Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls.
How It Works
The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters.
Main Operations
The strategy works on any timeframe but it's meant to be used on daily charts.
Entry Signals:
Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout.
Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites.
Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value.
Exit Signals:
Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period").
Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing).
Locks profits in trends, exits fast on fades.
Risk Controls:
Tracks realized equity peak.
10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x).
Full reset above peak—preserves capital in slumps.
Strategy
Engulfing StrategyThis indicator has the following key features:
- Detects bullish and bearish engulfing candlestick patterns using a well-established price and body comparison logic.
- Incorporates a customizable moving average filter with multiple smoothing options to confirm trend direction.
- Highlights both the current and previous candles involved in the engulfing pattern by coloring them distinctly, improving visual clarity for reversal signals.
- Offers an interchangeable mode allowing the user to switch between a fully automated trading strategy (entries and exits) and a simple indicator mode (signal and color visualization only).
- Supports pyramiding positions and accounts for commissions and initial capital for realistic strategy testing.
- Uses modern Pine Script v5 functions and syntax for reliable and efficient execution.
- Provides clear visual bar colors for bullish (orange) and bearish (yellow) engulfing signals.
- Allows configuration of MA type and period, adapting to various trading styles and assets.
These features make it a versatile tool for traders seeking both visual confirmation and automated trade execution based on engulfing candle patterns combined with trend filtering.
by @Tumiza999
Quantura - Quantified Price Action StrategyIntroduction
“Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices.
Originality & Value
The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of:
Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity.
Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs.
RSI filter: Can be set to normal or aggressive, confirming momentum before trades.
Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies.
EMA filter: Aligns trades with the broader market trend.
Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions.
This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow.
Functionality & Indicators
Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap.
Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection.
RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness.
FVG filter: Adds validation by requiring price interaction with inefficiency zones.
EMA filter: Ensures longs are above EMA and shorts below EMA.
Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status.
Parameters & Customization
Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options.
Liquidity filter: Mode (Run or Sweep), display, and swing length.
RSI: Enable/disable, length, and style (normal or aggressive).
Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles.
EMA: Length, enable/disable, and visualization.
Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing.
Visualization: Custom candle coloring and optional overlay for better clarity.
Default Properties (Strategy Settings)
Initial Capital: 10,000 USD
Position Size: 100% of equity per trade (backtest default)
Commission: 0.1%
Slippage: 1
Pyramiding: 0 (only one position at a time)
Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%.
Backtesting & Performance
Backtests on XPTUSD over 2.5 years with the default settings produced:
164 trades
67.68% win rate
Profit factor: 1.7
Maximum drawdown: 27.81%
These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (164) is sufficient for statistical analysis, results may vary across markets and timeframes.
Risk Management
Three configurable take-profit levels with percentage allocation.
Initial stop-loss based on user-defined percentage.
Dynamic stop-loss that adjusts with market movement.
Break-even logic that shifts stops to entry after predefined gains.
Position sizing based on risk percentage of equity.
This framework allows both conservative and aggressive configurations, depending on user preference.
Limitations & Market Conditions
Works best in volatile and liquid markets such as crypto, metals, indices, and FX.
May produce false signals in low-volume or sideways environments.
Unexpected news or macro events can override technical conditions.
Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use.
Usage Guide
Add “Quantura – Quantified Price Action Strategy” to your chart.
Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe.
Configure risk management: take-profits, stop-loss, and risk-per-trade percentage.
Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions.
Optimize parameters before applying the strategy to different markets.
Author & Access
Developed 100% by Quantura. Published as an Invite-Only script.
Important
This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Quantura - Quantitative AlgorythmIntroduction
“Quantura – Quantitative Algorithm” is an invite-only Pine Script strategy designed for multi-timeframe analysis, combining technical filters with user-adjustable fundamental sentiment. It was primarily developed for cryptocurrency markets but can also be applied across other assets such as Forex, stocks, and indices. The goal is to generate structured trade signals through a confluence of techniques rather than relying on a single indicator.
Originality & Value
Quantura is not a simple mashup of indicators. Its originality comes from how multiple layers of analysis are integrated into a single decision framework . Instead of showing indicators separately, the strategy only issues trades when several conditions align simultaneously:
RSI entry triggers confirm overbought/oversold reversals.
Market structure on a higher timeframe confirms trend direction.
Order block detection highlights zones of concentrated supply and demand.
Premium/Discount zones identify potential over- and undervaluation.
HTF EMA provides trend confirmation.
Optional candlestick patterns strengthen reversal or continuation signals.
An optional correlation filter compares the main asset to a reference instrument.
This design forces agreement between different methodologies (momentum, structure, value, volume, sentiment), which reduces noise compared to using them in isolation.
Functionality & Indicators
Entry trigger: RSI exits from extreme zones.
Filters: Only valid when all selected filters (HTF structure, EMA, order blocks, premium/discount, candlesticks, correlation, volume) confirm the direction.
Fundamental bias: User-defined sentiment and analysis settings (bullish, bearish, neutral) influence whether long or short trades are permitted.
Exits: ATR-based take profit and stop loss, with optional breakeven, opposite-signal exit, and session-end exit.
Visualization: Buy/Sell markers, trend-colored candles, and an optional dashboard summarizing indicator status.
Parameters & Customization
Timeframes: Independent HTF and LTF selection.
Trading direction: Long / Short / Both.
Session and weekday filters.
RSI length and thresholds.
Filters: HTF structure, order blocks, premium/discount, EMA, candlestick, ATR volatility, volume zones, correlation.
Exit rules: ATR multipliers for TP/SL, breakeven logic, session-end exit, opposite-signal exit.
Visuals: Toggle signals, candles, dashboard, custom colors.
Default Properties (Strategy Settings)
Initial Capital: 100,000 USD
Position Size: 15% of equity per trade
Commission: 0.25%
Slippage: enabled
Pyramiding: 0 (one position at a time)
Note: The position sizing of 15% equity per trade is intentionally set for backtesting demonstration. In real trading, risking this much is considered aggressive. Most traders prefer to risk 1-5% of equity, and rarely above 10%.
Backtesting & Performance
Backtests on BTCUSD (2 years) with the above defaults showed:
112 trades
Win rate: 40%
Profit factor: 1.4
Maximum drawdown: 34%
These results illustrate how the confluence model behaves, but they are not predictive of future performance . The trade sample size (72 trades) is below the 100+ usually recommended for statistical robustness. Users should re-test with their own preferred symbols, settings, and timeframes.
Risk Management
ATR-based stops and targets scale with volatility.
Commission and slippage are included by default for realistic modeling.
Opposite-signal exit helps capture trend reversals.
Session-end exit can close intraday positions before illiquid hours.
Breakeven option protects profits when available.
Although the default allocation uses 15% per trade for demonstration, this is not a recommendation. Users are encouraged to adjust risk sizing downwards to sustainable levels (commonly 1-5%).
Limitations & Market Conditions
Performs best in volatile, liquid markets (e.g., crypto).
May struggle in prolonged sideways markets with low volatility.
News events and fundamentals outside user inputs can override signals.
Backtests below 100 trades should be considered exploratory, not statistically conclusive.
Usage Guide
Add “Quantura – Quantitative Algorithm” to your chart in strategy mode.
Select HTF and LTF timeframes, trading direction, and session filters.
Configure confluence filters (structure, EMA, order blocks, premium/discount, candlestick, correlation, volume).
Set sentiment and analysis bias in fundamental settings.
Adjust ATR multipliers and exits.
Review buy/sell signals and analyze performance in the Strategy Tester.
Author & Access
Developed 100% by Quantura . Distributed as an Invite-Only script . Details are provided in the Author’s Instructions field.
Important: This description complies with TradingView’s Script Publishing Rules and House Rules. It does not guarantee profitability, avoids unrealistic claims, and explains how the strategy integrates multiple methods into a coherent decision framework.
🦁 Hunt and eat v14++My 🦁 Hunt & Eat v14++ strategy combines the best of both worlds: Peak and Valley (CYC) detection to capture precise market reversals, and Time-to-Move (TTM) filters to align with the overall trend, ensuring cleaner, less noisy trades.
