Session Volume Analyzer [JOAT]
Session Volume Analyzer — Global Trading Session and Volume Intelligence System
This indicator addresses the analytical challenge of understanding market participation patterns across global trading sessions. It combines precise session detection with comprehensive volume analysis to provide insights into when and how different market participants are active. The tool recognizes that different trading sessions exhibit distinct characteristics in terms of participation, volatility, and volume patterns.
Why This Combination Provides Unique Analytical Value
Traditional session indicators typically only show time boundaries, while volume indicators show raw volume data without session context. This creates analytical gaps:
1. **Session Context Missing**: Volume spikes without session context provide incomplete information
2. **Participation Patterns Hidden**: Different sessions have different participant types (retail, institutional, algorithmic)
3. **Comparative Analysis Lacking**: No easy way to compare volume patterns across sessions
4. **Timing Intelligence Absent**: Understanding WHEN volume occurs is as important as HOW MUCH volume occurs
This indicator's originality lies in creating an integrated session-volume analysis system that:
**Provides Session-Aware Volume Analysis**: Volume data is contextualized within specific trading sessions
**Enables Cross-Session Comparison**: Compare volume patterns between Asian, London, and New York sessions
**Delivers Participation Intelligence**: Understand which sessions are showing above-normal participation
**Offers Real-Time Session Tracking**: Know exactly which session is active and how current volume compares
Technical Innovation and Originality
While session detection and volume analysis exist separately, the innovation lies in:
1. **Integrated Session-Volume Architecture**: Simultaneous tracking of session boundaries and volume statistics creates comprehensive market participation analysis
2. **Multi-Session Volume Comparison System**: Real-time calculation and comparison of volume statistics across different global sessions
3. **Adaptive Volume Threshold Detection**: Automatic identification of above-average volume periods within session context
4. **Comprehensive Visual Integration**: Session backgrounds, volume highlights, and statistical dashboards provide complete market participation picture
How Session Detection and Volume Analysis Work Together
The integration creates a sophisticated market participation analysis system:
**Session Detection Logic**: Uses Pine Script's time functions to identify active sessions
// Session detection based on exchange time
bool inAsian = not na(time(timeframe.period, asianSession))
bool inLondon = not na(time(timeframe.period, londonSession))
bool inNY = not na(time(timeframe.period, nySession))
// Session transition detection
bool asianStart = inAsian and not inAsian
bool londonStart = inLondon and not inLondon
bool nyStart = inNY and not inNY
**Volume Analysis Integration**: Volume statistics are calculated within session context
// Session-specific volume accumulation
if asianStart
asianVol := 0.0
asianBars := 0
if inAsian
asianVol += volume
asianBars += 1
// Real-time session volume analysis
float asianAvgVol = asianBars > 0 ? asianVol / asianBars : 0
**Relative Volume Assessment**: Current volume compared to session-specific averages
float volMA = ta.sma(volume, volLength)
float volRatio = volMA > 0 ? volume / volMA : 1
// Volume classification within session context
bool isHighVol = volRatio >= 1.5 and volRatio < 2.5
bool isVeryHighVol = volRatio >= 2.5
This creates a system where volume analysis is always contextualized within the appropriate trading session, providing more meaningful insights than raw volume data alone.
Comprehensive Session Analysis Framework
**Default Session Definitions** (customizable based on broker timezone):
- **Asian Session**: 1800-0300 (exchange time) - Represents Asian market participation including Tokyo, Hong Kong, Singapore
- **London Session**: 0300-1200 (exchange time) - Represents European market participation
- **New York Session**: 0800-1700 (exchange time) - Represents North American market participation
**Session Overlap Analysis**: The system recognizes and highlights overlap periods:
- **London/New York Overlap**: 0800-1200 - Typically the highest volume period
- **Asian/London Overlap**: 0300-0300 (brief) - Transition period
- **New York/Asian Overlap**: 1700-1800 (brief) - End of NY, start of Asian
**Volume Intelligence Features**:
1. **Session-Specific Volume Accumulation**: Tracks total volume within each session
2. **Cross-Session Volume Comparison**: Compare current session volume to other sessions
3. **Relative Volume Detection**: Identify when current volume exceeds historical averages
4. **Participation Pattern Analysis**: Understand which sessions show consistent high/low participation
Advanced Volume Analysis Methods
**Relative Volume Calculation**:
float volMA = ta.sma(volume, volLength) // Volume moving average
float volRatio = volMA > 0 ? volume / volMA : 1 // Current vs average ratio
// Multi-tier volume classification
bool isNormalVol = volRatio < 1.5
bool isHighVol = volRatio >= 1.5 and volRatio < 2.5
bool isVeryHighVol = volRatio >= 2.5
bool isExtremeVol = volRatio >= 4.0
**Session Volume Tracking**:
// Cumulative session volume with bar counting
if londonStart
londonVol := 0.0
londonBars := 0
if inLondon
londonVol += volume
londonBars += 1
// Average volume per bar calculation
float londonAvgVol = londonBars > 0 ? londonVol / londonBars : 0
**Cross-Session Volume Comparison**:
The system maintains running totals for each session, enabling real-time comparison of participation levels across different global markets.
What the Display Shows
Session Backgrounds — Colored backgrounds indicating which session is active
- Pink: Asian session
- Blue: London session
- Green: New York session
Session Open Lines — Horizontal lines at each session's opening price
Session Markers — Labels (AS, LN, NY) when sessions begin
Volume Highlights — Bar coloring when volume exceeds thresholds
- Orange: High volume (1.5x+ average)
- Red: Very high volume (2.5x+ average)
Dashboard — Current session, cumulative volume, and averages
Color Scheme
Asian — #E91E63 (pink)
London — #2196F3 (blue)
New York — #4CAF50 (green)
High Volume — #FF9800 (orange)
Very High Volume — #F44336 (red)
Inputs
Session Times:
Asian Session window (default: 1800-0300)
London Session window (default: 0300-1200)
New York Session window (default: 0800-1700)
Volume Settings:
Volume MA Length (default: 20)
High Volume threshold (default: 1.5x)
Very High Volume threshold (default: 2.5x)
Visual Settings:
Session colors (customizable)
Show/hide backgrounds, lines, markers
Background transparency
How to Read the Display
Background color shows which session is currently active
Session open lines show where each session started
Orange/red bars indicate above-average volume
Dashboard shows cumulative volume for each session today
Alerts
Session opened (Asian, London, New York)
High volume bar detected
Very high volume bar detected
Important Limitations and Realistic Expectations
Session times are approximate and depend on your broker's server timezone—manual adjustment may be required for accuracy
Volume data quality varies significantly by broker, instrument, and market type
Cryptocurrency and some forex markets trade continuously, making traditional session boundaries less meaningful
High volume indicates participation level only—it does not predict price direction or market outcomes
Session participation patterns can change over time due to market structure evolution, holidays, and economic conditions
This tool displays historical and current market participation data—it cannot predict future volume or price movements
Volume spikes can occur for numerous reasons unrelated to directional price movement (news, algorithmic trading, etc.)
Different instruments exhibit different session sensitivity and volume patterns
Market holidays and special events can significantly alter normal session patterns
Appropriate Use Cases
This indicator is designed for:
- Market participation pattern analysis
- Session-based trading schedule planning
- Volume context and comparison across sessions
- Educational study of global market structure
- Supplementary analysis for session-based strategies
This indicator is NOT designed for:
- Standalone trading signal generation
- Volume-based price direction prediction
- Automated trading system triggers
- Guaranteed session pattern repetition
- Replacement of fundamental or sentiment analysis
Understanding Session Analysis Limitations
Session analysis provides valuable context but has inherent limitations:
- Session patterns can change due to economic conditions, holidays, and market structure evolution
- Volume patterns may not repeat consistently across different market conditions
- Global events can override normal session characteristics
- Different asset classes respond differently to session boundaries
- Technology and algorithmic trading continue to blur traditional session distinctions
— Made with passion by officialjackofalltrades
F#forex
Ocean Master [JOAT]Ocean Master QE - Advanced Oceanic Market Analysis with Quantum Flow Dynamics
Overview
Ocean Master QE is an open-source overlay indicator that combines multiple analytical techniques into a unified market analysis framework. It uses ATR-based dynamic channels, volume-weighted order flow analysis, multi-timeframe correlation (quantum entanglement concept), and harmonic oscillator calculations to provide traders with a comprehensive view of market conditions.
What This Indicator Does
The indicator calculates and displays several key components:
Dynamic Price Channels - ATR-adjusted upper, middle, and lower channels that adapt to current volatility conditions
Order Flow Analysis - Separates buying and selling volume pressure to calculate a directional delta
Smart Money Index - Volume-weighted order flow metric that highlights potential institutional activity
Harmonic Oscillator - Weighted combination of 10 Fibonacci-period EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) to identify trend direction
Multi-Timeframe Correlation - Measures price correlation across 1H, 4H, and Daily timeframes
Wave Function Analysis - Momentum-based state detection that identifies when price action becomes decisive
How It Works
The core channel calculation uses ATR with a configurable quantum sensitivity factor:
float atr = ta.atr(i_atrLength)
float quantumFactor = 1.0 + (i_quantumSensitivity * 0.1)
float quantumATR = atr * quantumFactor
upperChannel := ta.highest(high, i_length) - (quantumATR * 0.5)
lowerChannel := ta.lowest(low, i_length) + (quantumATR * 0.5)
midChannel := (upperChannel + lowerChannel) * 0.5
Order flow is calculated by separating volume into buy and sell components based on candle direction:
The harmonic oscillator weights shorter EMAs more heavily using inverse weighting (1/1, 1/2, 1/3... 1/10), creating a responsive yet smooth trend indicator.
