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
Tradingview
Quantum Flow [JOAT]Quantum Flow Nexus - Advanced Multi-Dimensional Flow Analysis
Overview
Quantum Flow Nexus is an open-source overlay indicator that combines custom EMA-based flow calculations with order flow analysis, multi-timeframe correlation, and liquidity zone detection. It provides traders with a structured framework for analyzing market momentum and identifying potential entry points based on multiple confirming factors.
What This Indicator Does
The indicator calculates several analytical components:
Quantum Flow Oscillator - A custom oscillator built from multiple EMA layers at different depths
Flow Momentum - Rate of change of the flow oscillator
Order Flow Delta - Buy vs sell volume pressure estimation
Smart Money Index - Volume-weighted directional bias metric
Multi-Timeframe Entanglement - Price correlation across 15m and 60m timeframes
Liquidity Zones - Historical swing high/low levels with volume significance
Wave Function State - Momentum-based decisiveness detection
How It Works
The core quantum oscillator uses a custom EMA calculation with depth layering:
quantumOscillator(series float src, simple int len, simple int depth) =>
float osc = 0.0
for i = 1 to depth
int fastLen = len / i
int slowLen = len * i
float emaFast = quantumEMA(src, fastLen)
float emaSlow = quantumEMA(src, slowLen)
osc += (emaFast - emaSlow) / depth
osc
This creates a multi-layered view of momentum by comparing EMAs at progressively different speeds.
Signal Generation
Basic signals occur when:
Bullish: Flow crosses above lower band + positive momentum + positive order flow delta
Bearish: Flow crosses below upper band + negative momentum + negative order flow delta
Strong signals require additional confirmation:
Smart Money Index above/below threshold (50/-50)
Entanglement score above 50%
Wave function in collapsed state (decisive momentum)
Confluence Score Calculation
The indicator combines multiple factors into a single confluence percentage:
float confluenceScore = (flowStrength * 20 + entanglementScore * 0.3 + math.abs(orderFlowDelta) * 0.5) / 3
Dashboard Panel (Top-Right)
Flow Strength - Distance from center line normalized by standard deviation
Momentum - Current rate of change of flow
Trend - BULLISH/BEARISH/NEUTRAL based on flow vs EMA
Confluence Score - Combined factor percentage
Order Flow Delta - Buy/sell pressure percentage
Entanglement - Multi-timeframe correlation score
Wave State - COLLAPSED or SUPERPOSITION
Signal - Current actionable status
Visual Elements
Flow Lines - Center flow line with upper/lower bands
Quantum Zones - Filled areas between bands showing bullish/bearish zones
3D Quantum Field - Five oscillating layers creating depth visualization
Order Flow Blocks - Boxes highlighting significant order flow imbalances
Liquidity Heatmap - Dashed lines at significant historical levels
Signal Markers - Triangles for basic signals, labels for strong signals
Input Parameters
Flow Period (default: 21) - Base period for flow calculations
Quantum Depth (default: 3) - Number of EMA layers
Sensitivity (default: 1.5) - Band width multiplier
Liquidity Max Levels (default: 8) - Maximum liquidity zones displayed
Liquidity Min Strength Ratio (default: 0.10) - Minimum volume significance
Suggested Use Cases
Identify momentum direction using flow oscillator position
Confirm entries with order flow and smart money readings
Use liquidity zones as potential support/resistance areas
Wait for strong signals with multiple factor confirmation
Timeframe Recommendations
Effective on 15m to Daily charts. Lower timeframes may produce more signals with higher noise levels.
Limitations
Order flow is estimated from candle structure, not actual order book data
Multi-timeframe requests add processing time
Liquidity zones are based on historical pivots and may not reflect current market structure
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.
- 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
Volatility Squeeze Pro [JOAT]
Volatility Squeeze Pro — Advanced Volatility Compression Analysis System
This indicator addresses a specific analytical challenge in volatility analysis: how to identify periods when different volatility measurements show compression relationships that may indicate potential energy buildup in the market. It combines two distinct volatility calculation methods—standard deviation-based bands and ATR-based channels—with a momentum oscillator to provide comprehensive volatility state analysis.
