01% commission, 2-point slippage Trade Logic: Internal directional state evaluation across discrete price progression Trade Activation: Trades occur only after confirmed directional progression Trade Closure: Positions closed when directional integrity weakens or reverses Market Inactivity: System remains inactive during low-clarity or low-volatility conditions Risk Management: Users responsible for stop-loss, capital allocation, and position-sizing IP Justification: Internal evaluation and thresholds abstracted to protect originality Purpose: Educational, research, and demonstration only
Estratégia Pine Script®
por AlgoVisionX
1
Quantum X StrategyQuantum X Strategy — Expanded Description Quantum X Strategy is a carefully structured market-participation framework, designed to initiate trades only when strong directional alignment is detected across multiple independent market dimensions. Unlike reactive or single-indicator systems, this strategy evaluates the overall market context to ensure participation only occurs under conditions that have a higher probability of meaningful directional movement. Random or partial signals are ignored, with the system prioritizing structured, high-quality opportunities over frequency of trades. Structural Design The strategy’s decision-making process is based on a multi-dimensional analysis of price behavior: Directional Alignment: The system monitors multiple market behaviors to determine whether they collectively indicate bullish or bearish intent. Weighted Contribution: Each contributing factor is scored independently, and trades are considered only when the combined state reaches a meaningful threshold. Quality Filtering: The model filters out low-quality setups, minimizing the chance of entering trades in ambiguous or volatile conditions without sufficient confirmation. This design ensures that no single signal can trigger a trade independently, maintaining structural discipline and consistency in execution. Trade Dynamics Trade Activation: Trades are executed only when the internal alignment reaches a significant level of directional agreement. Sporadic or incomplete signals are ignored, ensuring that only setups with sufficient conviction are considered. Trade Closure: Positions are closed when the internal momentum alignment deteriorates or when a reversal in trend bias is detected. This dynamic exit approach prevents unnecessary exposure during weak market conditions. Market Inactivity: The system remains passive during periods of indecision, low volatility, or ambiguous market behavior. By staying inactive during such phases, the strategy reduces risk and avoids overtrading. Backtesting Context The strategy’s execution is restricted to post-2025 market data, ensuring that its performance reflects recent structural patterns and volatility behavior. Older market regimes, which may not be representative of current conditions, are intentionally excluded from analysis. This approach provides a realistic and relevant evaluation of the strategy’s effectiveness in today’s market environment. Intended Use Instrument: MIDCAPNIFTY Timeframe: 15-Minute Application: Suitable for intraday trading and short-term directional observation Risk Management: Designed to be used in conjunction with independent position sizing, stop-loss, and capital allocation discipline This system is most effective when traders maintain strict adherence to its entry and exit signals, avoiding discretionary overrides that could compromise the model’s integrity. Intellectual Property Notice The internal scoring methodology, alignment logic, and activation thresholds are intentionally abstracted to protect the originality and intellectual property of the strategy. The design prevents direct replication while still allowing traders and moderators to understand the conceptual framework behind its decisions. Disclaimer This strategy is provided strictly for educational, research, and backtesting purposes only. Market conditions evolve, and past performance does not guarantee future results. Traders are responsible for forward-testing and applying their own capital, risk, and position-sizing controls before implementing any live trades. 🔹 Moderator-Friendly Expanded Summary Instrument & Timeframe: MIDCAPNIFTY, 15-Minute Start Date: January 2025 onward Position Size: 1 lot / fixed quantity Initial Capital: ₹100,000 Commission & Slippage: 0.01% commission, 2-point slippage Trade Logic: Internal alignment model evaluating multiple independent market behaviors Trade Activation: Trades executed only when internal directional consensus reaches a significant threshold Trade Closure: Positions closed when alignment weakens or trend bias shifts Market Inactivity: System remains inactive during ambiguous, low-information, or low-volatility periods Risk Management: Users are encouraged to define stop-loss, capital allocation, and position-sizing according to personal risk tolerance IP Justification: Internal scoring, alignment logic, and thresholds are abstracted to maintain strategy originality Purpose: Strictly educational, research, and demonstration use only
Estratégia Pine Script®
por AlgoVisionX