Signal Generation
Confluence signals require multiple conditions to align:
Bullish: Harmonic oscillator crosses above zero + positive Smart Money Index + positive Order Flow Delta
Bearish: Harmonic oscillator crosses below zero + negative Smart Money Index + negative Order Flow Delta
Dashboard Panel (Top-Right)
Bias - Current market direction based on price vs mid-channel
Entanglement - Multi-timeframe correlation score (0-100%)
Wave State - COLLAPSED (decisive) or SUPERPOSITION (uncertain)
Volume - Current volume relative to 20-period average
Volatility - ATR as percentage of price
Smart Money - Volume-weighted order flow reading
Visual Elements
Ocean Depth Layers - Gradient fills between channel levels representing different price zones
Channel Lines - Upper (surface), middle, and lower (seabed) dynamic levels
Divergence Markers - Triangle shapes when harmonic oscillator crosses zero
Confluence Labels - BULL/BEAR labels when multiple factors align
Suggested Use Cases
Identify trend direction using the harmonic oscillator and channel position
Monitor order flow for potential institutional activity
Use multi-timeframe correlation to confirm trade direction across timeframes
Watch for confluence signals where multiple factors align
Input Parameters
Length (default: 14) - Base period for channel and indicator calculations
ATR Length (default: 14) - Period for ATR calculation
Quantum Depth (default: 3) - Complexity factor for calculations
Quantum Sensitivity (default: 1.5) - Channel width multiplier
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide smoother signals; lower timeframes require faster reaction times and may produce more noise.
Limitations
Multi-timeframe requests add processing overhead
Order flow estimation is based on candle direction, not actual order book data
Correlation calculations require sufficient historical data
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
Trend Strength Matrix [JOAT]Trend Strength Matrix — Multi-Timeframe Confluence Analysis System
This indicator addresses a specific analytical challenge: how to efficiently compare multiple technical measurements across different timeframes while accounting for their varying scales and interpretations. Rather than managing separate indicator windows with different scales, this tool normalizes four distinct analytical approaches to a common -1 to +1 scale and presents them in a unified matrix format.
Why This Combination Adds Value
The core problem this indicator solves is analytical fragmentation. Traders often use multiple indicators but struggle with:
1. **Scale Inconsistency**: RSI ranges 0-100, MACD has no fixed range, ADX ranges 0-100 but measures strength not direction
2. **Timeframe Coordination**: Checking multiple timeframes requires switching between charts or cramming multiple indicators
3. **Cognitive Load**: Processing different indicator types simultaneously creates mental overhead
4. **Confluence Assessment**: Determining when multiple approaches agree requires manual comparison
This indicator specifically addresses these issues by creating a standardized analytical framework where different measurement approaches can be directly compared both within and across timeframes.
Originality and Technical Innovation
While the individual components (RSI, MACD, ADX, Moving Average) are standard, the originality lies in:
1. **Unified Normalization System**: Each component is mathematically transformed to a -1 to +1 scale using component-specific normalization that preserves the indicator's core characteristics
2. **Multi-Timeframe Weighting Algorithm**: Higher timeframes receive proportionally more weight (40% current, 25% next, 20% third, 15% fourth) based on the principle that longer timeframes provide more significant context
3. **Real-Time Confluence Scoring**: The composite calculation provides an instant assessment of how much the different analytical approaches agree
4. **Adaptive Visual Encoding**: The heatmap format allows immediate pattern recognition of agreement/disagreement across both indicators and timeframes
How the Components Work Together
Each component measures a different aspect of market behavior, and their combination provides a more complete analytical picture:
**Momentum Component (RSI-based)**: Measures the velocity of price changes by comparing average gains to losses
**Trend Component (MACD-based)**: Measures the relationship between fast and slow moving averages, indicating trend acceleration/deceleration
**Strength Component (ADX-based)**: Measures trend strength regardless of direction, then applies directional bias
**Position Component (MA-based)**: Measures price position relative to a reference average
The mathematical relationship between these components creates a comprehensive view:
- When all four agree (similar colors), it suggests multiple analytical approaches are aligned
- When they disagree (mixed colors), it highlights analytical uncertainty or transition periods
- The composite score quantifies the degree of agreement numerically
Detailed Component Analysis
**1. Momentum Oscillator Component**
This component transforms RSI into a centered oscillator by subtracting 50 and dividing by 50, creating a -1 to +1 range where 0 represents equilibrium between buying and selling pressure.
// Momentum calculation normalized to -1 to +1 scale
float rsi = ta.rsi(close, rsiLength)
float rsiScore = (rsi - 50) / 50
// Result: 0 at equilibrium, +1 at extreme overbought, -1 at extreme oversold
**2. Moving Average Convergence Component**
MACD is normalized by its own volatility (standard deviation) to create a bounded oscillator. This prevents the unbounded nature of MACD from dominating the composite calculation.
// MACD normalized by its historical volatility
= ta.macd(close, macdFast, macdSlow, macdSignal)
float macdStdev = ta.stdev(macdLine, 100)
float macdScore = macdStdev != 0 ? math.max(-1, math.min(1, macdLine / (macdStdev * 2))) : 0
**3. Directional Movement Component**
This combines ADX (strength) with directional movement (+DI vs -DI) to create a directional strength measurement. ADX alone shows strength but not direction; this component adds directional context.
// ADX-based directional strength
= calcADX(adxLength)
float adxStrength = math.min(adx / 50, 1) // Normalize ADX to 0-1
float adxDirection = plusDI > minusDI ? 1 : -1 // Direction bias
float adxScore = adxStrength * adxDirection // Combine strength and direction
**4. Price Position Component**
This measures price deviation from a moving average, weighted by the magnitude of deviation to distinguish between minor and significant displacements.
// Price position relative to moving average
float ma = ta.sma(close, maLength)
float maDirection = close > ma ? 1 : -1
float maDeviation = math.abs(close - ma) / ma * 10 // Percentage deviation scaled
float maScore = math.max(-1, math.min(1, maDirection * math.min(maDeviation, 1)))
Multi-Timeframe Integration Logic
The multi-timeframe system uses a weighted average that gives more influence to higher timeframes:
// Timeframe weighting system
float currentTF = composite * 0.40 // Current timeframe: 40%
float higherTF1 = composite_tf2 * 0.25 // Next higher: 25%
float higherTF2 = composite_tf3 * 0.20 // Third higher: 20%
float higherTF3 = composite_tf4 * 0.15 // Fourth higher: 15%
float multiTFComposite = currentTF + higherTF1 + higherTF2 + higherTF3
This weighting reflects the principle that higher timeframes provide more significant context for market direction, while lower timeframes provide timing precision.
What the Dashboard Shows
The heatmap displays a grid where:
Each row represents a timeframe
Each column shows one component's normalized reading
Colors indicate the value: green shades for positive, red shades for negative, gray for neutral
The rightmost column shows the composite average for that timeframe
Visual Elements
Moving Average Line — A simple moving average plotted on the price chart
Background Tint — Subtle coloring based on the composite score
Shift Labels — Markers when the composite crosses threshold values
Dashboard Table — The main heatmap display
Inputs
Calculation Parameters:
Momentum Length (default: 14)
MACD Fast/Slow/Signal (default: 12/26/9)
Directional Movement Length (default: 14)
Moving Average Length (default: 50)
Timeframe Settings:
Enable/disable multi-timeframe analysis
Select additional timeframes to display
How to Read the Display
Similar colors across a row indicate the components are showing similar readings
Mixed colors indicate the components are showing different readings
The composite percentage shows the average of all four components
Alerts
Composite crossed above/below threshold values
Strong readings (above 50% or below -50%)
Important Limitations and Realistic Expectations
This indicator displays current analytical conditions—it does not predict future price movements
Agreement between components indicates current analytical alignment, not future price direction
All four components are based on historical price data and inherently lag price action
Market conditions can change rapidly, making current readings irrelevant
Different parameter settings will produce different readings and interpretations
No combination of technical indicators can reliably predict future market behavior
Strong readings in one direction do not guarantee continued movement in that direction
The composite score reflects mathematical relationships, not market fundamentals or sentiment
This tool should be used as one input among many in a comprehensive analytical approach
Appropriate Use Cases
This indicator is designed for:
- Analytical organization and efficiency
- Multi-timeframe confluence assessment
- Pattern recognition in indicator relationships
- Educational study of how different analytical approaches relate
- Supplementary analysis alongside other methods
This indicator is NOT designed for:
- Standalone trading signals
- Guaranteed profit generation
- Market timing precision
- Replacement of fundamental analysis
- Automated trading systems
— Made with passion by officialjackofalltrades
Futures Ultra CVD (Pure )Futures Ultra CVD (Pure)
Futures Ultra CVD (Pure) is a volume-driven Cumulative Volume Delta (CVD) indicator designed to expose real buying and selling pressure behind price movement. Unlike price-only indicators, this script analyzes how volume is distributed within each bar to determine whether aggressive buyers or sellers are in control, then tracks how that pressure evolves over time.
This version is intentionally pure and ungated: it does not rely on external symbols, market filters, session bias, or macro confirmation. All signals are derived strictly from price, volume, and delta behavior of the active chart, making it suitable for futures, equities, crypto, and FX.