Why This Combination Provides Unique Analytical Value
Traditional volatility indicators typically focus on single measurements, but markets exhibit different types of volatility that require different analytical approaches:
1. **Closing Price Volatility** (Standard Deviation): Measures how much closing prices deviate from their average
2. **Trading Range Volatility** (ATR): Measures the actual high-to-low trading ranges
3. **Directional Momentum**: Measures where price sits within its recent range
The problem with using these individually:
- Standard deviation alone doesn't account for intraday volatility
- ATR alone doesn't consider closing price clustering
- Momentum alone doesn't provide volatility context
- No single measurement captures the complete volatility picture
This indicator's originality lies in creating a comprehensive volatility analysis system that:
**Identifies Volatility Compression**: When closing price volatility contracts inside trading range volatility, it suggests potential energy buildup
**Provides Momentum Context**: Shows directional bias during compression periods
**Offers Multi-Dimensional Analysis**: Combines three different analytical approaches into one coherent system
**Delivers Real-Time Assessment**: Continuously monitors the relationship between different volatility types
Technical Innovation and Originality
While individual components (Bollinger Bands, Keltner Channels, Linear Regression) are standard, the innovation lies in:
1. **Volatility Relationship Detection**: The mathematical comparison between standard deviation bands and ATR channels creates a unique compression identification system
2. **Integrated Momentum Analysis**: Linear regression-based momentum calculation provides directional context specifically during volatility compression periods
3. **Multi-State Visualization**: The indicator provides clear visual encoding of different volatility states (compressed vs. normal) with momentum direction
4. **Adaptive Threshold System**: The squeeze detection automatically adapts to different instruments and timeframes without manual calibration
How the Components Work Together Analytically
The three components create a comprehensive volatility analysis framework:
**Standard Deviation Component**: Measures closing price dispersion around the mean
float bbBasis = ta.sma(close, bbLength)
float bbDev = bbMult * ta.stdev(close, bbLength)
float bbUpper = bbBasis + bbDev
float bbLower = bbBasis - bbDev
**ATR Channel Component**: Measures actual trading range volatility
float kcBasis = ta.ema(close, kcLength)
float kcRange = ta.atr(atrLength)
float kcUpper = kcBasis + kcRange * kcMult
float kcLower = kcBasis - kcRange * kcMult
**Squeeze Detection Logic**: Identifies when closing price volatility compresses within trading range volatility
bool squeezeOn = bbLower > kcLower and bbUpper < kcUpper
// This condition indicates closing prices are clustering more tightly
// than the typical trading range would suggest
**Momentum Context Component**: Provides directional bias during compression
float highestHigh = ta.highest(high, momLength)
float lowestLow = ta.lowest(low, momLength)
float momentum = ta.linreg(close - math.avg(highestHigh, lowestLow), momLength, 0)
float momSmooth = ta.sma(momentum, smoothLength)
The analytical relationship creates a system where:
- Squeeze detection identifies WHEN volatility compression occurs
- Momentum analysis shows WHERE price is positioned during compression
- Combined analysis provides both timing and directional context
How the Volatility Comparison Works
The indicator compares two volatility measurements:
Standard Deviation Bands
These measure how much closing prices deviate from their average. When prices cluster tightly around the average, the bands contract.
// Standard deviation bands calculation
float bbBasis = ta.sma(close, bbLength)
float bbDev = bbMult * ta.stdev(close, bbLength)
float bbUpper = bbBasis + bbDev
float bbLower = bbBasis - bbDev
ATR-Based Channels
These measure volatility using Average True Range—the typical distance between high and low prices. They respond to the actual trading range rather than closing price dispersion.
// ATR-based channels calculation
float kcBasis = ta.ema(close, kcLength)
float kcRange = ta.atr(atrLength)
float kcUpper = kcBasis + kcRange * kcMult
float kcLower = kcBasis - kcRange * kcMult
The Squeeze Condition
A "squeeze" is detected when the standard deviation bands are completely contained within the ATR channels:
// Squeeze detection
bool squeezeOn = bbLower > kcLower and bbUpper < kcUpper
This condition indicates that closing price volatility has compressed relative to the overall trading range.