Its main strengths are:
Adaptability: It can trade in both trending phases and reversal zones, thanks to its selectable modules.
Multiple Confirmation: It combines structural signals (pivots) with dynamic conditions such as ADX, EMA angle, and neutrality filters.
Disciplined Management: It avoids entering flat or directionless zones, reducing unnecessary trades.
Visual Clarity: It uses a performance panel and EMA colors that reflect the actual state of the position.
In short, it's a trend-chasing strategy with contextual intelligence, designed to capitalize on strong moves without getting caught in market indecision.
Strategy Builder v1.0.0 [BigBeluga]🔵 OVERVIEW
The Strategy Builder combines advanced price-action logic, smart-money concepts, and volatility-adaptive momentum signals to automate high-quality entries and exits across any market. It blends trend recognition, market structure shifts, order block reactions, imbalance (FVG) signals, liquidity sweeps, candlestick confirmations, and oscillator-powered divergences into one cohesive engine.
Whether used as a full automation workflow or as a structured confirmation framework, this strategy provides a disciplined, rules-driven method to trade with logic — not emotion.
🔵 BACKTEST WINDOW CONTROL
This module allows you to restrict strategy execution to a specific historical period.
Ideal for performance isolation, regime testing, and forward-walk validation.
Limit Backtest Window
Enabling this option activates custom date filters for the backtest engine.
Start — Define the starting date & time for backtesting
End — Define the ending date & time for backtesting
Only trades and signals inside this window are executed
Reduces computation load on large datasets
Useful for testing specific market environments (e.g., bull cycles, crash periods, sideways regimes)
🔵 SIGNAL GLOSSARY (Advanced Technical Explanation)
Traders can build long and short setups using up to 6 configurable entry conditions for each direction.
Every condition can be set as Bullish or Bearish and mapped to any signal source — allowing deep customization
Below is the full internal logic overview of every signal available in the Strategy Builder.
Signals are based on trend models, volatility structures, liquidity logic, oscillator behavior, and market structure mapping.
Trend Signals (Low-Lag Trend Engine)
Uses a proprietary low-lag baseline + momentum gradient model to detect directional bias.
Trend Signal — Momentum breaks above/below adaptive trend baseline.
Trend Signal+ — Stronger trend confirmation using volatility-weighted momentum.
Trend Signal Any — Triggers when any bullish/bearish trend signal appears.
SmartBand & Retests (Adaptive Volatility Bands)
Dynamic envelope that contracts/expands with volatility & trend strength.
SmartBand Retest — Price retests dynamic band and rejects, confirming continuation.
ActionWave Signals (Impulse-Pullback Engine)
Tracks wave behavior, acceleration and deceleration in price.
ActionWave — Detects directional impulse strength vs pullback weakness.
ActionWave Cross — Momentum acceleration threshold crossed → trend ignition.
Magnet Signals (Liquidity Gravity + Mean Reversion Bias)
Detects zones where price is being drawn due to liquidity voids or imbalance.
Magnet — Trend and liquidity pressure align, creating directional “pull.”
MagnetBar Low Momentum — Low-volatility compression → pre-breakout condition.
Flow Trend (Directional Flow State + ATR Envelope)
Higher-timeframe bias confirmation + dynamic volatility filter.
FlowTrend — Confirms major directional bias (uptrend or downtrend).
FlowTrend Retest — Price tests HTF flow band and rejects → trend resume.
Voltix (Volatility Expansion Pulse)
Detects regime shift from quiet accumulation → trending expansion.
Voltix — Breakout volatility signature, trend acceleration trigger.
Candlestick Pattern (Algorithmic Price Action Recognition)
Auto-recognizes meaningful reversal or continuation candle formations.
Candlestick Pattern — Confirms momentum reversal/continuation via candle logic.
OrderBlock Logic (Institutional Footprint System)
Institutional demand/supply zone tracking with mitigation logic.
Order Block Touch — Price taps institutional zone → reaction filter.
Order Block Break — OB invalidation → institutional flow shift.
Market Structure Engine (Swing Logic + Volume Confirmation)
Tracks major swing breaks and structural reversals.
BoS — Break of Structure in trend direction (continuation bias).
ChoCh — Change of Character — early reversal marker.
Fair Value Gaps (Imbalance & Volume Displacement)
Identifies inefficiencies caused by rapid displacement moves.
FVG Created — Price leaves inefficiency behind.
FVG Retest — Price returns to rebalance inefficiency → reaction zone.
Liquidity Events (Stop-Run & Reversal Logic)
Detects stop-hunt events and liquidity sweeps.
SFP — Swing failure & wick sweep → reversal confirmation.
Liquidity Created — New equal highs/lows form liquidity pool.
Liquidity Grab — Sweep through liquidity line followed by rejection.
Support / Resistance Break Logic
Adaptive zone recognition + momentum confirmation.
Support/Resistance Cross — Zone decisively broken → structural shift.
Pattern Breakouts (Market Geometry Engine)
Tracks breakout from compression & expansion formations.
Channel Break — Channel breakout → trend acceleration.
Wedge Break — Break from contraction wedge → burst of momentum.
Session Logic (Opening Range Behavior)
Session-based volatility trigger.
Session Break — Break above/below session opening range.
Momentum / Reversal Oscillator Suite
Oscillator-driven exhaustion & reversal signals.
Nautilus Signals — Momentum reversal signature (oscillator shift).
Nautilus Peak — Momentum peak → exhaustion risk.
OverSold/Overbought ❖ — Extreme exhaustion zones → reversal setup.
DipX Signals ✦ — Dip buy / Dip sell timing, micro-reversal engine.
Advanced Divergence Engine
Momentum/price disagreement layer with multi-trigger confirmation.
Normal Divergence — Classic divergence reversal.
Hidden Divergence — Trend continuation divergence.
Multiple Divergence — Multiple divergence confirmations stacked → high confidence.
🔧 Adjustable Signal Logic
Some signals in this system can be additionally refined through the strategy settings panel.
This allows traders to tune internal behavior for different market regimes, assets, and volatility conditions.
🔵 LONG / SHORT EXIT CONDITIONS
This section allows you to automate exits using the same advanced market conditions available for entries.
Each exit rule consists of:
Toggle — Enable/disable individual exit rule.
Direction Filter — Trigger exit only if selected market bias appears (Bullish/Bearish).
Signal Type — Choose which market event triggers the exit (same list as entry conditions).
When the active conditions are met, the strategy automatically closes the current position — ensuring emotion-free risk management and systematic trade control.
🔵 TAKE PROFIT & STOP LOSS SYSTEM
This strategy builder provides a fully dynamic risk-management engine designed for both systematic traders and discretionary confirmation users.
Take Profit Logic
Scale out of trades progressively or exit fully using algorithmic TP levels.
Up to 3 Take-Profit targets available
Choose TP calculation method:
• ATR-based distance (volatility-adaptive targets)
• %-based distance (fixed percentage from entry)
Define Size — ATR multiplier or % value
Custom Exit Size per TP (e.g., 25% / 25% / 50%)
Visual TP plotting on chart for clarity
Stop Loss Logic
Automated protection logic for every trade.
Two SL Modes:
• Fixed Stop Loss — static SL from entry
• Trailing Stop Loss — SL follows price as trade progresses
Distance options:
• ATR multiplier (adapts to volatility)
• %-based from entry (fixed distance)
SL dynamically draws on chart for transparency
Trailing SL behavior:
Follows price only in profitable direction
Never moves against the trade
Locks profits as trend develops
🔵 Strategy Dashboard
A compact on-chart performance dashboard is included to help monitor live trade status and backtest results in real time.
It displays key metrics:
Start Capital — Initial account balance used in simulation.
Position Size — % of capital allocated per trade based on user settings (It changes if the trade hits take profits, when more than one take profit is selected).
Current Trade — Shows active trade direction (Long / Short) and real-time % return from entry.
Closed Trades — Counter of completed positions, useful for reading sample size during testing.