Panic Spike Reversal Strategy | KR3000Panic Spike Reversal Strategy | KR3000 This is a highly attractive yet dangerous trading tool, designed for traders who understand risk and are willing to face it. The core idea is simple but powerful: when the market experiences an abnormal surge or collapse within a higher timeframe, this strategy identifies those panic-driven spikes and enters against the move, aiming to capture the natural price mean reversion that often follows extreme emotional behavior. This strategy is not designed for comfort. It is designed for discipline, execution, and courage. 🔍 What This Strategy Does Monitors a higher timeframe (e.g. 1H) in real time Detects sharp upward or downward price spikes based on user-defined percentage thresholds Automatically enters contrarian positions: Spike up → Short Spike down → Long Optionally allows both directions within the same monitoring bar, selecting the stronger extreme when both occur Executes all entries only after bar close, ensuring non-repainting behavior Uses fixed percentage-based take profit and stop loss, fully adjustable by the user Limits signals to one trigger per monitoring timeframe bar (optional), preventing overtrading ⚙️ Core Logic & Principles Markets do not move in straight lines. Extreme moves are often driven by fear, greed, and forced liquidity, not balanced price discovery. This strategy is built on the assumption that: Violent price expansions are statistically unstable Panic moves frequently overextend, creating short-term opportunities in the opposite direction However, mean reversion is not guaranteed. This is why strict stop loss control is essential and fully configurable. ⚠️ Risk Warning This is a contrarian strategy by nature. It intentionally trades against strong momentum Losses can occur quickly if the trend continues It is not suitable for beginners Best used by experienced traders who understand: market structure volatility behavior and emotional discipline If you are looking for safety, this strategy is not for you. If you are looking for controlled danger with defined risk, this tool may be worth your attention. 🧠 Who This Strategy Is For Traders who specialize in mean reversion or fade setups Instruments with high liquidity and volatility (e.g. indices, gold, FX majors) Users who value transparent logic, non-repainting signals, and full parameter control Traders who accept that high reward potential comes with high psychological pressure
Estratégia Pine Script®
por Kr-3000
Market Dynamics - Backtest Engine [NeuraAlgo]Market Dynamics – Backtest Engine Market Dynamics – Backtest Engine is an advanced research-grade trading framework engineered by NeuraAlgo. 🔹 Core Engine – Dynamic Trend Model The strategy leverages the NeuraAlgo – Market Dynamics indicator as its foundation, providing intelligent insights to guide trading decisions. It is designed to automatically identify the optimal settings for the NeuraAlgo – Market Dynamics indicator, helping traders fine-tune their strategy for maximum efficiency, accuracy, and profitability. This engine dynamically adapts to market conditions, ensuring your strategy stays optimized in real-time. 🔹 Optimization Engine A built-in optimization module allows automatic testing of: Winrate-focused configurations Profit-focused configurations Sensitivity ranges Step sizes Main Entry, Main Filter, Feature Filter, and Risk Manager categories This enables rapid identification of optimal parameters similar to a lightweight AI optimizer. This Backtesting + Auto Optimization Engine includes an integrated optimizer that automatically tests sensitivity ranges: Maximize Winrate Maximize Profits Optimize Main Entries, Risk Manager, or Feature Filters Users can set: start sensitivity step size parameter category The engine autonomously computes which parameter delivers the strongest performance. 🔹 How To Use 1. Identify the Parameters First, you need to know which indicator parameters can be optimized. For the NeuraAlgo – Market Dynamics indicator, these might include: Trend sensitivity Smoothing periods Threshold values for bullish/bearish signals These parameters are the inputs your engine will test. 2. Define a Range For each parameter, define a range of values to test. Example: Sensitivity: 2 → 10 Trend period: 14 → 50 Threshold: 0.1 → 1.0 The more granular the range, the more precise the optimization—but it will also take longer. 3. Run Backtest Optimization Attach the strategy to a chart. Select optimization mode in your engine (or set the range for each parameter). Start the backtest: the engine will simulate trades for every combination of parameter values. The system will automatically record key metrics for each run: Net profit Win rate Profit factor Max drawdown 4. Analyze the Results After the backtest, your engine will display a results table or chart showing performance for each parameter combination. Look for: Highest net profit Highest win rate Or a combination depending on your strategy goals Some engines will highlight the “best” parameter set automatically. 5. Apply Optimal Settings Once identified: Select the best-performing parameter values. Apply them to your live strategy or paper trade. Optionally, forward test to confirm they work on unseen market data. Congratulations! The setup is now optimized. 🔹 Conclusion The backtest optimization process helps you find the best parameter values for the NeuraAlgo – Market Dynamics indicator by systematically testing different settings and measuring their performance. By analyzing metrics like net profit, win rate, and drawdown, you can select optimized parameters that are more likely to perform consistently in real trading. Proper optimization ensures your strategy is data-driven, adaptable, and reduces guesswork, giving you a stronger edge in the market.