The Momentum Component
The momentum oscillator measures where price sits relative to its recent high-low range, using linear regression for smoothing:
// Momentum calculation
float highestHigh = ta.highest(high, momLength)
float lowestLow = ta.lowest(low, momLength)
float momentum = ta.linreg(close - math.avg(highestHigh, lowestLow), momLength, 0)
float momSmooth = ta.sma(momentum, smoothLength)
Positive values indicate price is above the midpoint of its recent range; negative values indicate below.
Why Display Both Together
The squeeze detection shows WHEN volatility is compressed. The momentum reading shows the current directional bias of price within that compression. Together, they provide two pieces of information:
1. Is volatility currently compressed? (squeeze status)
2. Where is price leaning within the current range? (momentum)
These are observations about current conditions, not predictions about future movement.
Visual Elements
Momentum Histogram — Bars showing momentum value
- Green shades: Positive momentum (price above range midpoint)
- Red shades: Negative momentum (price below range midpoint)
- Brighter colors: Momentum increasing
- Faded colors: Momentum decreasing
Squeeze Dots — Circles on the zero line
- Red: Squeeze condition active
- Green: No squeeze condition
Release Markers — Triangle markers when squeeze condition ends
Dashboard — Current readings and status
Color Scheme
Squeeze Active — #FF5252 (red)
No Squeeze — #4CAF50 (green)
Momentum Positive — #00E676 / #81C784 (green shades)
Momentum Negative — #FF5252 / #E57373 (red shades)
Inputs
Standard Deviation Bands:
Length (default: 20)
Multiplier (default: 2.0)
ATR Channels:
Length (default: 20)
Multiplier (default: 1.5)
ATR Period (default: 10)
Momentum:
Length (default: 12)
Smoothing (default: 3)
How to Read the Display
Red dots indicate the squeeze condition is present
Green dots indicate normal volatility relationship
Histogram direction shows current momentum bias
Histogram color brightness shows whether momentum is increasing or decreasing
Alerts
Squeeze condition started
Squeeze condition ended
Squeeze ended with positive momentum
Squeeze ended with negative momentum
Extended squeeze (8+ bars)
Important Limitations and Realistic Expectations
Volatility compression detection is a mathematical relationship between calculations—it does not predict future price movements
Many compression periods do not result in significant price expansion or directional moves
Momentum direction during compression does not reliably indicate future breakout direction
This indicator analyzes current and historical volatility conditions only—it cannot predict future volatility
False signals are common—not every squeeze leads to tradeable price movement
Different parameter settings will produce different compression detection sensitivity
Market conditions, news events, and fundamental factors often override technical volatility patterns
No volatility indicator can predict the timing, direction, or magnitude of future price movements
This tool should be used as one component of comprehensive market analysis
Appropriate Use Cases
This indicator is designed for:
- Volatility state analysis and monitoring
- Educational study of volatility relationships
- Multi-dimensional volatility assessment
- Supplementary analysis alongside other technical tools
- Understanding market compression/expansion cycles
This indicator is NOT designed for:
- Standalone trading signal generation
- Guaranteed breakout prediction
- Automated trading system triggers
- Market timing precision
- Replacement of fundamental analysis
Understanding Volatility Analysis Limitations
Volatility analysis, while useful for understanding market conditions, has inherent limitations:
- Past volatility patterns do not guarantee future patterns
- Compression periods can extend much longer than expected
- Expansion periods may be brief and insufficient for trading
- External factors (news, fundamentals) often override technical patterns
- Different markets and timeframes exhibit different volatility characteristics
— Made with passion by officialjackofalltrades
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
Smart Money Fluid [JOAT]
Smart Money Fluid — Accumulation and Distribution Flow Analysis
Smart Money Fluid tracks institutional-style accumulation and distribution patterns using a sophisticated combination of Money Flow Index, Chaikin Money Flow, and VWAP-relative price analysis. It aims to reveal whether larger participants may be accumulating (buying) or distributing (selling)—information that can precede significant price moves.