Core Concept: How CVD Is Calculated
For each bar, volume is split into buying pressure and selling pressure using the bar’s price position:
Buying volume increases as price closes closer to the high
Selling volume increases as price closes closer to the low
The difference between buying and selling volume forms Delta:
Positive delta = net aggressive buying
Negative delta = net aggressive selling
This delta is then accumulated into Cumulative Volume Delta (CVD) using one of three user-selectable modes:
Total – running cumulative sum of all delta values
Periodic – rolling sum over a fixed lookback period
EMA – smoothed cumulative delta using an exponential average
This flexibility allows traders to choose between raw order-flow tracking or smoother, trend-like behavior depending on timeframe and instrument.
Visual Structure & Histogram Logic
The CVD is displayed as a column histogram, not a line, to emphasize momentum and pressure shifts.
Enhanced coloring provides additional context:
Brighter green/red bars indicate increasing momentum
Muted colors indicate stalling or weakening pressure
Optional footprint-style highlights appear when buy or sell volume overwhelms the opposite side by a user-defined imbalance factor
This allows traders to visually distinguish:
Strength vs weakness
Continuation vs exhaustion
Absorption and aggressive participation
Built-In Order Flow Signals
The script automatically detects and labels key order-flow events:
Strong Delta
Triggered when delta exceeds a user-defined threshold, highlighting unusually aggressive buying or selling.
Delta Surge
Detects sudden expansion in delta compared to the prior bar, often associated with breakout attempts or liquidation events.
Zero-Line Crosses
Marks transitions between net bullish and bearish participation as CVD crosses above or below zero.
CVD Continuation Logic (Trend Confirmation)
Beyond raw delta, the script evaluates CVD structure to identify continuation conditions:
A bullish continuation requires:
Positive and rising CVD
Strong buy delta
Confirmation from at least one of the following:
CVD above its EMA and SMA
Bullish price expansion
Sustained positive delta pressure
Bearish continuation follows the inverse logic.
These continuation signals are designed to confirm participation strength, not predict reversals.
Conflict Detection (Divergence Warning)
The indicator also flags conflict conditions, where:
Strong buying occurs while CVD remains negative
Strong selling occurs while CVD remains positive
These scenarios often precede failed breakouts, absorption zones, or short-term reversals and can be used as cautionary signals.
Alerts & Practical Use
All major events include built-in alerts:
Strong delta
Delta surge
CVD continuations
Zero-line crosses
Buy/sell imbalances
Conflict signals
Alerts can be set to trigger on bar close or intrabar in real time, depending on trader preference.
How Traders Typically Use This Indicator
Confirm breakouts with delta participation
Validate trends using CVD continuation instead of price alone
Identify absorption or exhaustion via conflicts and imbalances
Combine with price structure, VWAP, or market profile tools
This script is not a trading system by itself. It is a decision-support tool designed to reveal what price alone cannot: who is actually in control of the market.
On-Chart Symbols & What They Mean
This script uses a small number of visual symbols to communicate order-flow events clearly and consistently. All symbols are derived directly from the Cumulative Volume Delta calculations described above.
Δ+ (Green Up Arrow)
Strong Buy Delta
Indicates that buying pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market buying dominating selling volume
Often appears during breakouts, trend acceleration, or initiative buying
This symbol does not imply direction by itself; it only confirms strong buyer participation.
Δ− (Red Down Arrow)
Strong Sell Delta
Indicates that selling pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market selling dominating buying volume
Often appears during breakdowns, liquidation events, or initiative selling
Like Δ+, this symbol measures participation strength, not trade direction.
↑ (Green Label Up)
CVD Bullish Continuation
Appears when all of the following are present:
CVD is positive and increasing
Strong buy delta is detected
At least one confirmation condition is met:
CVD is above its EMA and SMA
Price shows bullish expansion
Consecutive positive delta bars (sustained buying pressure)
This symbol highlights trend continuation supported by volume, not a reversal signal.
↓ (Red Label Down)
CVD Bearish Continuation
Appears when:
CVD is negative and decreasing
Strong sell delta is detected
At least one confirmation condition is met:
CVD is below its EMA and SMA
Price shows bearish expansion
Consecutive negative delta bars (sustained selling pressure)
This indicates bearish continuation with participation confirmation.
Cyan / Orange Histogram Bars
Footprint-Style Volume Imbalance
Cyan bars indicate buy volume exceeds sell volume by the imbalance factor
Orange bars indicate sell volume exceeds buy volume by the imbalance factor
These bars highlight areas where one side is overwhelming the other, often associated with absorption, initiative moves, or failed auctions.
Bright vs Muted Histogram Colors
CVD Momentum State
Bright colors = CVD increasing in the direction of its current bias
Muted colors = CVD losing momentum or stalling
This allows quick visual identification of strengthening vs weakening participation.
Conflict Alerts (No Symbol by Default)
Delta vs CVD Disagreement
These conditions trigger alerts (but no fixed chart icon):
Strong buying while CVD remains negative
Strong selling while CVD remains positive
Conflicts often signal absorption, trap conditions, or short-term exhaustion.
Important Usage Notes
All symbols are informational, not trade entries.
Signals are calculated from price-based volume distribution, not true bid/ask data.
Results depend on the quality of volume data provided by the exchange and TradingView.
Liquidity Maxing [JOAT]Liquidity Maxing - Institutional Liquidity Matrix
Introduction
Liquidity Maxing is an open-source strategy for TradingView built around institutional market structure concepts. It identifies structural shifts, evaluates trades through multi-factor confluence, and implements layered risk controls.
The strategy is designed for swing trading on 4-hour timeframes, focusing on how institutional order flow manifests in price action through structure breaks, inducements, and liquidity sweeps.
Core Functionality
Liquidity Maxing performs three primary functions:
Tracks market structure to identify when control shifts between buyers and sellers
Scores potential trades using an eight-factor confluence system
Manages position sizing and risk exposure dynamically based on volatility and user-defined limits
The goal is selective trading when multiple conditions align, rather than frequent entries.
Market Structure Engine
The structure engine tracks three key events:
Break of Structure (BOS): Price pushes beyond a prior pivot in the direction of trend
Change of Character (CHoCH): Control flips from bullish to bearish or vice versa
Inducement Sweeps (IDM): Market briefly runs stops against trend before moving in the real direction
The structure module continuously updates strong highs and lows, labeling structural shifts visually. IDM markers are optional and disabled by default to maintain chart clarity.
The trade engine requires valid structure alignment before considering entries. No structure, no trade.
Eight-Factor Confluence System
Instead of relying on a single indicator, Liquidity Maxing uses an eight-factor scoring system:
Structure alignment with current trend
RSI within healthy bands (different ranges for up and down trends)
MACD momentum agreement with direction
Volume above adaptive baseline
Price relative to main trend EMA
Session and weekend filter (configurable)
Volatility expansion/contraction via ATR shifts
Higher-timeframe EMA confirmation
Each factor contributes one point to the confluence score. The default minimum confluence threshold is 6 out of 8, but you can adjust this from 1-8 based on your preference for trade frequency versus selectivity.
Only when structure and confluence agree does the strategy proceed to risk evaluation.
Dynamic Risk Management
Risk controls are implemented in multiple layers:
ATR-based stops and targets with configurable risk-to-reward ratio (default 2:1)
Volatility-adjusted position sizing to maintain consistent risk per trade as ranges expand or compress
Daily and weekly risk budgets that halt new entries once thresholds are reached
Correlation cooldown to prevent clustered trades in the same direction
Global circuit breaker with maximum drawdown limit and emergency kill switch
If any guardrail is breached, the strategy will not open new positions. The dashboard clearly displays risk state for transparency.
Market Presets
The strategy includes configuration presets optimized for different market types:
Crypto (BTC/ETH): RSI bands 70/30, volume multiplier 1.2, enhanced ATR scaling
Forex Majors: RSI bands 75/25, volume multiplier 1.5
Indices (SPY/QQQ): RSI bands 70/30, volume multiplier 1.3
Custom: Default values for user customization
For crypto assets, the strategy automatically applies ATR volatility scaling to account for higher volatility characteristics.
Monitoring and Dashboards
The strategy includes optional monitoring layers:
Risk Operations Dashboard (top-right):
Trend state
Confluence score
ATR value
Current position size percentage
Global drawdown
Daily and weekly risk consumption
Correlation guard state
Alert mode status
Performance Console (top-left):
Net profit
Current equity
Win rate percentage
Average trade value
Sharpe-style ratio (rolling 50-bar window)
Profit factor
Open trade count
Optional risk tint on chart background provides visual indication of "safe to trade" versus "halted" state.
All visualization elements can be toggled on/off from the inputs for clean chart viewing or full telemetry during parameter tuning.
Alerts and Automation
The strategy supports alert integration with two formats:
Standard alerts: Human-readable messages for long, short, and risk-halt conditions
Webhook format: JSON-formatted payloads ready for external execution systems (optional)
Alert messages are predictable and unambiguous, suitable for manual review or automated forwarding to execution engines.
Built-in Validation Suite
The strategy includes an optional validation layer that can be enabled from inputs. It checks:
Internal consistency of structure and confluence metrics
Sanity and ordering of risk parameters
Position sizing compliance with user-defined floors and caps
This validation is optional and not required for trading, but provides transparency into system operation during development or troubleshooting.