Estratégia Pine Script®
por NeuraAlgo
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙 1. Executive Summary & Architecture Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm. The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed. Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events. 2. ⚠️ The Philosophy of "Curve Fitting" (Must Read) One must be careful when applying Gypsy Bot to new pairs or charts. To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure. To use this engine successfully, you must adopt a specific optimization mindset: Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless. Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve. Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility. Timeframe Recommendations: Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets. 3. The Voting Mechanism: How Entries Are Generated The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings). The engine constantly monitors the output of all enabled Modules. Long Votes: GoLongCount Short Votes: GoShortCount If you have 10 Modules enabled, and you set ActivateOrders to 7: The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle. If only 6 modules agree, the trade is rejected. This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment. 4. Technical Deep Dive: The 12 Modules Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading. Module 1: Modified Slope Angle (MSA) Logic: Calculates the geometric angle of a moving average relative to the timeline. Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal. Module 2: Correlation Trend Indicator (CTI) Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend). Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs. Module 3: Ehlers Roofing Filter Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise). Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react. Module 4: Forecast Oscillator Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is. Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module. Module 5: Chandelier ATR Stop Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts). Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support. Module 6: Crypto Market Breadth (CMB) Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges. Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset. Module 7: Directional Index Convergence (DIC) Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices. Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum. Module 8: Market Thrust Indicator (MTI) Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data. Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart. Module 9: Simple Ichimoku Cloud Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen. Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module. Module 10: Simple Harmonic Oscillator Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms. Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up. Module 11: HSRS Compression / Super AO Logic: Two options in one. HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands. Super AO: A combination of the Awesome Oscillator and SuperTrend logic. Function: Great for catching explosive moves that result from periods of low volatility (consolidation). Module 12: Fisher Transform (MTF) Logic: Converts price data into a Gaussian normal distribution. Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend. 5. Global Inhibitors (The Veto Power) Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked. Bitcoin Halving Logic: Hardcoded dates for past and projected future Bitcoin halvings (up to 2040). Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes. Miner Capitulation: Uses Hash Rate Ribbons (Moving averages of Hash Rate). If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat. ADX Filter (Flat Market Protocol): If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market. CryptoCap Trend: Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins. 6. Risk Management & The Dump Protection Team (DPT) Gypsy Bot separates "Entry Logic" from "Risk Management Logic." Dump Protection Team (DPT) This is a specialized logic branch designed to save the account during Black Swan events. Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit. Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction. Advanced Adaptive Trailing Stop (AATS) Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic. Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks. Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital. Staged Take Profits TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win. TP2: Take the bulk of profit. TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves. 7. Recommended Setup Guide When applying Gypsy Bot to a new chart, follow this sequence: Set Timeframe: 4 Hours (4H). Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first). Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance. Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended). Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging). Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative). Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade. 8. Technical Specs Engine Version: Pine Script V6 Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals). Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode. Disclaimer: This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it. 9. About Signal Lynx Automation for the Night-Shift Nation 🌙 Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management. We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to: Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search. License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Estratégia Pine Script®
por SignalLynx
1