🔵 CONCLUSION
The Strategy Builder brings together a powerful suite of smart-money and momentum-driven signals, allowing traders to automate robust trade logic built on modern market structure concepts. With access to trend filters, order blocks, liquidity events, divergence signals, volatility cues, and session-based triggers, it provides a deeply adaptive trade engine capable of fitting many market environments.
MA Fractal Signal (Dual Zones 50-100-200)📈 MA Fractal Signal (Dual Zones 50-100-200)
This indicator is a comprehensive trend-following tool designed to identify high-probability pullback entries. It combines a classic triple moving average setup (50, 100, 200) with fractal signals, but adds a unique twist: it only generates signals when a pullback fractal forms within one of two dynamic "pullback zones" created between the moving averages.
The core strategy is to:
Identify the Trend: Using the alignment of the 50, 100, and 200 MAs.
Wait for a Pullback: Identified by a fractal (pivot low or pivot high).
Confirm Entry Location: The fractal must form inside a key "support/resistance" zone (between MA 50/100 or MA 100/200).
Filter for Quality: The signal is then filtered for trend strength (ADX), momentum (RSI), and trend structure (MA separation) to reduce false signals.
⚙️ How It Works: Core Components
Triple Moving Averages:
Plots three MAs (defaulting to 50, 100, 200).
You can select the MA type (SMA, EMA, WMA, SMMA, HMA) and source.
Their alignment determines the trend direction.
Dual Pullback Zones: The script creates two distinct shaded zones on the chart:
Zone 1 (Gray): The area between the 50 MA and 100 MA.
Zone 2 (Blue): The area between the 100 MA and 200 MA.
ATR Buffer: You can (and should) enable an ATR-based buffer. This makes the zones "thicker" by adding/subtracting a small ATR multiple from the MAs, allowing the script to catch pullbacks that almost touch the MAs but reverse just before.
Fractal Signals:
Uses standard ta.pivotlow (for buys) and ta.pivothigh (for sells) to identify local turning points.
The fractal period (bars to the left and right) is adjustable.
🚦 Signal Logic: Rules for Entry
The indicator will plot a shape and send an alert when all the following conditions are met at the time the fractal was formed:
🚀 Buy Signal (Red Up-Triangle)
Uptrend: MA 50 is above MA 100, AND MA 100 is above MA 200.
Pullback Signal: A Low Fractal (pivotlow) is confirmed.
Location: The low of the fractal candle is inside Zone 1 (between 50/100) OR Zone 2 (between 100/200).
Filters (if enabled):
ADX: Trend strength is above the adxThreshold.
RSI: RSI is above the rsiBuyLevel (e.g., > 40), indicating the pullback isn't deeply oversold.
MA Distance: The MAs are sufficiently "spread out" (measured by ATR), confirming a stable trend.
📉 Sell Signal (Green Down-Triangle)
Downtrend: MA 50 is below MA 100, AND MA 100 is below MA 200.
Pullback Signal: A High Fractal (pivothigh) is confirmed.
Location: The high of the fractal candle is inside Zone 1 (between 50/100) OR Zone 2 (between 100/200).
Filters (if enabled):
ADX: Trend strength is above the adxThreshold.
RSI: RSI is below the rsiSellLevel (e.g., < 60), indicating the pullback isn't deeply overbought.
MA Distance: The MAs are sufficiently "spread out."
🔧 Settings & Inputs
MA Settings: Choose the MA Type, Source, and Lengths for all three MAs.
Zone Buffer: Toggle the ATR buffer on/off and set its ATR Length and Multiplier. A smaller multiplier (e.g., 0.25) keeps the zone tight to the MAs.
Fractal Period: Set the number of bars to the left/right to identify a fractal.
ATR Distance Filter: Toggle the filter and set the ATR Length and Min. Multiplier required for the MAs to be considered "spread out."
ADX Filter: Toggle the filter and set the DI Length, ADX Smoothing, and Min. Trend Strength threshold.
RSI Filter: Toggle the filter and set the RSI Length and the Buy/Sell Levels.
Binary Options Gold Scalping [TradingFinder] 1 & 5 Min Strategy🔵 Introduction
In binary options trading, price movements are often driven by the market’s tendency to reach key liquidity zones. These areas include Liquidity, Fair Value Gaps (FVGs), and Order Blocks (OBs), zones where a large number of pending orders are concentrated.
When price reaches one of these zones, it typically enters a Liquidity Sweep phase to collect available liquidity. After this process, the market often reacts sharply, either reversing direction or continuing its move with renewed momentum. Understanding this cycle forms the foundation of most smart money-based binary options strategies.
In this analytical approach, a Liquidity Sweep is usually seen as a False Breakout, often recognized through a distinctive candle confirmation pattern. The pattern appears when price briefly breaks a level to trigger stops, then quickly returns within range. This formation is one of the most reliable reversal signals for short-term trades and plays a central role in many binary options strategies.
After a liquidity sweep, price often returns to Fair Value Gap (FVG) or Order Block (OB) areas to restore balance in the market. These are zones where institutional orders are typically placed, and reactions around them can create high-probability trade setups. In binary options trading, this quick reaction following a sweep and retrace into an FVG or OB provides one of the best entry opportunities for short-term trades.
By combining the concepts of Liquidity Sweep, Fair Value Gap, and Order Block, traders can build a precise binary options strategy based on smart money behavior, allowing them to identify market reversals with greater confidence and enter at the optimal moment.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator is built on the Smart Money Concept (SMC) framework and serves as a core tool for accurately detecting Liquidity Sweeps, Order Blocks, and Fair Value Gaps in binary options trading.
Its logic is simple yet powerful : when price reaches high-interest liquidity zones and shows reversal signs, the indicator issues an entry signal immediately after a Candle Confirmation is complete.
Signals only activate when both the market structure and the candle confirmation pattern align, ensuring high accuracy in spotting genuine reversals.
🟣 Long Position
A bullish signal appears when the market, after a downward move, reaches sell-side liquidity zones where liquidity has built up below previous lows. In such conditions, a bullish Order Block or Fair Value Gap often exists in the same region, acting as a potential reversal point.
When the indicator detects the presence of liquidity, an imbalance zone (FVG), and a valid candle confirmation simultaneously, it triggers a green Call signal.
In a binary options strategy, the best entry moment is immediately after the candle confirmation closes, as this is when the probability of reversal is highest and the market tends to react strongly within the next few candles.
In the example below, after the liquidity sweep and candle confirmation, price quickly rallied, resulting in a Binary Win setup.
🟣 Short Position
A bearish signal occurs when price, after an upward move, reaches an area of buy-side liquidity and collects liquidity above recent highs. At this stage, the market is typically overbought and ready to reverse. If a bearish Order Block or Fair Value Gap exists in the same area and a candle confirmation pattern forms, the indicator displays a red Put signal.
This setup is highly accurate because multiple structural confirmations occur simultaneously : liquidity has been absorbed, price is rebalancing, and the confirmation candle has closed.
In binary options trading, this is the ideal moment to enter a Put (Sell) position, as the price reaction to the downside is usually quick and decisive.
In the example chart, the indicator generated a bearish signal right after the candle confirmation and completion of the liquidity sweep, price then dropped within minutes, resulting in another Binary Win.
🔵 Settings
Time Frame : Select the desired timeframe for analysis. If left blank, the indicator uses the chart’s current timeframe.
Swing Period : Defines how many candles are used to detect structural pivots (swing highs and lows). A higher value increases accuracy but reduces the number of signals.
Candle Pattern : Enables candle-based confirmation logic. When turned on, the indicator issues signals only if a valid reversal pattern is detected. You can also choose the confirmation filter strength, tighter filters show fewer but more precise signals.
🔵 Conclusion
A deep understanding of Liquidity Sweeps, Order Blocks, and Fair Value Gaps can make a decisive difference between ordinary and professional traders in the binary options market.
This indicator, combining smart money logic with candle confirmation, is one of the most precise tools for detecting true market reversals. When liquidity is collected and structural reversal signs emerge, the indicator automatically recognizes the price reaction and generates a reliable Call or Put signal.
Using this tool alongside market structure analysis and FVG detection allows traders to enter high-probability setups while filtering out false breakouts. For that reason, this binary options strategy is not only suitable for short-term trading but also valuable for understanding deeper smart-money behavior across timeframes.