What Makes This Indicator Unique
Unlike single money flow indicators, Smart Money Fluid:
Combines three different money flow methodologies into one composite signal
Detects divergences between price and money flow automatically
Identifies high-volume conditions that add conviction to signals
Provides both the composite signal and individual component values
Features a momentum histogram showing flow acceleration
What This Indicator Does
Combines multiple money flow indicators into a composite signal (0-100 scale)
Identifies accumulation zones (potential institutional buying) and distribution zones (potential selling)
Detects divergences between price and money flow
Highlights high-volume conditions for stronger signals
Tracks momentum direction within the flow
Provides comprehensive dashboard with all component values
Composite Calculation Explained
The Smart Money Flow composite combines three proven money flow methodologies:
// Component 1: Money Flow Index (MFI) - 40% weight
// Measures buying/selling pressure using price and volume
float mfi = 100 - (100 / (1 + mfRatio))
// Component 2: Chaikin Money Flow (CMF) - 30% weight
// Measures accumulation/distribution based on close position within range
float cmf = sum(mfVolume, length) / sum(volume, length) * 100
// Component 3: VWAP Price Strength - 30% weight
// Measures price position relative to volume-weighted average price
float priceVsVWAP = (close - vwap) / vwap * 100
// Final Composite (scaled to 0-100)
float rawSMF = (mfi * 0.4 + (cmf + 50) * 0.3 + (50 + priceVsVWAP * 5) * 0.3)
float smf = ta.ema(rawSMF, smoothLength)
State Classification
Accumulating (Green Zone) — SMF above accumulation threshold (default: 60). Suggests institutional buying may be occurring.
Distributing (Red Zone) — SMF below distribution threshold (default: 40). Suggests institutional selling may be occurring.
Neutral (Gray Zone) — SMF between thresholds. No clear accumulation or distribution detected.
Divergence Detection
The indicator automatically detects divergences using pivot analysis:
Bullish Divergence — Price makes a lower low while SMF makes a higher low. This suggests selling pressure is weakening despite lower prices—potential reversal signal.
Bearish Divergence — Price makes a higher high while SMF makes a lower high. This suggests buying pressure is weakening despite higher prices—potential reversal signal.
Divergences are marked with "DIV" labels on the chart.
Visual Features
SMF Line with Glow — Main composite line with gradient coloring and glow effect
Signal Line — Slower EMA of SMF for crossover signals
Flow Momentum Histogram — Shows the difference between SMF and signal line with four-color coding:
- Bright green: Positive and accelerating
- Faded green: Positive but decelerating
- Bright red: Negative and accelerating
- Faded red: Negative but decelerating
Zone Backgrounds — Green tint in accumulation zone, red tint in distribution zone
Reference Lines — Dashed lines at accumulation/distribution thresholds, dotted line at 50
Strong Signal Markers — Triangles appear when accumulation/distribution occurs with high volume
Divergence Labels — "DIV" markers when divergences are detected
Color Scheme
Accumulation Color — Default: #00E676 (bright green)
Distribution Color — Default: #FF5252 (red)
Neutral Color — Default: #9E9E9E (gray)
Gradient Coloring — SMF line transitions smoothly between colors based on value
Dashboard Information
The on-chart table (top-right corner) displays:
Current SMF value with state coloring
State classification (ACCUMULATING, DISTRIBUTING, or NEUTRAL)
Flow momentum direction (Up/Down with magnitude)
MFI component value
CMF component value with directional coloring
Volume status (High or Normal)
Active divergence detection (Bullish, Bearish, or None)
Inputs Overview
Calculation Settings:
Money Flow Length — Period for flow calculations (default: 14, range: 5-50)
Smoothing Length — EMA smoothing period (default: 5, range: 1-20)
Divergence Lookback — Bars for pivot detection in divergence analysis (default: 5, range: 2-20)
Sensitivity:
Accumulation Threshold — Level above which accumulation is detected (default: 60, range: 50-90)
Distribution Threshold — Level below which distribution is detected (default: 40, range: 10-50)
High Volume Multiplier — Multiple of average volume for "high volume" classification (default: 1.5x, range: 1.0-3.0)
Visual Settings:
Accumulation/Distribution/Neutral Colors — Customizable color scheme
Show Flow Histogram — Toggle momentum histogram