Momentum Reversal / Dip Buyer [Score Based]Strategy Overview Momentum Reversal / Dip Buyer is a quantitative reversal engine designed to fade stretched moves and buy dips / sell rallies when multiple momentum and context factors line up. It’s built for liquid instruments especially for ticker CME_MINI:ES1! and works best on intraday timeframes like the 5-minute or 1-minute chart. Core Logic This strategy builds a composite Momentum Score by combining: Price Location: Relative to 100 SMA, 1000 EMA, and VWAP (trend / regime filter). RSI: Overbought/oversold and mid-zone strength. VWMO (Volume-Weighted Momentum): Direction and strength of volume-weighted price drift. ADX: Trend strength filter (high vs low trend environment). Full Stoch (%K): Short-term exhaustion and mean-reversion context. CCI: Overbought/oversold turns (key trigger). MFI: Volume-confirmed buying/selling pressure. ATR Regime: High vs low volatility environment. Cumulative Delta: Whether net aggressor flow is rising or falling. From this, a single Momentum Score is computed each bar: Longs: Taken when the score is depressed (scoreLow) and CCI crosses up from oversold. Shorts: Taken when the score is elevated (scoreHigh) and CCI crosses down from overbought. Risk Management & Trade Logic Max Daily Trades: Hard cap on entries per day. Hard Stop: Fixed % stop based on entry price. Profit Target: Target ATR Multiplier × main ATR from entry. Breakeven Logic: Optional; moves stop to breakeven (plus optional offset) after price moves a configurable multiple of the main ATR in your favor. Trailing Stop (Separate ATR): Optional; uses its own ATR length and ATR-based trigger and distance. This lets you run slower ATR for targets while using a tighter, more reactive ATR for the trail. Session Control Trading Window: Optional session filter (e.g., 09:30–16:00). Entries are only allowed inside the defined window. Force Flat at Session End: Option to automatically close all open positions when the session ends. Visuals The script plots entry arrows and a compact dashboard displaying: current Momentum Score, daily trade usage, and CCI status. Disclaimer: This script is for educational and research purposes only and is not financial advice. Past performance does not guarantee future results. Always forward-test and adjust parameters to your own risk tolerance and market. Shoutout and all credit goes to AuclairsCapital for building the base foundation of this strategy on ThinkScript
Estratégia Pine Script®
por TheTRADRS
BTC Fear & Greed Incremental StrategyIMPORTANT: READ SETUP GUIDE BELOW OR IT WON'T WORK # BTC Fear & Greed Incremental Strategy — TradeMaster AI (Pure BTC Stack) ## Strategy Overview This advanced Bitcoin accumulation strategy is designed for long-term hodlers who want to systematically take profits during greed cycles and accumulate during fear periods, while preserving their core BTC position. Unlike traditional strategies that start with cash, this approach begins with a specified BTC allocation, making it perfect for existing Bitcoin holders who want to optimize their stack management. ## Key Features ### 🎯 **Pure BTC Stack Mode** - Start with any amount of BTC (configurable) - Strategy manages your existing stack, not new purchases - Perfect for hodlers who want to optimize without timing markets ### 📊 **Fear & Greed Integration** - Uses market sentiment data to drive buy/sell decisions - Configurable thresholds for greed (selling) and fear (buying) triggers - Automatic validation to ensure proper 0-100 scale data source ### 🐂 **Bull Year Optimization** - Smart quarterly selling during bull market years (2017, 2021, 2025) - Q1: 1% sells, Q2: 2% sells, Q3/Q4: 5% sells (configurable) - **NO SELLING** during non-bull years - pure accumulation mode - Preserves BTC during early bull phases, maximizes profits at peaks ### 🐻 **Bear Market Intelligence** - Multi-regime detection: Bull, Early Bear, Deep Bear, Early Bull - Different buying strategies based on market conditions - Enhanced buying during deep bear markets with configurable multipliers - Visual regime backgrounds for easy market condition identification ### 🛡️ **Risk Management** - Minimum BTC allocation floor (prevents selling entire stack) - Configurable position sizing for all trades - Multiple safety checks and validation ### 📈 **Advanced Visualization** - Clean 0-100 scale with 2 decimal precision - Three main indicators: BTC Allocation %, Fear & Greed Index, BTC Holdings - Real-time portfolio tracking with cash position display - Enhanced info table showing all key metrics ## How to Use ### **Step 1: Setup** 1. Add the strategy to your BTC/USD chart (daily timeframe recommended) 2. **CRITICAL**: In settings, change the "Fear & Greed Source" from "close" to a proper 0-100 Fear & Greed indicator --------------- I recommend Crypto Fear & Greed Index by TIA_Technology indicator When selecting source with this indicator, look for "Crypto Fear and Greed Index:Index" --------------- 3. Set your "Starting BTC Quantity" to match your actual holdings 4. Configure your preferred "Start Date" (when you want the strategy to begin) ### **Step 2: Configure Bull Year Logic** - Enable "Bull Year Logic" (default: enabled) - Adjust quarterly sell percentages: - Q1 (Jan-Mar): 1% (conservative early bull) - Q2 (Apr-Jun): 2% (moderate mid bull) - Q3/Q4 (Jul-Dec): 5% (aggressive peak targeting) - Add future bull years to the list as needed ### **Step 3: Fine-tune Thresholds** - **Greed Threshold**: 80 (sell when F&G > 80) - **Fear Threshold**: 20 (buy when F&G < 20 in bull markets) - **Deep Bear Fear Threshold**: 25 (enhanced buying in bear markets) - Adjust based on your risk tolerance ### **Step 4: Risk Management** - Set "Minimum BTC Allocation %" (default 20%) - prevents selling entire stack - Configure sell/buy percentages based on your position