Ultimately, success with this system comes down to two key principles: understanding the logic of the liquidity sweep and waiting for the candle confirmation to close. When these two conditions align, the indicator can pinpoint the best entry points with remarkable precision, helping you build a structured, intelligent, and profitable binary options strategy.
Futures Fighter MO: Multi-Confluence Day Trading System ADX/SMI👋 Strategy Overview: The Multi-Confluence Mashup
The Futures Fighter MO is a comprehensive, multi-layered day trading strategy designed for experienced traders focusing on high-liquidity futures contracts (e.g., NQ, ES, R2K).
This strategy is a sophisticated mashup that uses the 1-minute chart for surgical entries while enforcing strict environmental filtering through higher-timeframe data. We aim to capture high-conviction moves only when multiple, uncorrelated signals align.
🧠 How the Logic Works (Concepts & Confluence)
Our logic is built on four pillars, which must align for a trade to be executed:
Primary Trend Filter
Indicators :
ADX/DMI (15-Minute Lookback)
Role :
Price action is filtered to ensure the ADX (17/14) is above 25, confirming a strong, prevailing market trend (Bullish or Bearish). Trades are strictly rejected during "Flat" (sideways) market regimes.
Entry Signal Types
The system uses multiple entry types:
- 🟢 Trend Long/Short: A breakout/rejection near the 200-Period EMA is confirmed by the primary ADX trend.
- 🔴 Engulfing Rejection: A strong signal when a Bullish/Bearish Engulfing or Doji prints near the long-term 500-Period EMA (emaGOD) while the Stochastic Momentum Index (SMI on 30M) is in an extreme overbought/oversold state (below $-40$ or above $40$).
Volatility & Volume Confirmation
Indicators: Average True Range (ATR) and 20-Period SMA of Volume
Role: Every entry requires a volume spike (Current Volume $> 1.5 \times$ SMA Volume) to confirm that the move is supported by significant liquidity. Volatility is tracked via ATR to define bar range and stop boundaries.
Structural Guardrails
Indicators: Daily Pivot Points (PP, S1-S3, R1-R3)
Role: Trades are disabled if the current bar's price range intersects with a Daily Pivot Point. This is a critical filter to avoid high-chop consolidation zones near key structural levels.
📊 Strategy Results & Required Disclosures
I strive to publish backtesting results that are transparent and realistic for the retail futures trader.
- Initial Capital: $50,000 - A realistic base for Mini/Micro futures contracts.
- Order Size: 1 Contract (Pyramiding up to 3) - Conservative risk relative to the account size.
- Commission: $0.11 USD per order - Represents realistic costs for low-cost brokers.
- Slippage: 2 Ticks - Accounts for expected market friction.
⚠️ Risk Management & Deviations
Stop-Loss: The strategy uses a dynamic stop-loss system where positions are closed upon a reversal (e.g., breaking the 50-Period EMA or failure to hold a Pivot Point), rather than a fixed tick-based stop. This is suited for experienced traders using a low relative risk (single Micro-contract entry) on a larger account. Users must confirm that the first entry's maximum potential loss remains below $10\%$ of their capital for compliance.
Trade Sample Size: Due to data limitations of the TradingView Essential plan (showing $\approx 50$ trades over 2 weeks), the sample size is under the ideal $100+$ target. Justification: This system is designed to generate signals across a portfolio of correlated futures markets (NQ, ES, R2K, Gold, Crude), meaning the real sample size for a user tracking the portfolio is significantly higher.
Drawdown Control: This strategy is designed for manual management. It requires the user to turn the script/alerts OFF after a significant drawdown and only reactivate it once a recovery trend is established externally.
The strategy uses a combination of dynamic trailing stops, structural support/resistance zones, and a fixed profit target to manage open positions.
🛑 Strategy Exit Logic
1. General Stop-Loss (Dynamic Trailing Stop)
These conditions act as the primary dynamic stop, closing the position if the market reverses past a key Moving Average (MA):
- Long Positions Closed When: The current bar's close crosses under the 50-Period EMA (emaLong).
- Short Positions Closed When: The current bar's close crosses above the 50-Period EMA (emaLong).
2. Profit Target (Fixed Percentage)
The script includes a general exit based on a user-defined profit percentage:
Take Profit Trigger: The position is closed when the currentProfitPercent meets or exceeds the input Profit Target (%) (default is 1.0% of the entry price).
3. Structural Exits (Daily Pivot Points)
These exits are high-priority, "close all" orders that trigger when the price fails to hold or reclaims a recent Daily Pivot Point, suggesting a failure of the current move.
- VR Close All - Long ($\sym{size} > 0$) - Price crosses under a Daily Resistance Level (R1, R2, or R3) minus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Resistance as support.
- VS Close All - Short ($\sym{size} < 0$) - Price crosses above a Daily Support Level (S1, S2, or S3) plus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Support as resistance.
4. Trend Failure Exit (Trend-Following Signals Only)
This exit protects against holding a position when the primary high-timeframe trend used for the entry has failed:
- Long Positions Closed When: The primary trend is no longer "bullish" for more than 2 consecutive bars (i.e., it turned "bearish" or "flat").
- Short Positions Closed When: The primary trend is no longer "bearish" for more than 2 consecutive bars (i.e., it turned "bullish" or "flat").
5. End of Day (EOD) Session Control
The final hard exits based on time:
- End of Session (EoS): At 11:30 AM, new trades are disabled (TradingDay := false). Open positions are kept.
- End of Day (EoD): At 1:30 PM, all remaining open positions are closed (strategy.close_all).
🤝 Development & Disclaimer
This script and description were created with assistance from Gemini and GitHub Copilot. My focus is on helping fellow real estate investors and day traders develop mechanically sound systems.
Disclaimer: This is for educational purposes only and does not constitute financial advice. Always abide by the Realtor Code and manage your own risk.
Trend Entry_0 [TS_Indie]Trend Entry_0 — Mechanism Overview
The core structure of this strategy is based on a price action reversal pattern, as detailed below:
In the case of a Bullish Trend Reversal:
The price initially moves in a bearish direction. When candle A forms a low lower than the previous low, the high of candle A becomes a key reference point.
If the next candle closes above the high of candle A , it confirms a Bullish Trend Reversal.
* Upon a Bullish signal, a Long position is opened at the opening price of the next candle (candle B).
* When a subsequent Bearish signal occurs, the Long position is closed at the opening price of the next candle (candle C).
In the case of a Bearish Trend Reversal:
The price initially moves in a bullish direction. When candle A forms a high higher than the previous high, the low of candle A becomes a key reference point.
If the next candle closes below the low of candle A , it confirms a Bearish Trend Reversal.
* Upon a Bearish signal, a Short position is opened at the opening price of the next candle (candle B).
* When a subsequent Bullish signal occurs, the Short position is closed at the opening price of the next candle (candle C).
Options
* The start and end dates of the backtest can be customized.
* The swing lines of the trend can be displayed as an optional visual aid.
* The user can choose whether to open only Long or Short positions.
Backtest Results and Observations
Based on the backtesting results of this strategy across various assets and timeframes, it has been observed that this approach works best on trending assets such as Gold, BTC, and stocks.
It also performs well on higher timeframes, starting from the Daily timeframe and above, especially when taking Long positions only.
However, when applied to currency pairs such as EUR/USD, the results tend to be less impressive.
I encourage everyone to try backtesting and further developing this strategy — adding new conditions or filters may potentially lead to improved performance.
Disclaimer
This script is intended solely for backtesting purposes, based on a particular price action pattern.
It does not constitute financial or investment advice.
Backtest results do not guarantee future performance.
AnkeAlgo A68 strategy™ || AnkeAlgo®[16.6]## ✅ Multi-Timeframe Trend Strategy Based on MFI and Momentum Factors
### 📌 Overview
This strategy combines **Money Flow Index (MFI)** and **Momentum** to identify trend continuation and momentum reversal opportunities in the crypto market. It focuses on volume-weighted capital flow and price strength, generating trend-biased signals suitable for swing and intraday traders.