Show Divergences — Toggle divergence detection and labels
Show Dashboard — Toggle the information table
Show Zone Background — Toggle colored backgrounds in accumulation/distribution zones
Alerts:
Await Bar Confirmation — Wait for bar close before triggering (recommended)
How to Use It
For Trend Confirmation:
Accumulation during uptrends confirms buying pressure
Distribution during downtrends confirms selling pressure
Divergence between price trend and SMF warns of potential reversal
For Reversal Detection:
Bullish divergence at price lows suggests potential bottom
Bearish divergence at price highs suggests potential top
Strong signals (triangles) with high volume add conviction
For Entry Timing:
Enter longs when SMF crosses into accumulation zone
Enter shorts when SMF crosses into distribution zone
Wait for high volume confirmation for stronger signals
Use divergences as early warning for position management
Alerts Available
SMF Accumulation Started — SMF entered accumulation zone
SMF Distribution Started — SMF entered distribution zone
SMF Strong Accumulation — Accumulation with high volume
SMF Strong Distribution — Distribution with high volume
SMF Bullish Divergence — Bullish divergence detected
SMF Bearish Divergence — Bearish divergence detected
Best Practices
High volume during accumulation/distribution adds significant conviction
Divergences are early warnings—don't trade them alone
Use in conjunction with price action and support/resistance
Works best on liquid markets with reliable volume data
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
Iridescent Liquidity Prism [JOAT]Iridescent Liquidity Prism | Peer Momentum HUD
A multi-layered order-flow indicator that combines microstructure analysis, smart-money footprint detection, and intermarket momentum signals. The script uses dynamic color-shifting themes to visualize liquidity patterns, structure, and peer momentum data directly on the chart.
There is so much to choose from inside the settings, if you think it's a mess on the chart it's because you have to personally customize it based on your needs...
Core Functionality
The indicator calculates and displays several analytical layers simultaneously:
Order-Flow Imbalance (OFI): Calculates buy vs. sell volume pressure using volume-weighted price distribution within each bar. Uses an EMA filter (default: 55 periods) to smooth the signal. Values are normalized using standard deviation to identify significant imbalances.
Smart Money Footprints: Detects accumulation and distribution zones by comparing volume rate of change (ROC) against price ROC. When volume ROC exceeds a threshold (default: 65%) and price ROC is positive, accumulation is detected. When volume ROC is high but price ROC is negative, distribution is detected.
Fractal Structure Mapping: Identifies pivot highs and lows using a fractal detection algorithm (default: 5-bar period). Maintains a rolling window of recent structure points (default: 4 levels) and draws connecting lines to show trend structure.
Fair Value Gap (FVG) Detection: Automatically detects price gaps where three consecutive candles create an imbalance. Bullish FVGs occur when the current low exceeds the high two bars ago. Bearish FVGs occur when the current high is below the low two bars ago. Gaps persist for a configurable duration (default: 320 bars) and fade when price fills the gap.
Liquidity Void Detection: Identifies candles where the high-low range exceeds an ATR threshold (default: 1.7x ATR) while volume is below average (default: 65% of 20-bar average). These conditions suggest areas where liquidity may be thin.
Price/Volume Divergence: Uses linear regression to detect when price trend direction disagrees with volume trend direction. A divergence alert appears when price is trending up while volume is trending down, or vice versa.
Peer Momentum Heatmap (PMH): Calculates composite momentum scores for up to 6 symbols across 4 timeframes. Each score combines RSI (default: 14 periods) and StochRSI (default: 14 periods, 3-bar smooth) to create a momentum composite between -1 and +1. The highest absolute momentum score across all combinations is displayed in the HUD.
Custom settings using Fractal Pivots, Skeleton Structure, Pulse Liquidity Voids, Bottom Colorful HeatMaps, and Iridescent Field.
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Visual Components
Spectrum Aura Glow: ATR-weighted bands (default: 0.25x ATR) that expand and contract around price action, indicating volatility conditions. The thickness adapts to market volatility.