size - Enable bear market filters for enhanced timing ### **Step 5: Monitor Performance** - **Orange Line**: Your BTC allocation percentage (target: fluctuate between 20-100%) - **Blue Line**: Actual BTC holdings (should preserve core position) - **Pink Line**: Fear & Greed Index (drives all decisions) - **Table**: Real-time portfolio metrics including cash position ## Reading the Indicators ### **BTC Allocation Percentage (Orange Line)** - **100%**: All portfolio in BTC, no cash available for buying - **80%**: 80% BTC, 20% cash ready for fear buying - **20%**: Minimum allocation, maximum cash position ### **Trading Signals** - **Green Buy Signals**: Appear during fear periods with available cash - **Red Sell Signals**: Appear during greed periods in bull years only - **No Signals**: Either allocation limits reached or non-bull year ## Strategy Logic ### **Bull Years (2017, 2021, 2025)** - Q1: Conservative 1% sells (preserve stack for later) - Q2: Moderate 2% sells (gradual profit taking) - Q3/Q4: Aggressive 5% sells (peak targeting) - Fear buying active (accumulate on dips) ### **Non-Bull Years** - **Zero selling** - pure accumulation mode - Enhanced fear buying during bear markets - Focus on rebuilding stack for next bull cycle ## Important Notes - **This is not financial advice** - backtest thoroughly before use - Designed for **long-term holders** (4+ year cycles) - **Requires proper Fear & Greed data source** - validate in settings - Best used on **daily timeframe** for major trend following - **Cash calculations**: Use allocation % and BTC holdings to calculate available cash: `Cash = (Total Portfolio × (1 - Allocation%/100))` ## Risk Disclaimer This strategy involves active trading and position management. Past performance does not guarantee future results. Always do your own research and never invest more than you can afford to lose. The strategy is designed for educational purposes and long-term Bitcoin accumulation thesis. --- *Developed by Sol_Crypto for the Bitcoin community. Happy stacking! 🚀*
Estratégia Pine Script®
por Sol_Crypto
1
Adaptive Averaging Concept [NeuraAlgo]Adaptive Averaging Concept A Quant-Engineered Dynamic Position Sizing & Optimization Framework Adaptive Averaging Concept™ is a next-generation, research-driven trading framework that combines multistage entries, ATR-based intelligent scaling, real-time sentiment filtering, and a fully automated optimization engine. It is designed for traders who want precision execution, adaptive risk control, and an architecture capable of learning from market structure. 🔹 Core Concept Unlike traditional averaging or DCA methods, this engine uses Adaptive Averaging — a controlled, mathematically tuned accumulation system that adjusts entries based on volatility, trend conditions, and signal confidence. Each additional entry intelligently recalculates average price and updates a volatility-sensitive dynamic Take Profit. 🔹 Main Features 1. Intelligent Multi-Stage Entry System Initial entries triggered by SMA crossover, rising volume, or Always-On mode Secondary entries triggered only when price retraces by a volatility-adjusted threshold Every added position recalculates: Total quantities Capital distribution Average price Adaptive Take Profit (ATR-based) 2. Adaptive Risk & Position Management ATR-driven take-profit using Exit Sensitivity ATR-driven add-entry logic using Exit Tuner Dynamic or Fixed lot sizing Capital-per-entry control Automatic minimum lot protection 3. High-Level Market Filters Trend Filter A volatility-normalized EMA slope filter that identifies: 1.Bullish trend 2.Bearish trend 3.Neutral trend Sentiment Cloud Filter A structural sentiment engine analyzing: 1.Micro-gaps 2.Bull and bear pressure 3.Range compression 4.Market regime bias Trades only execute when filters align with your directional bias. 4. NeuraAlgo Optimization Engine The strategy includes a built-in optimizer allowing you to test & tune with no loops and no external computation. You can automatically optimize: Smooth Period (ATR) Exit Sensitivity Exit Tuner SMA Period Trend Filter Length Trend Filter Smooth Sentiment Cloud Period Optimization Goals: Maximize Winrate Maximize Net Profits This allows the strategy to self-configure based on live market conditions. Here, the optimization is finally complete. 🔹 Summary Adaptive Averaging Concept™ is not a simple indicator or basic DCA script. It is a complete quant-grade execution engine capable of dynamically adjusting its behavior to volatility, price structure, trend strength, and sentiment. Engineered for traders who demand: High-precision entry logic Adaptive position sizing Volatility-calibrated exits Smart accumulation Built-in optimization Professional-grade backtesting It is a powerful framework suitable for swing traders, intraday traders, and automated system developers.
Estratégia Pine Script®
por NeuraAlgo
2
Superior-Range Bound Renko - Strategy - 11-29-25 - SignalLynxSuperior-Range Bound Renko Strategy with Advanced Risk Management Template Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙 1. Overview Welcome to Superior-Range Bound Renko (RBR) — a volatility-aware, structure-respecting swing-trading system built on top of a full Risk Management (RM) Template from Signal Lynx. Instead of relying on static lookbacks (like “14-period RSI”) or plain MA crosses, Superior RBR: Adapts its range definition to market volatility in real time Emulates Renko Bricks on a standard, time-based chart (no Renko chart type required) Uses a stack of Laguerre Filters to detect genuine impulse vs. noise Adds an Adaptive SuperTrend powered by a small k-means-style clustering routine on volatility Under the hood, this script also includes the full Signal Lynx Risk Management Engine: A state