---
### 📊 Technical Indicators Used
| Indicator | Purpose |
|-----------|---------|
| **MFI (Money Flow Index)** | Detects capital inflow/outflow and filters range-bound markets |
| **Momentum Indicator** | Measures price acceleration and confirms breakout strength |
| **Optional: ATR / EMA Filters** | Can be added for volatility stop or trend validation |
---
### ⚙️ Core Logic
- **Trend Confirmation**: MFI exceeds threshold and aligns with price direction
- **Momentum Entry Trigger**: Trades are executed only when momentum crosses a signal level
- **Noise Filter**: Avoids entries when MFI divergence or momentum weakness is detected
- **Position Management**: Supports ATR-based or percentage-based stop-loss systems
---
### 🪙 Market and Asset
✅ Designed for crypto derivatives
**Recommended symbol:** `ETHUSDT.P` (Perpetual Futures)
---
### ⏱️ Recommended Timeframes
- 30-minute
- 45-minute
- 1-hour
> The **45m timeframe** shows the most stable performance in forward testing.
---
### 📈 Strategy Features
- Performs best during trending and high-momentum phases
- Low overfitting risk, adaptable across different volatility environments
- Can be used as a signal engine for grid, martingale, or multi-asset systems
- Easily extendable to BTC, SOL, BNB, and other high-liquidity assets
---
### ⚠️ Risk Disclaimer
- This is **not** a mean-reversion strategy and may produce false signals in sideways markets
- Stop-loss management and position sizing are required for live deployment
- Backtest results do not guarantee live trading performance due to slippage and trading fees
---
Smart Risk - Three Institutional Models📘 Smart Risk – Three Institutional Entry Models
A precision-engineered institutional framework that blends liquidity, structure, and multi-time-frame confirmation.
🧠 Concept Overview
The Smart Risk indicator models how institutional traders and algorithms engineer entries around liquidity, imbalance, and structural shifts .
It unifies t hree distinct institutional entry models —each built around core Smart Money Concepts (SMC)—and enhances them with a Multi-Time-Frame Confluence (MTF) engine for directional alignment.
This tool doesn’t simply merge indicators.
It connects l iquidity sweeps, order-block reactions, breaker validation, and fair-value-gap mitigation into one cohesive trading logic—filtering every setup through trend, structure, and volume confirmation.
⚙️ How It Works
Setup #1 – Liquidity Sweep + Order Block Revisit + FVG Mitigation
Identifies engineered stop-hunts where price sweeps external liquidity and returns to a prior Order Block or Fair Value Gap (FVG).
Signals reversal-style entries with high probability of mean-reversion or mitigation.
Setup #2 – Supply/Demand + Mitigation / Breaker / FVG Continuation
Captures continuation trades inside trending structure.
When trend bias (via moving-average context) aligns with breaker or mitigation blocks, signals confirm institutional continuation sequences.
Setup #3 – Sweep + Classic FVG Reaction
Tracks clean displacement gaps following a liquidity sweep—ideal for scalpers and intraday reversals where imbalances act as magnets for price.
Each setup can be independently enabled or disabled from the panel.
A built-in signal-cooldown prevents repetitive triggers on the same leg.
🕒 Multi-Time-Frame Confluence
The new MTF module aligns lower-time-frame precision entries with higher-time-frame market structure.
When enabled, each setup only validates if the HTF trend confirms the same directional bias as the LTF pattern—e.g. a 5-minute bullish FVG signal requires a bullish 1-hour structure.
This ensures institutional logic respects global liquidity flow and avoids counter-trend traps.
MTF Controls:
• ✅ Enable MTF Confluence toggle
• ⏱️ Lower Time-Frame (LTF) selector (default 5 min)
• ⏱️ Higher Time-Frame (HTF) selector (default 1 hour)
• 🔄 Automatic SMA-based HTF trend detection
🎨 Visualization & Dashboard
• Order Block / Supply–Demand Zones — highlight institutional footprints
• Fair Value Gaps (FVGs) — reveal displacement inefficiencies
• Liquidity Sweeps (X / $) — mark engineered stops
• BOS & CHoCH — confirm structure continuation or reversal
• Compact Dashboard — live “Armed” state for each setup and MTF bias
Color-coded background cues emphasize active trade phases without clutter.
🧩 Core Algorithm Highlights
• Dynamic swing and pivot structure detection
• Breaker / Mitigation / Volume confirmation filters
• Fair-Value-Gap logic with directional alignment
• Cooldown control for signal throttling
• Multi-Time-Frame bias filter for contextual precision
⸻
📈 How to Use
1. Apply indicator to any asset or timeframe.
2. Select which institutional setups you want active.
3. Optionally enable MTF Confluence (5 min → 1 hr recommended).
4. Wait for BOS/CHoCH confirmation + zone alignment before entry.
5. Use OB and FVG zones for entry/exit planning with risk management.
⸻
💡 Originality Statement
This script introduces a multi-layered institutional logic engine that merges liquidity, mitigation, and imbalance behavior into a unified framework—augmented with time-frame synchronization and signal-cooldown management.
All logic, calculations, and visualization structure were built from scratch for this model.
It is not a mash-up of existing public indicators and offers measurable analytical value through MTF-aware trade validation.
⸻
⚠️ Disclaimer
This tool is intended for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Always back-test, validate setups, and apply proper risk management.
Vandan V2Vandan V2 is an automated trend-following strategy for NASDAQ E-mini Futures (NQ1!).
It uses multi-timeframe momentum and volatility filters to identify high-probability entries.
Includes dynamic risk management and trailing logic optimized for intraday trading.
PCP Arbitrage Monitor (Math by Thomas)Live monitor for Put–Call Parity (C + PV(K) = P + S) showing drift, arbitrage direction, and opportunity strength.
The PCP Arbitrage Monitor helps traders visualize and quantify deviations from the Put–Call Parity (PCP) relationship:
𝐶+𝐾𝑒−𝑟𝑇 = 𝑃+𝑆
When this equation drifts, it indicates a potential arbitrage opportunity between call, put, and underlying (spot or future).
This indicator plots the left-hand side (LHS) and right-hand side (RHS) of the PCP equation on your chart, computes the drift, and automatically highlights and displays actionable trade combinations when the deviation exceeds a set threshold.
⚙️ How It Works
Inputs
Call & Put Symbols – Select matching call and put options (same strike & expiry).
Strike (K) – The strike price for those options.
Expiry (UTC) – Option expiry date/time (used to calculate 𝑇 and PV(K)).
Risk-free Rate (r) – Annualized rate used for discounting the strike.
Lot Size / Tick Value – Used to calculate profit in INR.
Arbitrage Threshold – Minimum drift (in points) to trigger signals (default 200).
Displayed Data
LHS = C + PV(K) (Call + discounted Strike)
RHS = P + S (Put + Spot/Future)
Drift = LHS – RHS
Bookable Profit (INR)
Action Suggestion (only when |drift| ≥ threshold)
Background Highlight
🟩 Green – Call side expensive → Sell Call + Buy Put + Buy Fut
🟥 Red – Call side cheap → Buy Call + Sell Put + Sell Fut
Table
Displays all key values live in the top-right corner:
Option prices
LHS, RHS
Drift (points)
Time to expiry
Lot size
Bookable profit (INR)
Trade action (only if |drift| ≥ threshold)
📈 How to Use
Open a NIFTY Spot or Futures chart (works on both).
Enter the exact option symbols (e.g., NSE:NIFTY24DEC21900CE and NSE:NIFTY24DEC21900PE).
Adjust Strike (K) and Expiry to match those options.
Observe:
The green/red background highlights large deviations (≥ threshold).
The Action cell displays the arbitrage combination and expected profit.
A drift beyond the threshold suggests a potential risk-free arbitrage if executed simultaneously across all legs.
Hold positions till expiry if margin allows; the profit is theoretically locked in.
💡 Tips
Works on both Spot and Futures charts — the script auto-uses the chart’s close as 𝑆
Set smoothing to 0 to see raw parity values.
Adjust threshold based on costs and margin — e.g., 150–200 points for NIFTY is practical.