Strategy Parameters
Market Presets:
Configuration Preset: Choose between Crypto (BTC/ETH), Forex Majors, Indices (SPY/QQQ), or Custom
Market Structure Architecture:
Pivot Length: Default 5 bars
Filter by Inducement (IDM): Default enabled
Visualize Structure: Default enabled
Structure Lookback: Default 50 bars
Risk & Capital Preservation:
Risk:Reward Ratio: Default 2.0
ATR Period: Default 14
ATR Multiplier (Stop): Default 2.0
Max Drawdown Circuit Breaker: Default 10%
Risk per Trade (% Equity): Default 1.5%
Daily Risk Limit: Default 6%
Weekly Risk Limit: Default 12%
Min Position Size (% Equity): Default 0.25%
Max Position Size (% Equity): Default 5%
Correlation Cooldown (bars): Default 3
Emergency Kill Switch: Default disabled
Signal Confluence:
RSI Length: Default 14
Trend EMA: Default 200
HTF Confirmation TF: Default Daily
Allow Weekend Trading: Default enabled
Minimum Confluence Score (0-8): Default 6
Backtesting Considerations
When backtesting this strategy, consider the following:
Commission: Default 0.05% (adjustable in strategy settings)
Initial Capital: Default $100,000 (adjustable)
Position Sizing: Uses percentage of equity (default 2% per trade)
Timeframe: Optimized for 4-hour charts, though can be tested on other timeframes
Results will vary significantly based on:
Market conditions and volatility regimes
Parameter settings, especially confluence threshold
Risk limit configuration
Symbol characteristics (crypto vs forex vs equities)
Past performance does not guarantee future results. Win rate, profit factor, and other metrics should be evaluated in context of drawdown periods, trade frequency, and market conditions.
How to Use This Strategy
This is a framework that requires understanding and parameter tuning, not a one-size-fits-all solution.
Recommended workflow:
Start on 4-hour timeframe with default parameters and appropriate market preset
Run backtests and study performance console metrics: focus on drawdown behavior, win rate, profit factor, and trade frequency
Adjust confluence threshold to match your risk appetite—higher thresholds mean fewer but more selective trades
Set realistic daily and weekly risk budgets appropriate for your account size and risk tolerance
Consider ATR multiplier adjustments based on market volatility characteristics
Only connect alerts or automation after thorough testing and parameter validation
Treat this as a risk framework with an integrated entry engine, not merely an entry signal generator. The risk controls are as important as the trade signals.
Strategy Limitations
Designed for swing trading timeframes; may not perform optimally on very short timeframes
Requires sufficient market structure to identify pivots; may struggle in choppy or low-volatility environments
Crypto markets require different parameter tuning than traditional markets
Risk limits may prevent entries during favorable setups if daily/weekly budgets are exhausted
Correlation cooldown may delay entries that would otherwise be valid
Backtesting results depend on data quality and may not reflect live trading with slippage
Design Philosophy
Many indicators tell you when price crossed a moving average or RSI left oversold. This strategy addresses questions institutional traders ask:
Who is in control of the market right now?
Is this move structurally significant or just noise?
Do I want to add more risk given what I've already done today/week?
If I'm wrong, exactly how painful can this be?
The strategy provides disciplined, repeatable answers to these questions through systematic structure analysis, confluence filtering, and multi-layer risk management.
Technical Implementation
The strategy uses Pine Script v6 with:
Custom types for structure, confluence, and risk state management
Functional programming approach for reusable calculations
State management through persistent variables
Optional visual elements that can be toggled independently
The code is open-source and can be modified to suit individual needs. All important logic is visible in the source code.
Disclaimer
This script is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation. Trading involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by historical tests of strategies, is not indicative of future results.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between backtested results and actual results subsequently achieved by any particular trading strategy.
The user should be aware of the risks involved in trading and should trade only with risk capital. The authors and publishers of this script are not responsible for any losses or damages, including without limitation, any loss of profit, which may arise directly or indirectly from use of or reliance on this script.
This strategy uses technical analysis methods and indicators that are not guaranteed to be accurate or profitable. Market conditions change, and strategies that worked in the past may not work in the future. Users should thoroughly test any strategy in a paper trading environment before risking real capital.
Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, and other factors not captured in backtesting.
The user assumes full responsibility for all trading decisions made using this script. Always consult with a qualified financial advisor before making investment decisions.
Enjoy - officialjackofalltrades
Arbitrage Detector [LuxAlgo]The Arbitrage Detector unveils hidden spreads in the crypto and forex markets. It compares the same asset on the main crypto exchanges and forex brokers and displays both prices and volumes on a dashboard, as well as the maximum spread detected on a histogram divided by four user-selected percentiles. This allows traders to detect unusual, high, typical, or low spreads.
This highly customizable tool features automatic source selection (crypto or forex) based on the asset in the chart, as well as current and historical spread detection. It also features a dashboard with sortable columns and a historical histogram with percentiles and different smoothing options.
🔶 USAGE
Arbitrage is the practice of taking advantage of price differences for the same asset across different markets. Arbitrage traders look for these discrepancies to profit from buying where it’s cheaper and selling where it’s more expensive to capture the spread.
For begginers this tool is an easy way to understand how prices can vary between markets, helping you avoid trading at a disadvantage.
For advanced traders it is a fast tool to spot arbitrage opportunities or inefficiencies that can be exploited for profit.
Arbitrage opportunities are often short‑lived, but they can be highly profitable. By showing you where spreads exist, this tool helps traders:
Understand market inefficiencies
Avoid trading at unfavorable prices
Identify potential profit opportunities across exchanges
As we can see in the image, the tool consists of two main graphics: a dashboard on the main chart and a histogram in the pane below.
Both are useful for understanding the behavior of the same asset on different crypto exchanges or forex brokers.
The tool's main goal is to detect and categorize spread activity across the major crypto and forex sources. The comparison uses data from up to 19 crypto exchanges and 13 forex brokers.
🔹 Forex or Crypto
The tool selects the appropriate sources (crypto exchanges or forex brokers) based on the asset in the chart. Traders can choose which one to use.
The image shows the prices and volumes for Bitcoin and the euro across the main sources, sorted by descending average price over the last 20 days.
🔹 Dashboard
The dashboard displays a list of all sources with four main columns: last price, average price, volume, and total volume.
All four columns can be sorted in ascending or descending order, or left unsorted. A background gradient color is displayed for the sorted column.
Price and volume delta information between the chart asset and each exchange can be enabled or disabled from the settings panel.
🔹 Histogram
The histogram is excellent for visualizing historical values and comparing them with the asset price.
In this case, we have the Euro/U.S. Dollar daily chart. As we can see, the unusual spread activity detected since 2016, with values at or above 98%, is usually a good indication of increased trader activity, which may result in a key price area where the market could turn around.
By default, the histogram has the gradient and smoothing auto features enabled.
The differences are visible in the chart above. On top is an adaptive moving average with higher values for unusual activity. At the bottom is an exponential moving average with a length of 9.
The differences between the gradient and solid colors are evident. In the first case, the colors are in sync with the data values, becoming more yellow with higher values and more green with lower values. In the second case, the colors are solid and only distinguish data above or below the defined percentiles.
🔶 SETTINGS
Sources: Choose between crypto exchanges, forex brokers, or automatic selection based on the asset in the chart.
Average Length: Select the length for the price and volume averages.
🔹 Percentiles
Percentile Length: Select the length for the percentile calculation, or enable the use of the full dataset. Enabling this option may result in runtime errors due to exceeding the allotted resources.
Unusual % >: Select the unusual percentile.
High % >: Select the high percentile.
Typical % >: Select the typical percentile.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Sorting: Select the sorting column and direction.
Position: Select the dashboard location.
Size: Select the dashboard size.
Price Delta: Show the price difference between each exchange and the asset on the chart.
Volume Delta: Show the volume difference between each exchange and the asset on the chart.
🔹 Style
Unusual: Enable the plot of the unusual percentile and select its color.
High: Enable the plot of the high percentile and select its color.
Typical: Enable the plot of the typical percentile and select its color.
Low: Select the color for the low percentile.
Percentiles Auto Color: Enable auto color for all plotted percentiles.
Histogram Gradient: Enable the gradient color for the histogram.
Histogram Smoothing: Select the length of the EMA smoothing for the histogram or enable the Auto feature. The Auto feature uses an adaptive moving average with the data percent rank as the efficiency ratio.
3 EMA with Alerts 2025This indicator plots three key EMAs (20, 50, and 200) directly on the chart, making it easy to track short-, medium-, and long-term trends. A color-coded table is displayed in the top-right corner for quick reference.
The script also includes smart alerts that trigger only when the state changes:
• 🔵 EMA 20 crossing above EMA 50 & EMA 200 → Bullish signal
• 🔴 EMA 20 crossing below EMA 50 & EMA 200 → Bearish signal
This tool is designed for traders who want clean visuals, reliable alerts, and simplified trend recognition in 2025 markets.
VWAP Flow ParmezanThe "Official Bank Flow VWAP" is a comprehensive trading suite designed for institutional Forex traders.
This indicator solves the problem of chart clutter by combining two critical components of liquidity: Price (Value) and Time (Sessions). It is specifically optimized for EUR/USD and GBP/USD on intraday timeframes (M5, M15), helping you identify high-probability setups where "Fair Value" meets "Volatility."