machine that separates “Signal” from “Execution” Layered exit tools: Stop Loss, Trailing Stop, Staged Take Profit, Advanced Adaptive Trailing Stop (AATS), and an RSI-style stop (RSIS) Designed for non-repainting behavior on closed candles by basing execution-critical logic on previous-bar data We are publishing this as an open-source template so traders and developers can leverage a professional-grade RM engine while integrating their own signal logic if they wish. 2. Quick Action Guide (TL;DR) Best Timeframe: 4 Hours (H4) and above. This is a high-conviction swing-trading system, not a scalper. Best Assets: Volatile instruments that still respect market structure: Bitcoin, Ethereum, Gold (XAUUSD), high-volatility Forex pairs (e.g., GBPJPY), indices with clean ranges. Strategy Type: Volatility-Adaptive Trend Following + Impulse Detection. It hunts for genuine expansion out of ranges, not tiny mean-reversion nibbles. Key Feature: Renko Emulation on time-based candles. We mathematically model Renko Bricks and overlay them on your standard chart to define: “Equilibrium” zones (inside the brick structure) “Breakout / impulse” zones (when price AND the impulse line depart from the bricks) Repainting: Designed to be non-repainting on closed candles. All RM execution logic uses confirmed historical data (no future bars, no security() lookahead). Intrabar flicker during formation is allowed, but once a bar closes the engine’s decisions are stable. Core Toggles & Filters: Enable Longs and Shorts independently Optional Weekend filter (block trades on Saturday/Sunday) Per-module toggles: Stop Loss, Trailing Stop, Staged Take Profits, AATS, RSIS 3. Detailed Report: How It Works A. The Strategy Logic: Superior RBR Superior RBR builds its entry signal from multiple mathematical layers working together. 1) Adaptive Lookback (Volatility Normalization) Instead of a fixed 100-bar or 200-bar range, the script: Computes ATR-based volatility over a user-defined period. Normalizes that volatility relative to its recent min/max. Maps the normalized value into a dynamic lookback window between a minimum and maximum (e.g., 4 to 100 bars). High Volatility: The lookback shrinks, so the system reacts faster to explosive moves. Low Volatility: The lookback expands, so the system sees a “bigger picture” and filters out chop. All the core “Range High/Low” and “Range Close High/Low” boundaries are built on top of this adaptive window. 2) Range Construction & Quick Ranges The engine constructs several nested ranges: Outer Range: rangeHighFinal – dynamic highest high rangeLowFinal – dynamic lowest low Inner Close Range: rangeCloseHighFinal – highest close rangeCloseLowFinal – lowest close Quick Ranges: “Half-length” variants of those, used to detect more responsive changes in structure and volatility. These ranges define: The macro box price is trading inside Shorter-term “pressure zones” where price is coiling before expansion 3) Renko Emulation (The Bricks) Rather than using the Renko chart type (which discards time), this script emulates Renko behavior on your normal candles: A “brick size” is defined either: As a standard percentage move, or As a volatility-driven (ATR) brick, optionally inhibited by a minimum standard size The engine tracks a base value and derives: brickUpper – top of the emulated brick brickLower – bottom of the emulated brick When price moves sufficiently beyond those levels, the brick “shifts”, and the directional memory (renkoDir) updates: renkoDir = +2 when bricks are advancing upward renkoDir = -2 when bricks are stepping downward You can think of this as a synthetic Renko tape overlaid on time-based candles: Inside the brick: equilibrium / consolidation Breaking away from the brick: momentum / expansion 4) Impulse Tracking with Laguerre Filters The script uses multiple Laguerre Filters to smooth price and brick-derived data without traditional lag. Key filters include: LagF_1 / LagF_W: Based on brick upper/lower baselines LagF_Q: Based on HLCC4 (high + low + 2×close)/4 LagF_Y / LagF_P: Complex averages combining brick structures and range averages LagF_V (Primary Impulse Line): A smooth, high-level impulse line derived from a blend of the above plus the outer ranges Conceptually: When the impulse line pushes away from the brick structure and continues in one direction, an impulse move is underway. When its direction flips and begins to roll over, the impulse is fading, hinting at mean reversion back into the range. 5) Fib-Based Structure & Swaps The system also layers in Fib levels derived from the adaptive ranges: Standard levels (12%, 23.6%, 38.2%, 50%, 61%, 76.8%, 88%) from the main range A secondary “swap” set derived from close-range dynamics (fib12Swap, fib23Swap, etc.) These Fibs are used to: Bucket price into structural zones (below 12, between 23–38, etc.) Detect breakouts when price and Laguerre move beyond key Fib thresholds Drive zSwap logic (where a secondary Fib set becomes the active structure once certain conditions are met) 6) Adaptive SuperTrend with K-Means-Style Volatility Clustering Under the hood, the script uses a small k-means-style clustering routine on ATR: ATR is measured over a fixed period The range of ATR values is split into Low, Medium, High volatility centroids Current ATR is assigned to the nearest centroid (cluster) From that, a SuperTrend variant (STK) is computed with dynamic sensitivity: In quiet markets, SuperTrend can afford to be tighter In wild markets, it widens appropriately to avoid constant whipsaw This SuperTrend-based oscillator (LagF_K and its signals) is then combined with the brick and Laguerre stack to confirm valid trend regimes. 