Only valid when options are European (no early exercise risk).
Ensure both option symbols are liquid and from the same expiry.
⚠️ Disclaimer
This tool is for educational and analytical purposes.
Real arbitrage execution depends on liquidity, bid-ask spread, slippage, and margin requirements.
Always validate prices with your broker before trading.
🚀 DocBrown PRO Edition V14++🚀 DocBrown PRO Edition V14++ | Advanced 10-Minute Scalping System
A sophisticated algorithmic trading bot designed for high-frequency scalping on 10-minute timeframes, delivering exceptional results with 91%+ win rate and controlled 6.5% maximum drawdown.
Key Features:
Multi-Layer EMA System with dynamic support/resistance detection
Adaptive Volatility Stop Loss (VATS) - automatically adjusts to market conditions
Smart Entry Filters - ADX-based trend detection prevents range-bound losses
Dynamic Take Profit - targets key S&R levels for optimal exits
Anti-Liquidation Protection - multiple safety mechanisms including ATR trailing stops
Momentum Derivative Logic - closes positions before reversals hit your stop loss
Breakeven Protection - locks in profits automatically after minimal gains
Risk Management Excellence:
✅ Automatic stop-loss at breakeven + commission buffer
✅ Counter-trend detection with multi-confirmation system
✅ Volume spike protection against adverse moves
✅ Stagnation exit to avoid dead positions
✅ Consecutive bar monitoring for early exit signals
Optimized for: BTC, ETH, and high-volume altcoin pairs on leverage (20x recommended)
Performance: 17.76% net profit with 34.4 profit factor - wins $34 for every $1 risked.
Perfect for traders seeking consistent scalping profits with institutional-grade risk management.
RSI Divergence Strategy v6 What this does
Detects regular and hidden divergences between price and RSI using confirmed RSI pivots. Adds RSI@pivot entry gates, a normalized strength + volume filter, optional volume gate, delayed entries, and transparent risk management with rigid SL and activatable trailing. Visuals are throttled for clarity and include a gap-free horizontal RSI gradient.
How it works (simple)
🧮 RSI is calculated on your selected source/period.
📌 RSI pivots are confirmed with left/right lookbacks (lbL/lbR). A pivot becomes final only after lbR bars; before that, it can move (expected).
🔎 The latest confirmed pivot is compared against the previous confirmed pivot within your bar window:
• Regular Bullish = price lower low + RSI higher low
• Hidden Bullish = price higher low + RSI lower low
• Regular Bearish = price higher high + RSI lower high
• Hidden Bearish = price lower high + RSI higher high
💪 Each divergence gets a strength score that multiplies price % change, RSI change, and a volume ratio (Volume SMA / Baseline Volume SMA).
• Set Min divergence strength to filter tiny/noisy signals.
• Turn on the volume gate to require volume ratio ≥ your threshold (e.g., 1.0).
🎯 RSI@pivot gating:
• Longs only if RSI at the bullish pivot ≤ 30 (default).
• Shorts only if RSI at the bearish pivot ≥ 70 (default).
⏱ Entry timing:
• Immediate: on divergence confirm (delay = 0).
• Delayed: after N bars if RSI is still valid.
• RSI-only mode: ignore divergences; use RSI thresholds only.
🛡 Risk:
• Rigid SL is placed from average entry.
• Trailing activates only after unrealized gain ≥ threshold; it re-anchors on new highs (long) or new lows (short).
What’s NEW here (vs. the reference) — and why you may care
• Improved pivots + bar window → fewer early/misaligned signals; cleaner drawings.
• RSI@pivot gates → entries aligned with true oversold/overbought at the exact decision bar.
• Normalized strength + volume gate → ignore weak or low-volume divergences.
• Delayed entries → require the signal to persist N bars if you want more confirmation.
• Rigid SL + activatable trailing → trailing engages only after a cushion, so it’s less noisy.
• Clutter control + gradient → readable chart with a smooth RSI band look.
Suggested starting values (clear ranges)
• RSI@pivot thresholds: LONG ≤ 30 (oversold), SHORT ≥ 70 (overbought).
• Min divergence strength:
0.0 = off
3–6 = moderate filter
7–12 = strict filter for noisy LTFs
• Volume gate (ratio):
1.0 = at least baseline volume
1.2–1.5 = strong-volume only (fewer but cleaner signals)
• Pivot lookbacks:
lbL 1–2, lbR 3–4 (raise lbR to confirm later and reduce noise)
• Bar window (between pivots):
Min 5–10, Max 30–60 (increase Min if you see micro-pivots; increase Max for wider structures)
• Risk:
Rigid SL 2–5% on liquid majors; 5–10% on higher-volatility symbols
Trailing activation 1–3%, trailing 0.5–1.5% are common intraday starts
Plain-text examples
• BTCUSDT 1h → RSI 9, lbL 1, lbR 3, Min strength 5.0, Volume gate 1.0, SL 4.5%, Trail on 2.0%, Trail 1.0%.
• SPY 15m → RSI 8, lbL 1, lbR 3, Min strength 7.0, Volume gate 1.2, SL 3.0%, Trail on 1.5%, Trail 0.8%.
• EURUSD 4h → RSI 14, lbL 2, lbR 4, Min strength 4.0, Volume gate 1.0, SL 2.5%, Trail on 1.0%, Trail 0.5%.
Notes & limitations
• Pivot confirmation means the newest candidate pivot can move until lbR confirms it (expected).
• Results vary by timeframe/symbol/settings; always forward-test.
• Educational tool — no performance or profit claims.
Credits
• RSI by J. Welles Wilder Jr. (1978).
• Reference divergence script by eemani123:
• This version by tagstrading 2025 adds: improved pivot engine, RSI@pivot gating, normalized strength + optional volume gate, delayed entries, rigid SL and activatable trailing, and a gap-free RSI gradient.
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
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
ProbRSI Adaptive SPY and QQQ Swing One Hour Strategy Summary in one paragraph
A probabilistic RSI engine for large cap ETFs and index names on intraday and swing timeframes. It converts ATR scaled returns into a 0 to 100 probability line, adapts its smoothing from path efficiency, and gates flips with simple percent levels. It is original because it fuses three pieces that traders rarely combine in one signal line: ATR normalized return probability, curvature compression, and per bar adaptive EMA. Add it to a clean chart, keep the default one hour signal on QQQ, and read the entry and exit markers generated by the strategy. For conservative alerts select on bar close.
Scope and intent
• Markets. Major ETFs and large cap equities. Index futures. Liquid crypto. Major FX pairs
• Timeframes. One minute to daily. Defaults to one hour for swing pace
• Default demo used in this publication. SPY/QQQ on one hour
• Purpose. Reduce false flips by adapting to path efficiency and by gating long and short separately
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Logistic probability of ATR scaled returns with arcsine pre transform, optional curvature compression, and per bar adaptive EMA steered by an efficiency ratio
• Failure mode addressed. Fast whips in congestion and late entries after spikes
• Testability. Each component has a named input and can be tuned directly. Entry names Long and Short are visible in the list of trades
• Portable yardstick. ATR scaled return is a common unit across symbols and venues
• Protected rationale. The code stays protected to preserve implementation details of the adaptive engine and curvature assist while the method and usage are fully explained here for community review
Method overview in plain language
You convert raw returns into a probability scale, adapt the smoothing to the straightness of the path, and only allow flips when a simple gate is satisfied. The probability line crosses its own EMA to generate signals. When the cross happens below a short gate or above a long gate, the flip is allowed. Otherwise it is ignored.