Key Features
1. Multi-Timeframe VWAP Hierarchy Unlike standard indicators, this tool visualizes the interaction between three distinct timeframes:
Daily VWAP (Dynamic Color): Your primary trend filter. Green when Bullish (Price > VWAP), Red when Bearish (Price < VWAP).
Weekly VWAP (Orange Dots): Represents the medium-term balance. Acts as a magnet for mean reversion mid-week.
Monthly VWAP (Purple Line): The institutional "line in the sand." Major support/resistance level.
2. Standard Deviation Bands (Market Balance) The indicator plots SD1 and SD2 bands around the Daily VWAP:
Inner Zone (SD1): Represents the "Fair Value" area.
Outer Bands (SD2): Represents overbought/oversold conditions. Useful for identifying mean reversion plays back to the center.
3. Official Exchange Sessions (Time) Forget confusing "killzones." This tool highlights the Official Open times for major exchanges, adjusted for Daylight Savings via New York time:
London Open (08:00 LDN): The start of European volume.
New York Open (08:00 NY): The injection of US liquidity.
London Close/Fix: The daily overlap close, often marking trend reversals.
Note: Sessions are visualized with non-intrusive black "shadow" backgrounds to keep your chart clean.
4. "Ghost" Levels (Previous VWAP) A unique feature that plots the closing VWAP level of the previous day. Institutional algorithms often target these "untested" levels as Take Profit targets or liquidity pools.
How to Use
Trend Following: If Price is above the Daily VWAP (Green) during the London Open, look for Long entries targeting the SD1/SD2 upper bands.
Mean Reversion: If Price hits the SD2 Band while far away from the Weekly VWAP, look for a reversal back to the mean.
Confluence: The strongest signals occur when price touches a key VWAP level (e.g., Weekly VWAP) specifically during the highlighted Session Start times.
Settings
Timezone: Defaults to America/New_York to automatically handle DST shifts for London/NY opens.
Visuals: Fully customizable colors and transparency. Default is set to a "Dark Mode" friendly professional palette.
VCAI Stochastic RSI+VCAI Stoch RSI+ is a cleaned-up Stochastic RSI built with V-Core colours for faster, clearer momentum reads and more reliable OB/OS signals.
What it shows:
Purple %K line → bearish momentum strengthening
Yellow %D line → bullish momentum building and smoothing
Soft purple/yellow background bands → OB/OS exhaustion zones, not just raw 80/20 triggers
Midline at 50 → balance point where momentum shifts between bull- and bear-side control
Optional HTF mode → run Stoch RSI from any timeframe while viewing it on your current chart
How to read it:
Both lines rising out of OS → early bullish shift; pullbacks that hold direction favour continuation
Both lines falling from OB → early bearish shift; bounces into the purple OB zone can become fade setups
Lines stacked and moving together → strong, cleaner momentum
Lines crossing repeatedly → low-conviction, choppy conditions
OB/OS shading highlights exhaustion so you focus on moves with context, not every 80/20 tick
Why it’s different:
Classic Stoch RSI is hyper-sensitive and mostly noise.
VCAI Stoch RSI+ applies V-Core’s colour-driven regime logic, controlled OB/OS shading, and optional HTF smoothing so you see momentum structure instead of clutter — making it easier to judge when momentum is genuinely shifting and when it’s just another wiggle.
VCAI RSI Divergence +VCAI RSI Divergence+ is an RSI that shows trend, momentum, and divergence using V-CoresAI colour logic instead of a single white line.
What it shows:
Yellow RSI line → bullish momentum (RSI above its MA; buy-side pressure in control)
Purple RSI line → bearish momentum (RSI below its MA; sell-side pressure in control)
Thin blue line → fast RSI moving average that drives the colour flips
Dashed 70/30 lines → classic OB/OS zones
Background bands → soft purple in OB, soft yellow in OS to mark exhaustion areas
How to read it:
Yellow & rising → momentum shifting bullish; pullbacks into yellow OS band can be accumulation zones
Purple & falling → momentum shifting bearish; pushes into purple OB band can be distribution/sell zones
Hard colour flips (yellow ↔ purple) mark trend regime changes, not minor RSI noise
Divergence mode (on/off)
The divergence engine scans RSI and price pivot structure:
Bullish divergence (yellow) → price lower low + RSI higher low
Bearish divergence (purple) → price higher high + RSI lower high
Lines and tags appear only where a meaningful disagreement between price and RSI exists, giving early context for potential reversals or fade setups.
Together, the momentum colours + optional divergence mapping give a far clearer market read than a standard RSI, with zero clutter and no guesswork.
VCAI Volume LiteVCAI Volume Lite is a clean, modern take on volume analysis designed for traders who want a clearer read on participation without loading multiple indicators.
This Lite edition focuses on the essentials:
real activity vs dead sessions
expansion vs contraction
momentum shifts around breakouts and pullbacks
No hype, no filters, no hidden logic — just a straightforward volume tool rebuilt with the VCAI visual framework.
Use it to quickly spot:
stronger moves backed by genuine participation
weak pushes running on low volume
areas where momentum may stall or accelerate
Part of the VCAI Lite Series.
FVG Maxing - Fair Value Gaps, Equilibrium, and Candle Patterns
What this script does
This open-source indicator highlights 3-candle fair value gaps (FVGs) on the active chart timeframe, draws their midpoint ("equilibrium") line, tracks when each gap is mitigated, and optionally marks simple candle patterns (engulfing and doji) for confluence. It is intended as an educational tool to study how price interacts with imbalances.
3-candle bullish and bearish FVG zones drawn as forward-extending boxes.
Equilibrium line at 50% of each gap.
Different styling for mitigated vs unmitigated gaps.
Compact statistics panel showing how many gaps are currently active and filled.
Optional overlays for bullish/bearish engulfing patterns and doji candles.
1. FVG logic (3-candle gaps)
The script focuses on a strict 3-candle definition of a fair value gap:
Three consecutive candles with the same body direction.
The wick of candle 3 is separated from the wick of candle 1 (no overlap).
A bullish gap is created when price moves up fast enough to leave a gap between candle 1 and 3. A bearish gap is the mirror case to the downside.
In Pine, the core detection looks like this:
// Three candles with the same body direction
bull_seq = close > open and close > open and close > open
bear_seq = close < open and close < open and close < open
// Wick gap between candle 1 and candle 3
bull_gap = bull_seq and low > high
bear_gap = bear_seq and high < low
// Final FVG flags
is_bull_fvg = bull_gap
is_bear_fvg = bear_gap
For each detected FVG:
Bullish FVG range: from high up to low (gap below current price).
Bearish FVG range: from low down to high (gap above current price).
Each zone is stored in a custom FVGData structure so it can be updated when price later trades back inside it.
2. Equilibrium line (0.5 of the gap)
Every FVG box gets an optional equilibrium line plotted at the midpoint between its top and bottom:
eq_level = (top + bottom) / 2.0
right_index = extend_boxes ? bar_index + extend_length_bars : bar_index
bx = box.new(bar_index - 2, top, right_index, bottom)
eq_ln = line.new(bar_index - 2, eq_level, right_index, eq_level)
line.set_style(eq_ln, line.style_dashed)
line.set_color(eq_ln, eq_color)
You can use this line as a neutral “fair value” reference inside the zone, or as a simple way to think in terms of premium/discount within each gap.
3. Mitigation rules and styling
Each FVG stays active until price trades back into the gap:
Bullish FVG is considered mitigated when the low touches or moves below the top of the gap.
Bearish FVG is considered mitigated when the high touches or moves above the bottom of the gap.
When that happens, the script:
Marks the internal FVGData entry as mitigated.
Softens the box fill and border colors.
Optionally updates the label text from "BULL EQ / BEAR EQ" to "BULL FILLED / BEAR FILLED".
Can hide mitigated zones almost completely if you only want to see unfilled imbalances.
This allows you to distinguish between current areas of interest and zones that have already been traded through.
4. Candle pattern overlays (engulfing and doji)
For additional confluence, the script can mark simple candle patterns on top of the FVG view:
Bullish engulfing — current candle body fully wraps the previous bearish body and is larger in size.
Bearish engulfing — current candle body fully wraps the previous bullish body and is larger in size.
Doji — candles where the real body is small relative to the full range (high–low).
The detection is based on basic body and range geometry:
curr_body = math.abs(close - open)
prev_body = math.abs(close - open )
curr_range = high - low
body_ratio = curr_range > 0 ? curr_body / curr_range : 1.0
bull_engulfing = close > open and close < open and open <= close and close >= open and curr_body > prev_body
bear_engulfing = close < open and close > open and open >= close and close <= open and curr_body > prev_body
is_doji = curr_range > 0 and body_ratio <= doji_body_ratio
On the chart, they appear as:
Small triangle markers below bullish engulfing candles.
Small triangle markers above bearish engulfing candles.
Small circles above doji candles.
All three overlays are optional and can be turned on or off and recolored in the CANDLE PATTERNS group of inputs.
5. Inputs overview
The script organizes settings into clear groups:
DISPLAY SETTINGS : Show bullish/bearish FVGs, show/hide mitigated zones, box extension length, box border width, and maximum number of boxes.
EQUILIBRIUM : Toggle equilibrium lines, color, and line width.
LABELS : Enable labels, choose whether to label unmitigated and/or mitigated zones, and select label size.
BULLISH COLORS / BEARISH COLORS : Separate fill and border colors for bullish and bearish gaps.