7) Final Baseline Signals (+2 / -2) The “brain” of Superior RBR lives in the Baseline & Signal Generation block: Two composite signals are built: B1 and B2: They combine: Fib breakouts Renko direction (renkoDir) Expansion direction (expansionQuickDir) Multiple Laguerre alignments (LagF_Q, LagF_W, LagF_Y, LagF_Z, LagF_P, LagF_V) They also factor in whether Fib structures are expanding or contracting. A user toggle selects the “Baseline” signal: finalSig = B2 (default) or B1 (alternate baseline) finalSig is then filtered through the RM state machine and only when everything aligns, we emit: +2 = Long / Buy signal -2 = Short / Sell signal 0 = No new trade Those +2 / -2 values are what feed the Risk Management Engine. B. The Risk Management (RM) Engine This script features the Signal Lynx Risk Management Engine, a proprietary state machine built to separate Signal from Execution. Instead of firing orders directly on indicator conditions, we: Convert the raw signal into a clean integer (Fin = +2 / -2 / 0) Feed it into a Trade State Machine that understands: Are we flat? Are we in a long or short? Are we in a closing sequence? Should we permit re-entry now or wait? Logic Injection / Template Concept: The RM engine expects a simple integer: +2 → Buy -2 → Sell Everything else (0) is “no new trade” This makes the script a template: You can remove the Superior RBR block Drop in your own logic (RSI, MACD, price action, etc.) As long as you output +2 or -2 into the same signal channel, the RM engine can drive all exits and state transitions. Aggressive vs Conservative Modes: The input AgressiveRM (Aggressive RM) governs how we interpret signals: Conservative Mode (Aggressive RM = false): Uses a more filtered internal signal (AF) to open trades Effectively waits for a clean trend flip / confirmation before new entries Minimizes whipsaw at the cost of fewer trades Aggressive Mode (Aggressive RM = true): Reacts directly to the fresh alert (AO) pulses Allows faster re-entries in the same direction after RM-based exits Still respects your pyramiding setting; this script ships with pyramiding = 0 by default, so it will not stack multiple positions unless you change that parameter in the strategy() call. The state machine enforces discipline on top of your signal logic, reducing double-fires and signal spam. C. Advanced Exit Protocols (Layered Defense) The exit side is where this template really shines. Instead of a single “take profit or stop loss,” it uses multiple, cooperating layers. 1) Hard Stop Loss A classic percentage-based Stop Loss (SL) relative to the entry price. Acts as a final “catastrophic protection” layer for unexpected moves. 2) Standard Trailing Stop A percentage-based Trailing Stop (TS) that: Activates only after price has moved a certain percentage in your favor (tsActivation) Then trails price by a configurable percentage (ts) This is a straightforward, battle-tested trailing mechanism. 3) Staged Take Profits (Three Levels) The script supports three staged Take Profit levels (TP1, TP2, TP3): Each stage has: Activation percentage (how far price must move in your favor) Trailing amount for that stage Position percentage to close Example setup: TP1: Activate at +10% Trailing 5% Close 10% of the position TP2: Activate at +20% Trailing 10% Close another 10% TP3: Activate at +30% Trailing 5% Close the remaining 80% (“runner”) You can tailor these quantities for partial scaling out vs. letting a core position ride. 4) Advanced Adaptive Trailing Stop (AATS) AATS is a sophisticated volatility- and structure-aware stop: Uses Hirashima Sugita style levels (HSRS) to model “floors” and “ceilings” of price: Dungeon → Lower floors → Mid → Upper floors → Penthouse These levels classify where current price sits within a long-term distribution. Combines HSRS with Bollinger-style envelopes and EMAs to determine: Is price extended far into the upper structure? Is it compressed near the lower ranges? From this, it computes an adaptive factor that controls how tight or loose the trailing level (aATS / bATS) should be: High Volatility / Penthouse areas: Stop loosens to avoid getting wicked out by inevitable spikes. Low Volatility / compressed structure: Stop tightens to lock in and protect profit. AATS is designed to be the “smart last line” that responds to context instead of a single fixed percentage. 5) RSI-Style Stop (RSIS) On top of AATS, the script includes a RSI-like regime filter: A McGinley Dynamic mean of price plus ATR bands creates a dynamic channel. Crosses above the top band and below the lower band change a directional state. When enabled (UseRSIS): RSIS can confirm or veto AATS closes: For longs: A shift to bearish RSIS can force exits sooner. For shorts: A shift to bullish RSIS can do the same. This extra layer helps avoid over-reactive stops in strong trends while still respecting a regime change when it happens. D. Repainting Protection Many strategies look incredible in the Strategy Tester but fail in live trading because they rely on intrabar values or future-knowledge functions. This template is built with closed-candle realism in mind: The Risk Management logic explicitly uses previous bar data (open , high , low , close ) for the key decisions on: Trailing stop updates TP triggers SL hits RM state transitions No security() lookahead or future-bar access is used. This means: Backtest behavior is designed to match what you can actually get with TradingView alerts and live automation. Signals may “flicker” intrabar while the candle is forming (as with any strategy), but on closed candles, the RM decisions are stable and non-repainting. 