Base measures
• Return basis. Close minus prior close normalized by ATR, then arcsine to damp large steps. ATR window is set by ATR length. Sensitivity is adjusted by an ATR scale input
• Probability map. A logistic function maps the normalized return to 0 to 1 which becomes 0 to 100 after scaling
Components
• Probability core. Logistic probability of ATR scaled returns. Higher values imply upside pressure. Smoothed by an adaptive EMA
• Curvature assist optional. A curvature proxy compresses extreme spikes toward neutral. Useful after news bars. Weight controls strength
• Efficiency ratio. A path efficiency score from 0 to 1 extends the smoothing length during noisy paths and shortens it during directional paths
• Signal line. An EMA of the probability line creates the reference for cross up and cross down
• Gates. Two simple percent levels define when long and short flips are allowed
Fusion rule
• The adaptive EMA length is computed as a linear map between a minimum and a maximum bound based on one minus efficiency
• If curvature assist is enabled the probability is adjusted by a small counter spike term
• Final probability is compared to its EMA
Signal rule
• Long. A long entry is suggested when probability crosses above the signal line and the current probability is above the Long gate level
• Short. A short entry is suggested when probability crosses below the signal line and the current probability is below the Short gate level
• Exit and flip. When an opposite entry condition appears the current position is closed and a new position opens in the opposite direction
What you will see on the chart
• Strategy markers on suggestion bars. Orders named Long and Short
• Exit marker when the opposite signal closes the open side
• No table by design. All tuning lives in Inputs for a clean chart
Inputs with guidance
Market TF
• Symbol. Series used for oscillator computation. Use the instrument you trade or a close proxy
• Signal timeframe. Timeframe where the oscillator is evaluated. Leave blank to follow the chart
Core
• Price source. Series used for returns. Typical choice close
• Base length. Fallback EMA length used when adaptation is off. Typical range 20 to 200. Larger smooths more
• ATR length. Window for ATR that scales returns. Typical range 10 to 30. Larger normalizes more and lowers sensitivity
• Logit sharpness. Steepness of the logistic link. Typical range 1 to 8. Raising it reacts more to the same input
• ATR scale. Extra divisor on ATR. Typical range 0.5 to 2. Smaller is more sensitive
• Signal length. EMA of the probability line. Typical range 5 to 20. Larger gives fewer flips
• Long gate. Allow long flips only above this level. Typical range 20 to 40
• Short gate. Allow short flips only below this level. Typical range 20 to 40
Adaptive
• Adaptive smoothing. If on, the efficiency ratio controls the per bar EMA length
• Min effective length. Lower bound of adaptive EMA. Typical range 5 to 50
• Max effective length. Upper bound of adaptive EMA. Typical range 50 to 300
• Efficiency window. Window for efficiency ratio. Typical range 30 to 100
Shape Assist
• Curvature influence. If on, extreme spikes are nudged toward neutral
• Curvature weight. Strength of compression. Typical range 0.1 to 0.3
Properties visible in this publication
• Initial capital. 25000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3 for realistic testing
• Pyramiding 0
• Process orders on close ON
• Bar magnifier OFF
• Recalculate after order is filled OFF
• Calc on every tick OFF
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 use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the curvature assist
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher gates or longer signal length
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Mode
Public protected. Source is hidden while access is free. Implementation detail remains private. Method and use are fully disclosed here
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.
TalaJooy V1.31 𓅂💎 استراتژی معاملاتی TalaJooy V1.31 𓅂
TalaJooy (طلاجوی) یک چارچوب معاملاتی حرفهای و کامل برای TradingView است که برای حذف حدس و گمان، احساسات و تصمیمگیریهای هیجانی از فرآیند معاملات طراحی شده است.
این محصول یک «اندیکاتور سیگنالدهی» ساده نیست؛ بلکه یک استراتژی (Strategy) کامل است که چهار وظیفه کلیدی را به صورت خودکار انجام میدهد:
تحلیل بازار (بر اساس یک موتور امتیازدهی کمی)
صدور سیگنال (ورود و خروج شفاف)
مدیریت ریسک پویا (محاسبه خودکار حد ضرر)
مدیریت حجم پوزیشن (محاسبه خودکار حجم بر اساس ریسک)
هدف «طلاجوی» تبدیل معاملهگری شهودی به یک فرآیند مکانیکی، مبتنی بر داده و مدیریت ریسک است.
⚙️ قابلیتهای کلیدی (آنچه دریافت میکنید)
این استراتژی مجهز به مجموعهای از ابزارهای حرفهای است که مستقیماً روی چارت شما اجرا میشوند:
🎯 ۱. سیگنالهای ورود و خروج شفاف
فلشهای واضح خرید (▲) و فروش (▼) که نقاط دقیق ورود بر اساس منطق استراتژی را مشخص میکنند. این سیستم تنها زمانی سیگنال صادر میکند که فیلترهای روند، همسویی لازم را تایید کنند.
🛡️ ۲. مدیریت ریسک پویای ATR
بزرگترین چالش معاملهگران، تعیین حد ضرر (SL) مناسب است. این استراتژی حد ضرر را به صورت خودکار و پویا بر اساس نوسانات واقعی بازار (با استفاده از ATR) محاسبه میکند.
نتیجه: در بازارهای پرنوسان، استاپ شما برای جلوگیری از استاپهانت شدن، فاصله ایمنتری میگیرد و در بازارهای آرام، بهینهتر و نزدیکتر تنظیم میشود.
💰 ۳. محاسبه خودکار حجم پوزیشن
دیگر نیازی به «ماشین حساب پوزیشن» ندارید. استراتژی به صورت اتوماتیک، حجم دقیق هر معامله را بر اساس درصد ریسک ثابتی که شما از کل سرمایهتان تعیین میکنید، محاسبه مینماید. این ویژگی، مدیریت سرمایه حرفهای را در تمام معاملات شما تضمین میکند.
🎨 ۴. نواحی بصری سود و زیان (TP/SL)
هنگامی که یک معامله باز است، این ابزار به صورت زنده، نواحی حد سود (سبز) و حد ضرر (قرمز) را مشابه ابزار پوزیشن خود تریدینگ ویو، مستقیماً روی چارت برای شما رسم میکند.
📈 ۵. پنل آمار عملکرد پیشرفته
یک جدول آماری جامع که تمام معیارهای کلیدی عملکرد شما را به صورت زنده نمایش میدهد:
سود و زیان خالص (دلاری و درصدی)
ضریب سود (Profit Factor)
نرخ موفقیت (Win Rate)
تعداد معاملات سودده / زیانده
حداکثر افت سرمایه (Max Drawdown)
و موارد دیگر...
🚦 ۶. آیکونهای بازخورد معامله
با آیکونهای هوشمند، فوراً کیفیت معاملات بسته شده خود را ارزیابی کنید:
😎🚀 (سود ویژه و قابل توجه)
💰 (سود عادی)
🙈 (زیان)
📈 چگونه از این ابزار استفاده کنید؟
«طلاجوی» یک 'ماشین چاپ پول' جادویی نیست، بلکه یک ابزار تست و اجرای حرفهای است.
۱. بکتست و بهینهسازی (Backtesting)
مهمترین قدرت این اسکریپت، قابلیت Strategy بودن آن است. شما میتوانید این استراتژی را روی هر جفتارز و تایم فریمی که معامله میکنید (طلا، کریپتو، جفتارزها و...) بکتست بگیرید تا آمار عملکرد آن را مشاهده کنید.
۲. تنظیم پارامترها
از طریق منوی تنظیمات، پارامترهای کلیدی مانند درصد ریسک، نسبت ریسک به ریوارد (R:R)، و فیلترهای زمانی را مطابق با سبک معاملاتی و دارایی مورد نظر خود بهینهسازی کنید.
۳. اجرای سیستماتیک
پس از یافتن تنظیمات بهینه در بکتست، در معاملات زنده به سیگنالها پایبند بمانید و اجازه دهید منطق مکانیکی، معاملات شما را مدیریت کند.
⚠️ سلب مسئولیت مهم (مطابق با قوانین TradingView)
این اسکریپت صرفاً یک ابزار تحلیلی و معاملاتی است و نباید به عنوان سیگنال مالی یا توصیهای برای خرید و فروش تلقی شود. تمام معاملات دارای ریسک هستند و نتایج گذشته تضمینکننده عملکرد آینده نمیباشد.
لطفاً قبل از استفاده از این استراتژی در حساب واقعی، آن را به طور کامل در حالت دمو یا بکتست ارزیابی کنید. مسئولیت تمامی سودها و زیانها بر عهده خود معاملهگر است.