MITIGATED STYLE : Opacity used when a gap is marked as mitigated.
STATISTICS : Toggle the on-chart FVG statistics panel.
CANDLE PATTERNS : Show engulfing patterns, show dojis, colors, and the body-to-range threshold that defines a doji.
6. Statistics panel
An optional table in the corner of the chart summarizes the current state of all tracked gaps:
Total number of FVGs still being tracked.
Number of bullish vs bearish FVGs.
Number of unfilled vs mitigated FVGs.
Simple fill rate: percentage of tracked FVGs that have been marked as mitigated.
This can help you study how a particular market tends to treat gaps over time.
7. How you might use it (examples)
These are usage ideas only, not recommendations:
Study how often your symbol mitigates gaps and where inside the zone price tends to react.
Use higher-timeframe context and then refine entries near the equilibrium line on your trading timeframe.
Combine FVG zones with basic candle patterns (engulfing/doji) as an extra visual anchor, if that fits your process.
Hope you enjoy, give your feedback in the comments!
- officialjackofalltrades
VectorCoresAI SMA + Bollinger Fusion v1VectorCoresAI — SMA + Bollinger Fusion (Free)
A clean, modern visual tool combining four key SMAs with an adaptive Bollinger structure.
This script merges two of the most widely used charting concepts into one simple, readable view:
Included
✔ SMA 21
✔ SMA 50
✔ SMA 100
✔ SMA 200
✔ Bollinger Bands with adjustable length + multiplier
✔ Adaptive “Fusion Squeeze” shading to highlight compression phases
✔ Optional visibility toggles for each SMA
✔ Lightweight, non-intrusive overlay
What this indicator is designed for
This tool helps traders quickly understand:
Trend alignment using the 21/50/100/200 SMAs
Volatility conditions around the Bollinger midline
Price compression and expansion
Early awareness of breakout environments
Clean visual structure without clutter
Everything is intentionally simple and transparent.
No predictions, no signals, no trading advice — just clean chart structure.
Why this version is unique
Instead of using standard Bollinger visuals, this Fusion edition uses subtle adaptive shading to show when the bands contract.
This makes compression zones instantly visible without overwhelming the chart.
The SMAs are fixed to widely-used trend levels, giving consistent readings across all markets and timeframes.
Who this is for
Newer traders who want a clear introduction to SMAs + Bollinger Bands
Experienced traders who want a lightweight visual tool
Anyone building structure-based strategies
Users of the VectorCoresAI suite who want a simple companion tool
Notes
This indicator is part of the VectorCoresAI Free Tools collection.
All logic is open-source and educational only.
More tools coming soon.
FX OSINT - Institutional Midnight Intelligence For ForexFX OSINT — Institutional Midnight Intelligence For Forex
See Your FX Charts Like an Intelligence Briefing, Not a Guess
If you’ve ever stared at EURUSD or GBPJPY and thought:
Where is the real liquidity?
Is this move sponsored by smart money or just noise?
Am I buying into premium or discount?
…then FX OSINT is designed for you.
FX OSINT (Forex Open Source Intelligence) treats the FX market the way an analyst treats an investigation:
Collect open‑source signals from price, time, and volatility.
Map out liquidity, structure, and sessions in a repeatable way.
Present them in a clean, non‑cluttered dashboard so you can read context quickly.
No rainbow spaghetti. No 12 indicators stacked on top of each other. Just structured information, midnight visuals, and a clear read on what the market is doing right now.
Why FX OSINT Exists
Many FX traders run into the same problems:
Overloaded charts – multiple indicators fighting for space, none talking to each other.
Signals with no context – arrows that ignore structure, sessions, and liquidity.
Tools not tuned for FX – generic indicators that don’t care what pair you are on.
FX OSINT brings this together into one FX‑focused framework that:
Understands structure : BOS/CHOCH, swings, and trend across multiple timeframes.
Respects liquidity : sweeps, order blocks, and FVGs with controlled visibility.
Reads volatility & ADR : how far today’s range has developed.
Knows the clock : London, New York, and key killzones.
Scores confluence : a 0–100 engine that summarizes how much is lining up.
FX OSINT is built for traders who want structured, institutional‑style logic with a disciplined, midnight‑themed UI —not flashing buy/sell buttons.
1. Midnight Dashboard — Top‑Right Intelligence Panel
This panel acts as your compact “situation room”:
CONFLUENCE — 0–100 score blending trend alignment, volatility regime, sessions, liquidity events, order blocks, FVGs, and ADR context.
REGIME — Low / Building / Normal / Expansion / Extreme, driven by ATR relationships, so you know if you’re in chop, trend, or expansion.
HTF / MTF / LTF TREND — Higher‑, medium‑, and current‑timeframe bias in one place, so you see if you are trading with or against the larger flow.
ADR USED — How much of today’s typical range has already been consumed in percentage terms.
PIP VALUE — Approximate pip size per pair, including JPY‑style pairs.
Everything is bold, legible, and color‑coded, but the layout stays minimal so you can:
Look once → understand the context.
2. Structure, BOS, CHOCH — Smart‑Money‑Style Skeleton
FX OSINT tracks swing highs and lows, then shows how structure evolves:
Trend logic based on evolving swings, not just a moving average cross.
BOS (Break of Structure) when price expands in the direction of trend.
CHOCH (Change of Character) when behavior flips and the market structure changes.
Labels are selective, not spammy . You don’t get a tag on every minor wiggle—only when structure meaningfully shifts, so it’s easier to answer:
"Are we continuing the current leg, or did something actually change here?"
3. Liquidity Sweeps, Order Blocks & FVGs — The OSINT Layer
FX OSINT treats liquidity as a key information layer:
Liquidity sweeps — Detects when price spikes through recent highs/lows and then snaps back, flagging potential stop runs.
Order blocks — The last opposite candle before a displacement move, drawn as controlled boxes with limited lifespan to avoid clutter.
Fair Value Gaps (FVGs) — Three‑candle imbalances rendered as precise zones with a cap on how many can exist at once.
Under the hood, boxes are managed so your chart does not become a wall of old zones:
// Draw Order Blocks with overlap prevention
if isBullishOB and showOrderBlocks
if array.size(obBoxes) >= maxBoxes
oldBox = array.shift(obBoxes)
box.delete(oldBox)
newBox = box.new(bar_index , low , bar_index + obvLength, high ,
border_color = bullColor, bgcolor = bullColorTransp,
border_width = 2, extend = extend.none)
array.push(obBoxes, newBox)
Box limits keep the number of zones under control.
Borders and transparency are tuned so you still see price clearly.
You end up with a curated liquidity map , rather than a chart buried under every level price has ever touched.
4. Volatility, ADR & Sessions — Time and Range Intelligence
FX OSINT runs a Volatility Regime Analyzer and an ADR engine in the background:
Volatility regime — Five states (Low → Extreme) derived from fast vs. slow ATR.
ADR bands — Daily high/mid/low projected from the current daily open.
ADR used % — How far today’s move has traveled relative to its typical range.
On the time side:
Asia, London, New York sessions are softly highlighted with a single active background to avoid overlapping colors.
Killzones (e.g., London and New York opens) can be emphasized when you want to focus on where significant moves often begin.
Together, this helps you answer:
"What time is it in the trading day?"
"How stretched are we?"
"Is expansion just starting, or are we late to the move?"
5. ICT‑Style Add‑Ons — BOS/CHOCH, Premium/Discount, and Confluence
For modern FX / ICT‑inspired workflows, FX OSINT includes:
BOS / CHOCH labels — Clear structural shifts based on swings.
Premium / Discount zones — 25%, 50%, 75% levels of the daily range, so you know if you are buying discount in an uptrend or selling premium in a downtrend.
Confluence score — A single number summarizing how many conditions line up in the current context.
Instead of replacing your plan, FX OSINT compresses your checklist into the chart:
Structure
Liquidity
Session / Time
Volatility / ADR
Higher‑timeframe alignment
When these agree, the dashboard reflects it. When they don’t, it stays neutral and lets you see the conflict.
How To Use FX OSINT
FX OSINT is not a signal bot. It is an information engine that organizes context so you can apply your own plan.
A typical workflow might look like:
Start on higher timeframes (e.g., H4/D1) to form directional bias from structure, volatility regime, and ADR context.
Move to intraday timeframes (e.g., M15/H1) around your chosen sessions (London and/or New York).
Look for confluence :
HTF / MTF / LTF trends aligned.
Price in discount for longs or premium for shorts.
Recent liquidity sweep into a meaningful OB or FVG.
Confluence score at or above a level you consider significant.
Then refine entries using BOS/CHOCH on lower timeframes according to your own risk and execution rules.
FX OSINT aims to make sure you do not enter a trade without seeing:
Where you are in the day (ADR and sessions).
Where you are in the volatility cycle (regime).
Who currently appears in control (structure and trend).
Which liquidity was just targeted (sweeps and zones).
Design Choices and Scope
FX OSINT was designed around a few clear constraints:
FX‑focused — Logic and filters tuned for FX majors, minors, exotics, and metals. It is intended for FX markets, not for every possible asset class.
Open‑source — The full Pine Script code is available so you can read it, learn from it, and adapt it to your own workflow if needed.
Clear themes — Two main visual styles (e.g., dark institutional “midnight” and a lighter accent variant) with a focus on readability, not visual noise.
Chart‑friendly — Panels use fixed areas, session highlights avoid overlapping, and boxes are capped/pruned so the chart remains usable.