4. For Developers & Modders We strongly encourage you to mod this script. To plug your own strategy into the RM engine: Look for the section titled: // BASELINE & SIGNAL GENERATION You will see composite logic building B1 and B2, and then selecting: baseSig = B2 altSig = B1 finalSig = sigSwap ? baseSig : altSig You can replace the content used to generate baseSig / altSig with your own logic, for example: RSI crosses MACD histogram flips Candle pattern detectors External condition flags Requirements are simple: Your final logic must output: 2 → Buy signal -2 → Sell signal 0 → No new trade That output flows into the RM engine via finalSig → AlertOpen → state machine → Fin. Once you wire your signals into finalSig, the entire Risk Management system (Stops, TPs, AATS, RSIS, re-entry logic, weekend filters, long/short toggles) becomes available for your custom strategy without re-inventing the wheel. This makes Superior RBR not just a strategy, but a reference architecture for serious Pine dev work. 5. About Signal Lynx Automation for the Night-Shift Nation 🌙 Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management. We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to: Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search. License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Estratégia Pine Script®
por SignalLynx
Super-AO with Risk Management Strategy Template - 11-29-25Super-AO Strategy with Advanced Risk Management Template Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙 1. Overview Welcome to the Super-AO Strategy. This is more than just a buy/sell indicator; it is a complete, open-source Risk Management (RM) Template designed for the Pine Script community. At its core, this script implements a robust swing-trading strategy combining the SuperTrend (for macro direction) and the Awesome Oscillator (for momentum). However, the real power lies under the hood: a custom-built Risk Management Engine that handles trade states, prevents repainting, and manages complex exit conditions like Staged Take Profits and Advanced Adaptive Trailing Stops (AATS). We are releasing this code to help traders transition from simple indicators to professional-grade strategy structures. 2. Quick Action Guide (TL;DR) Best Timeframe: 4 Hours (H4) and above. Designed for Swing Trading. Best Assets: "Well-behaved" assets with clear liquidity (Major Forex pairs, BTC, ETH, Indices). Strategy Type: Trend Following + Momentum Confirmation. Key Feature: The Risk Management Engine is modular. You can strip out the "Super-AO" logic and insert your own strategy logic into the template easily. Repainting: Strictly Non-Repainting. The engine calculates logic based on confirmed candle closes. 3. Detailed Report: How It Works A. The Strategy Logic: Super-AO The entry logic is based on the convergence of two classic indicators: SuperTrend: Determines the overall trend bias (Green/Red). Awesome Oscillator (AO): Measures market momentum. The Signal: LONG (+2): SuperTrend is Green AND AO is above the Zero Line AND AO is Rising. SHORT (-2): SuperTrend is Red AND AO is below the Zero Line AND AO is Falling. By requiring momentum to agree with the trend, this system filters out many false signals found in ranging markets. B. The Risk Management (RM) Engine This script features a proprietary State Machine designed by Signal Lynx. Unlike standard strategies that simply fire orders, this engine separates the Signal from the Execution. Logic Injection: The engine listens for a specific integer signal: +2 (Buy) or -2 (Sell). This makes the code a Template. You can delete the Super-AO section, write your own logic, and simply pass a +2 or -2 to the RM_EngineInput variable. The engine handles the rest. Trade States: The engine tracks the state of the trade (Entry, In-Trade, Exiting) to prevent signal spamming. Aggressive vs. Conservative: Conservative Mode: Waits for a full trend reversal before taking a new trade. Aggressive Mode: Allows for re-entries if the trend is strong and valid conditions present themselves again (Pyramiding Type 1). C. Advanced Exit Protocols The strategy does not rely on a single exit point. It employs a "Layered Defense" approach: Hard Stop Loss: A fixed percentage safety net. Staged Take Profits (Scaling Out): The script allows you to set 3 distinct Take Profit levels. For example, you can close 10% of your position at TP1, 10% at TP2, and let the remaining 80% ride the trend. Trailing Stop: A standard percentage-based trailer. Advanced Adaptive Trailing Stop (AATS): This is a highly sophisticated volatility stop. It calculates market structure using Hirashima Sugita (HSRS) levels and Bollinger Bands to determine the "floor" and "ceiling" of price action. If volatility is high: The stop loosens to prevent wicking out. If volatility is low: The stop tightens to protect profit. D. Repainting Protection Many Pine Script strategies look great in backtesting but fail in live trading because they rely on "real-time" price data that disappears when the candle closes. This Risk Management engine explicitly pulls data from the previous candle close (close , high , low ) for its calculations. This ensures that the backtest results you see match the reality of live execution. 4. For Developers & Modders We encourage you to tear this code apart! Look for the section titled // Super-AO Strategy Logic. Replace that block with your own RSI, MACD, or Price Action logic. Ensure your logic outputs a 2 for Buy and -2 for Sell. Connect it to RM_EngineInput. You now have a fully functioning Risk Management system for your custom strategy. 5. About Signal Lynx Automation for the Night-Shift Nation 🌙 This code has been in action since 2022 and is a known performer in PineScript v5. We provide this open source to help the community build better, safer automated systems. If you are looking to automate your strategies, please take a look at Signal Lynx in your search. License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Estratégia Pine Script®
por SignalLynx