💎 TalaJooy V1.31 𓅂 Trading Strategy
TalaJooy (meaning "Gold Seeker") is a complete, professional trading framework for TradingView, designed to remove guesswork, emotion, and impulsive decisions from your trading process.
This is not a simple signal indicator; it is a complete Strategy script that automates four key tasks:
Market Analysis (Based on a quantitative scoring engine)
Signal Generation (Clear entries and exits)
Dynamic Risk Management (Automated Stop Loss calculation)
Position Sizing (Automated trade sizing based on risk)
The goal of "TalaJooy" is to transform intuitive trading into a mechanical, data-driven, and risk-managed process.
⚙️ Key Features (What You Get)
This strategy comes equipped with a suite of professional tools that run directly on your chart:
🎯 1. Clear Entry & Exit Signals
Receive unambiguous Buy (▲) and Sell (▼) arrows identifying precise entry points based on the strategy's logic. The system only generates signals when its trend-confirmation filters are aligned.
🛡️ 2. Dynamic ATR Risk Management
A trader's biggest challenge is setting a proper Stop Loss (SL). This strategy calculates your SL automatically and dynamically based on real-time market volatility (using ATR).
The Benefit: In volatile markets, your stop is placed at a safer distance to avoid being "stopped out" by noise. In calm markets, it's set tighter and more efficiently.
💰 3. Automated Position Sizing
Stop using external "position size calculators." The strategy automatically calculates the exact trade size for every position based on a fixed risk percentage of your total equity (which you define). This enforces professional money management on every trade.
🎨 4. Visual Profit & Loss (TP/SL) Zones
While a trade is active, this tool plots live, visual zones for your Take Profit (green) and Stop Loss (red) targets, similar to TradingView's native "Long/Short Position" tool.
📈 5. Advanced Performance Stats Panel
A comprehensive statistics table displays all your key performance metrics in real-time:
Net Profit (% and $)
Profit Factor
Win Rate
Win / Loss Trade Count
Max Drawdown
And more...
🚦 6. Smart Trade Feedback Icons
Instantly review the quality of your closed trades with intelligent emoji feedback:
😎🚀 (Exceptional Profit)
💰 (Standard Profit)
🙈 (Loss)
📈 How to Use This Tool
"TalaJooy" is not a "magic money machine"; it is a professional-grade tool for testing and execution.
1. Backtesting & Optimization
The most powerful feature of this script is its Strategy component. You can backtest it on any asset or timeframe you trade (Gold, Crypto, Forex, etc.) to see its historical performance data.
2. Parameter Tuning
Use the settings menu to optimize key parameters—such as Risk Percentage, Risk:Reward Ratio, and core filter settings—to match your personal trading style and preferred assets.
3. Systematic Execution
After identifying optimal settings via backtesting, adhere to the signals in your live trading and let the mechanical logic manage your trades.
⚠️ Important Disclaimer (TradingView Compliant)
This script is provided for educational and analytical purposes only. It is not financial advice or a recommendation to buy or sell any asset. All trading involves substantial risk. Past performance is not indicative of future results.
Please thoroughly evaluate this strategy via backtesting or paper trading before deploying it with real funds. The user assumes full responsibility for all profits and losses incurred.
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
Binary Options Fast Scalping [TradingFinder] M1 & M5 Signals🔵 Introduction
In the structure of financial markets, spiky moments and sudden price movements play a key role in Liquidity Grabs and Market Structure Resets. These movements usually occur after the accumulation of orders in Buy Side or Sell Side Liquidity zones and are accompanied by rapid breaks in the form of Break of Structure (BoS) or Change of Character (CHoCH).
At this stage, the market temporarily moves in the direction of liquidity to trigger counter orders and then enters a Retracement or Pullback phase, a point where professional traders using the Smart Money Concept (SMC) look for candle confirmation to enter with precision.
This strategy is built upon the same logic : an initial spiky move as a signal of institutional or liquidity driven algorithms, followed by a controlled pullback toward areas such as the Order Block, Fair Value Gap (FVG), or Imbalance Zone, and finally an entry based on a strong confirmation candle (Engulf, Rejection, Breaker) that defines the true direction of order flow.
This combination of price behavior, especially on lower timeframes such as M1 or M5, provides an ideal setup for fast Scalping, Micro Structure Trading, and even short term directional prediction in Binary Options Trading.
Since the main focus of this method is on identifying liquidity phases, structural confirmations, and momentum confirmation candles, the trader can design entries with high probability and logical stop loss placement using the concepts of Fractal Market Structure and Multi Timeframe Confirmation.
In the scalping version, the main objective is to capture the move toward the next liquidity pool or opposite demand and supply zone, while in the binary version, only the prediction of the next candle’s direction matters. This strategy inherently operates based on Smart Money Behavior, Liquidity Engineering, and Order Flow Dynamics, allowing the extraction of fast and profitable moves from the internal logic of market structure.
🔵 How to Use
The operational logic of this strategy is based on Liquidity Sweep, Pullback, and Confirmation Candle. The trader should first identify the initial Impulse Move, which is often accompanied by liquidity absorption around Buy Side or Sell Side Liquidity areas. After that, the market enters the Retracement phase and returns to structural zones such as the Order Block or the Fair Value Gap (FVG).
At this point, a position is taken only when a confirmation candle (Engulf, Breaker, or Rejection Candle) closes in the direction of continuation and aligns with the new structure (BOS or CHoCH). Applying this model on lower timeframes offers the highest precision for fast Scalping or for predicting the next candle’s direction in Binary Option trading.
🟣 Bullish Setup
In the bullish setup, the market first forms a spiky upward move with a sudden increase in momentum, indicating the activation of liquidity flow in the Buy Side Liquidity zone. This movement is usually accompanied by a Break of Structure (BOS) to the upside and marks the beginning of the Impulse Move phase. After this move, the price enters the Pullback phase and returns to structural areas such as the Bullish Order Block, Fair Value Gap (FVG), or Mitigation zone.
At this stage, the trader waits for a bullish confirmation candle (Bullish Engulf or Breaker Candle) to validate the end of the retracement. Entry is made at the close of the confirmation candle or on a minor pullback, with the stop loss placed below the Swing Low or below the pullback zone. The target is set at the next Buy Side Liquidity or Equal Highs. In the binary version, only the direction of the next candle matters and the entry takes place immediately after the confirmation candle.
🟣 Bearish Setup
In the bearish setup, the market first forms a spiky downward move, signaling increased selling pressure and liquidity absorption at the Sell Side Liquidity zone. This movement is accompanied by a Break of Structure (BOS) to the downside and represents the beginning of a bearish momentum phase. After the spike, the price enters the Retracement phase and returns to the Bearish Order Block or bearish Fair Value Gap zone. Within these areas, the formation of a bearish confirmation candle (Bearish Engulf, Breaker, or Rejection Candle) validates the continuation of the downtrend.
The entry is taken at the close of the confirmation candle, with the stop loss placed above the Swing High or above the pullback zone, and the target set toward the next Sell Side Liquidity or Equal Lows. In binary applications, only the direction of the next candle is considered and the confirmation candle serves as the entry trigger.
🔵 Conclusion
This strategy, by combining the principles of the Smart Money Concept, Liquidity Dynamics, and Candle Confirmation Logic, offers a precise and multi functional approach to market entry. Its core structure, identifying the initial spiky movement, waiting for a structural pullback, and entering based on a confirmation candle allows quick interpretation of institutional liquidity behavior and provides trading opportunities with high accuracy and controlled risk.
On lower timeframes, this logic becomes a powerful tool for Scalping and Micro Structure Trading, while in binary markets it delivers high success rates due to its focus on predicting the next candle’s direction. Built upon the foundations of Order Flow, Market Structure, and Fractal Liquidity Behavior, this strategy demonstrates that even in the fastest and noisiest market conditions, the order of Smart Money remains observable and exploitable.
AI Bot Regime Feed (v6) — stableThis indicator generates real-time, structured JSON alerts for external trading bots or automation systems.
It combines multiple technical layers to identify market regimes and high-probability buy/sell events, and sends them to any webhook endpoint (e.g., a FastAPI or Zapier listener).