FX OSINT is for only Forex pairs, not anything else!
Hope you enjoyed and remember your Open Source Intelligence Matters 😉!
-officialjackofalltrades
Auto Position CalculatorA position sizing tool that automatically detects the instrument you're trading and calculates the correct position size based on your risk parameters.
What It Does
This indicator calculates how many contracts, lots, or shares to trade based on your account size, risk percentage, and stop loss distance. It auto-detects the instrument type and adjusts the point/pip value accordingly.
Supported Instruments
Futures: NQ, MNQ, ES, MES, YM, MYM, RTY, M2K, CL, MCL, GC, MGC
Forex: All major pairs (USD, EUR, GBP, JPY, etc.)
Index CFDs: NAS100, US500, US30, GER40, UK100
Metals: XAU, XAG
Crypto and Stocks: Automatic detection
How to Use
Set your account size and risk % in settings
Click the settings icon and place Entry, Stop Loss, and Take Profit on the chart
The position size and risk calculations appear automatically
Levels auto-reset at your chosen session (Asia, London, or New York open)
Limitations
CFD and forex pip values assume standard lot sizing - your broker may differ
Auto-detection relies on ticker naming conventions, which vary by broker/data feed
Session reset times are based on ET (Eastern Time)
XAUUSD Fisher Transform Dashboard — Trend & Momentum InsightsThe script offers an educational visualization of trend and momentum on XAUUSD by combining the Fisher Transform with EMA direction. It plots momentum shifts, trend alignment, and includes a concise dashboard showing trend bias, the latest crossover event, and customizable percentage-based reference markers.
This tool is for market analysis and study purposes only and does not provide trading advice.
XenoSmooth Predictive Candles - Advanced Heikin Ashi CandlesXenoSmooth Predictive Candles
Summary in one paragraph
A synthetic candle engine for crypto, FX, equities, and futures on intraday to swing timeframes. It reduces noise and flip delay so structure is easier to read. The core novelty is a predictive open with inertia plus slope lead fused with a zero lag body filter and an overshoot based wick model normalized by the real range and capped by ATR. Add it to a clean chart, hide regular candles if desired, and tune lengths. Shapes can move while the bar is open and settle on close. For conservative workflows read on bar close.
Scope and intent
• Markets. Major FX pairs, index futures, large cap equities, liquid crypto
• Timeframes. One minute to daily
• Purpose. Faster and smoother visual structure than Heikin Ashi while keeping causality and realistic wicks
Originality and usefulness
• Unique concept. Predictive open with inertia and slope lead plus selectable zero lag body filter and ATR capped wick overshoot in percent of real range
• Failure mode addressed. Late flips in chop and unreal long wicks from raw extremes
• Testability. Every control is an input. Users can toggle body method, lengths, clipping, and percent modeling
• Portable yardstick. ATR based wick cap and percent of bar range scale across symbols
Method overview in plain language
Build a robust base price from O, H, L, and extra weight on Close. Smooth it with a chosen filter to produce the synthetic close. Drive a predictive open that follows the synthetic close with tunable inertia and a small lead from the last bar slope. Model wicks as the portion of the real extremes that extends beyond the synthetic body, smooth that overshoot, normalize by the bar range if selected, then cap by ATR to avoid tail spikes. Clamp synthetic values to the real high and low if enabled.
Base measures
• Range basis. True Range for the ATR cap and High minus Low for percent normalization
• Return basis. Not used
Components
• Body Base Blend. Weighted O H L with a close bias to stabilize the base
• Zero Lag Body Filter. ZLEMA or Super Smoother or WMA to set the synthetic close
• Predictive Open. Inertial follow of the synthetic close plus a slope lead term
• Wick Overshoot Model. Smoothed extension beyond the body, optional percent of real range, ATR cap
• Clamp Option. Keeps synthetic open and close inside the real bar range
Fusion rule
• Synthetic close equals filtered base
• Synthetic open equals previous open plus inertia times distance to synthetic close plus slope lead
• Wicks equal smoothed overshoot above and below the body, optionally percent of range then converted back to price and capped by ATR
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction. Not applicable
• Session windows. Not applicable
Logic
• Body length. Core smoothing length for the synthetic close. Typical 6 to 14. Higher gives smoother and slower. Lower gives faster flips
• Body method. ZLEMA or Super Smoother or WMA. ZLEMA is fastest. Super Smoother is calmest
• Close weight in base. 0 to 1. Higher gives stronger emphasis on close and less noise
• Open inertia. 0 to 1. Higher makes the open follow the close more tightly
• Lead gain. 0 to 1. Higher adds more phase lead. Keep modest to avoid overshoot
• Clamp body to real range. On keeps synthetic body inside high and low
• Wick smooth length. Typical 4 to 10. Higher reduces jitter
• Overshoot as percent. On stabilizes wicks across regimes
• ATR length. Typical 10 to 20 for the cap
• Max wick equals ATR times. 0 disables. 1.0 to 2.0 contains extreme tails
Filters
• Efficiency or trend filter. Not used
• Micro versus macro range relation. Not used
• Location filter. Not used
Realism and responsible publication
• No performance claims
• Intrabar motion reminder. Shapes can move while a bar forms and settle on close
• Strategies must use standard candles for signals and orders
Honest limitations and failure modes
• High impact releases and thin liquidity can distort wicks and produce gaps that any smoother cannot predict
• Very quiet regimes can reduce contrast. Consider longer body length
• Session time on the chart controls the definition of each bar
RightFlow Universal Volume Profile - Any Market Any TimeframeSummary in one paragraph
RightFlow is a right anchored microstructure volume profile for stocks, futures, FX, and liquid crypto on intraday and daily timeframes. It acts only when several conditions align inside a session window and presents the result as a compact right side profile with value area, POC, a bull bear mix by price bin, and a HUD of profile VWAP and pressure shares. It is original because it distributes each bar’s weight into multiple mid price slices, blends bull bear pressure per bin with a CLV based split, and grows the profile to the right so price action stays readable. Add to a clean chart, read the table, and use the visuals. For conservative workflows read on bar close.
Scope and intent
• Markets. Major FX pairs, index futures, large cap equities and ETFs, liquid crypto.
• Timeframes. One minute to daily.
• Default demo used in the publication. SPY on 15 minute.
• Purpose. See where participation concentrates, which side dominated by price level, and how far price sits from VA and POC.
Originality and usefulness
• Unique fusion. Right anchored growth plus per bar slicing and CLV split, with weight modes Raw, Notional, and DeltaProxy.
• Failure mode addressed. False reads from single bar direction and coarse binning.
• Testability. All parts sit in Inputs and the HUD.
• Portable yardstick. Value Area percent and POC are universal across symbols.
• Protected scripts. Not applicable. Method and use are fully disclosed.
Method overview in plain language
Pick a scope Rolling or Today or This Week. Define a window and number of price bins. For each bar, split its range into small slices, assign each slice a weight from the selected mode, and split that weight by CLV or by bar direction. Accumulate totals per bin. Find the bin with the highest total as POC. Expand left and right until the chosen share of total volume is covered to form the value area. Compute profile VWAP for all, buyers, and sellers and show them with pressure shares.
Base measures
Range basis. High minus low and mid price samples across the bar window.
Return basis. Not used. VWAP trio is price weighted by weights.
Components
• RightFlow Bins. Price histogram that grows to the right.
• Bull Bear Split. CLV based 0 to 1 share or pure bar direction.
• Weight Mode. Raw volume, notional volume times close, or DeltaProxy focus.
• Value Area Engine. POC then outward expansion to target share.
• HUD. Profile VWAP, Buy and Sell percent, winner delta, split and weight mode.
• Session windows optional. Scope resets on day or week.
Fusion rule
Color of each bin is the convex blend of bull and bear shares. Value area shading is lighter inside and darker outside.
Signal rule
This is context, not a trade signal. A strong separation between buy and sell percent with price holding inside VA often confirms balance. Price outside VA with skewed pressure often marks initiative moves.
What you will see on the chart
• Right side bins with blended colors.
• A POC line across the profile width.
• Labels for POC, VAH, and VAL.
• A compact HUD table in the top right.
Table fields and quick reading guide
• VWAP. Profile VWAP.
• Buy and Sell. Pressure shares in percent.
• Delta Winner. Winner side and margin in percent.
• Split and Weight. The active modes.
Reading tip. When Session scope is Today or This Week and Buy minus Sell is clearly positive or negative, that side often controls the day’s narrative.
Inputs with guidance
Setup
• Profile scope. Rolling or session reset. Rolling uses window bars.
• Rolling window bars. Typical 100 to 300. Larger is smoother.
Binning
• Price bins. Typical 32 to 128. More bins increase detail.
• Slices per bar. Typical 3 to 7. Raising it smooths distribution.
Weighting
• Weight mode. Raw, Notional, DeltaProxy. Notional emphasizes expensive prints.
• Bull Bear split. CLV or BarDir. CLV is more nuanced.
• Value Area percent. Typical 68 to 75.
View
• Profile width in bars, color split toggle, value area shading, opacities, POC line, VA labels.
Usage recipes
Intraday trend focus
• Scope Today, bins 64, slices 5, Value Area 70.
• Split CLV, Weight Notional.
Intraday mean reversion
• Scope Today, bins 96, Value Area 75.
• Watch fades back to POC after initiative pushes.
Swing continuation
• Scope Rolling 200 bars, bins 48.
• Use Buy Sell skew with price relative to VA.
Realism and responsible publication
No performance claims. Shapes can move while a bar forms and settle on close. Education only.
Honest limitations and failure modes
Thin liquidity and data gaps can distort bin weights. Very quiet regimes reduce contrast. Session time is the chart venue time.
Open source reuse and credits
None.
Legal
Education and research only. Not investment advice. Test on history and simulation before live use.
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Reactive Curvature Smoother Moving Average IndicatorSummary in one paragraph
RCS MA is a reactive curvature smoother for any liquid instrument on intraday through swing timeframes. It helps you act only when context strengthens by adapting its window length with a normalized path energy score and by smoothing with robust residual weights over a quadratic fit, then optionally blending a capped one step forecast. Add it to a clean chart and watch the single colored line. Shapes can shift while a bar forms and settle on close. For conservative use, judge on bar close.
Scope and intent
• Markets: major FX pairs, index futures, large cap equities, liquid crypto
• Timeframes: one minute to daily
• Purpose: reduce lag in trends while resisting chop and outliers
• Limits: indicator only, no orders
Originality and usefulness
• Novelty: adaptive window selection by minimizing normalized path energy with directionality bias, plus Huber weighted residuals and curvature aware penalty, finished with a mintick capped forecast blend
• Failure modes addressed: whipsaws from fixed length MAs and outlier spikes that pull means
• Testable: Inputs expose all components and optional diagnostics show chosen length, directionality, and energy
• Portable yardstick: forecast cap uses mintick to stay symbol aware
Method overview in plain language
Base measures
• Range span of the tested window and a path energy defined as the sum of squared price increments, normalized by span
Components
Adaptive window chooser: scans L between Min and Max using an energy over trend score and picks the lowest score
Robust smoother: fits a quadratic to the last L bars, computes residuals, applies Huber weights and an exponential residual penalty scaled down when curvature is high
Forecast blend: projects one step ahead from the quadratic, caps displacement by a multiple of mintick, blends by user weight
Fusion rule
• Final line equals robust mean plus optional capped forecast blend
Signal rule
• Visual bias only: color turns lime when close is above the line, red otherwise
What you will see on the chart
• One colored line that tightens in trends and relaxes in chop
• Optional debug overlays for core value, chosen L, directionality, and energy
• Optional last bar label with L, directionality, and energy
• Reminder: drawings can move intrabar and settle on close
Inputs with guidance
Setup
• Source: price series to smooth
Logic
• Min window l_min. Typical 5 to 21. Higher increases stability, adds lag
• Max window l_max. Typical 40 to 128. Higher reduces noise, adds lag ceiling
• Length step grid_step. Typical 1 to 8. Smaller is finer and heavier
• Trend bias trend_bias. Typical 0.50 to 0.80. Higher favors trend persistence
• Residual penalty lambda_base. Typical 0.8 to 2.0. Higher downweights large residuals more
• Huber threshold huber_k. Typical 1.5 to 3.0. Higher admits more outliers
• Curvature guard curv_guard. Typical 0.3 to 1.0. Higher reduces influence when curve is tight
• Forecast blend lead_blend. 0 disables. Typical 0.10 to 0.40
• Forecast cap lead_limit. Typical 1 to 5 minticks
• Show chosen L and metrics show_debug. Diagnostics toggle
Optional: enable diagnostics to see length, direction, and energy
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while bars are open and settle on close
• Use on standard candles for analysis and combine with your own risk process
Honest limitations and failure modes
• Very quiet regimes can reduce energy contrast, length selection may hover near the bounds
• Gap heavy symbols can disrupt quadratic fit on the window edges
• Excessive forecast blend may look anticipatory; use low values and the cap
DayFlow VWAP Relay Forex Majors StrategySummary in one paragraph
DayFlow VWAP Relay is a day-trading strategy for major FX pairs on intraday timeframes, demonstrated on EURUSD 15 minutes. It waits for alignment between a daily anchored VWAP regime check, residual percentiles, and lower-timeframe micro flow before suggesting trades. The originality is the fusion of daily VWAP residual percentiles with a live micro-flow score from 1 minute data to switch between fade and breakout behavior inside the same session. Add it to a clean chart and use the markers and alerts.
Scope and intent
• Markets: Major FX pairs such as EURUSD, GBPUSD, USDJPY, AUDUSD, USDCHF, USDCAD
• Timeframes: One minute to one hour
• Default demo in this publication: EURUSD on 15 minutes
• Purpose: Reduce false starts by acting only when context, location and micro flow agree
• Limits: This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Core novelty: Residual percentiles to daily anchored VWAP decide “balanced versus expanding day”. A separate 1 minute micro-flow score confirms direction, so the same model fades extremes in balance and rides range breaks in expansion
• Failure modes addressed: Chop fakeouts and unconfirmed breakouts are filtered by the expansion gate and micro-flow threshold
• Testability: Every input is exposed. Bands, background regime color, and markers show why a suggestion appears
• Portable yardstick: Stops and targets are ATR multiples converted to ticks, which transfer across symbols
• Open source status: No reused third-party code that requires attribution
Method overview in plain language
The day is anchored with a VWAP that updates from the daily session start. Price minus VWAP is the residual. Percentiles of that residual measured over a rolling window define location extremes for the current day. A regime score compares residual volatility to price volatility. When expansion is low, the day is treated as balanced and the model fades residual extremes if 1 minute micro flow points back to VWAP. When expansion is high, the model trades breakouts outside the VWAP bands if slope and micro flow agree with the move.
Base measures
• Range basis: True Range smoothed by ATR for stops and targets, length 14
• Return basis: Not required for signals; residuals are absolute price distance to VWAP
Components
• Daily Anchor VWAP Bands. VWAP with standard-deviation bands. Slope sign is used for trend confirmation on breakouts
• Residual Percentiles. Rolling percentiles of close minus VWAP over Signal length. Identify location extremes inside the day
• Expansion Ratio. Standard deviation of residuals divided by standard deviation of price over Signal length. Classifies balanced versus expanding day
• Micro Flow. Net up minus down closes from 1 minute data across a short span, normalized to −1..+1. Confirms direction and avoids fades against pressure
• Session Window optional. Restricts trading to your configured hours to avoid thin periods
• Cooldown optional. Bars to wait after a position closes to prevent immediate re-entry
Fusion rule
Gating rather than weighting. First choose regime by Expansion Ratio versus the Expansion gate. Inside each regime all listed conditions must be true: location test plus micro-flow threshold plus session window plus cooldown. Breakouts also require VWAP slope alignment.
Signal rule
• Long suggestion on balanced day: residual at or below the lower percentile and micro flow positive above the gate while inside session and cooldown is satisfied
• Short suggestion on balanced day: residual at or above the upper percentile and micro flow negative below the gate while inside session and cooldown is satisfied
• Long suggestion on expanding day: close above the upper VWAP band, VWAP slope positive, micro flow positive, session and cooldown satisfied
• Short suggestion on expanding day: close below the lower VWAP band, VWAP slope negative, micro flow negative, session and cooldown satisfied
• Positions flip on opposite suggestions or exit by brackets
What you will see on the chart
• Markers on suggestion bars: L for long, S for short
• Exit occurs on reverse signal or when a bracket order is filled
• Reference lines: daily anchored VWAP with upper and lower bands
• Optional background: teal for balanced day, orange for expanding day
Inputs with guidance
Setup
• Signal length. Residual and regime window. Typical 40 to 100. Higher smooths, lower reacts faster
Micro Flow
• Micro TF. Lower timeframe used for micro flow, default 1 minute
• Micro span bars. Count of lower-TF bars. Typical 5 to 20
• Micro flow gate 0..1. Minimum absolute flow. Raising it demands stronger confirmation and reduces trade count
VWAP Bands
• VWAP stdev multiplier. Band width. Typical 0.8 to 1.6. Wider bands reduce breakout frequency and increase fade distance
• Expansion gate 0..3. Threshold to switch from fades to breakouts. Raising it favors fades, lowering it favors breakouts
Sessions
• Use session filter. Enable to trade only inside your window
• Trade window UTC. Default 07:00 to 17:00
Risk
• ATR length. Stop and target basis. Typical 10 to 21
• Stop ATR x. Initial stop distance in ATR multiples
• Target ATR x. Profit target distance in ATR multiples
• Cooldown bars after close. Wait bars before a new entry
• Side. Both, long only, or short only
View
• Show VWAP and bands
• Color bars by residual regime
Properties visible in this publication
• Initial capital 10000
• Base currency Default
• request.security uses lookahead off everywhere
• Strategy: Percent of equity with value 3. Pyramiding 0. Commission cash per order 0.0001 USD. Slippage 3 ticks. Process orders on close ON. Bar magnifier ON. Recalculate after order is filled OFF. Calc on every tick OFF. Using standard OHLC fills ON.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Fills and slippage vary by venue. Shapes can move while a bar forms and settle on close. Strategies must run on standard candles for signals and orders.
Honest limitations and failure modes
High impact news, session opens, and thin liquidity can invalidate assumptions. Very quiet days can reduce contrast between residuals and price volatility. Session windows use the chart exchange time. If both stop and target are touched within a single bar, TradingView’s standard OHLC price-movement model decides the outcome.
Expect different behavior on illiquid pairs or during holidays. The model is sensitive to session definitions and feed time. Past results never guarantee future outcomes.
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.