Chromatic Flow Trail: A blended line combining EMA and WMA of price (default: 8-period EMA blended with WMA at 65% ratio). The trail uses gradient colors that shift based on a phase oscillator, creating an iridescent effect.
Volume Heat Projection: Creates horizontal volume profile bands at price levels (default: 14 levels). Scans recent bars (default: 150 bars) to calculate volume concentration. Each level is colored based on its volume density relative to the maximum volume level.
Structure Skeleton: Dashed lines connecting fractal pivot points. Uses two layers: a primary line (2-3px width) and an optional glow overlay (4-5px width) for enhanced visibility.
Fractal Markers: Diamond shapes placed at pivot high and low points. Color-coded: primary color for highs, secondary color for lows.
Iridescent Color Themes: Five color themes available: Iridescent (default), Pearlescent, Prismatic, ColorShift, and Metallic. Colors shift dynamically using a phase oscillator that cycles through the color spectrum based on bar index and a speed multiplier (default: 0.35).
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HUD Console Metrics
The right-side HUD displays seven key metrics:
Flow: Shows OFI status: ▲ FLOW BUY when normalized OFI exceeds imbalance threshold (default: 2.2), ▼ FLOW SELL when below -2.2, or ◆ FLOW BAL when balanced.
Struct: Structure trend bias: ▲ STRUCT BULL when microtrend > 2, ▼ STRUCT BEAR when < -2, or ◆ STRUCT RANGE when neutral.
Smart$: Institutional activity: ◈ ACCUM when smart money index = 1, ◈ DISTRIB when = -1, or ○ IDLE when inactive.
Liquid: Liquidity state: ⚡ VOID when a liquidity void is detected, or ● NORMAL otherwise.
Diverg: Divergence status: ⚠ ALERT when price/volume divergence detected, or ✓ CLEAR when aligned.
PMH: Peer Momentum Heatmap status: Shows dominant timeframe and momentum score. Displays 🪩 for bull surge (above 0.55 threshold) or 🧨 for bear surge (below -0.55).
FVG: Fair Value Gap status: Shows active gap count or CLEAR when no gaps exist. Displays GAP LONG when bullish gap detected, GAP SHORT when bearish gap detected.
Pearlscent Color with Volume Heatmap.
Parameters and Settings
Microstructure Engine:
Analysis Depth: 20-250 bars (default: 55) - Controls OFI smoothing period
Liquidity Threshold ATR: 1.0-4.0 (default: 1.7) - Multiplier for void detection
Imbalance Ratio: 1.5-6.0 (default: 2.2) - Standard deviations for OFI significance
Smart Money Layer:
Smart Money Window: 10-150 bars (default: 24) - Period for ROC calculations
Accumulation Threshold: 40-95% (default: 65%) - Volume ROC threshold
Structural Mapping:
Fractal Pivot Period: 3-15 bars (default: 5) - Period for pivot detection
Structure Memory: 2-8 levels (default: 4) - Number of structure points to track
Volume Heat Projection:
Heat Map Lookback: 60-400 bars (default: 150) - Bars to analyze for volume profile
Heat Map Levels: 5-30 levels (default: 14) - Number of price level bands
Heat Map Opacity: 40-100% (default: 92%) - Transparency of heat map boxes
Heat Map Width Limit: 6-80 bars (default: 26) - Maximum width of heat map boxes
Heat Map Visibility Threshold: 0.0-0.5 (default: 0.08) - Minimum density to display
Iridescent Enhancements:
Visual Theme: Iridescent, Pearlescent, Prismatic, ColorShift, or Metallic
Color Shift Speed: 0.05-1.00 (default: 0.35) - Speed of color phase oscillation
Aura Thickness (ATR): 0.05-1.0 (default: 0.25) - Multiplier for aura band width
Chromatic Trail Length: 2-50 bars (default: 8) - Period for trail calculation
Trail Blend Ratio: 0.1-0.95 (default: 0.65) - EMA/WMA blend percentage
FVG Persistence: 50-600 bars (default: 320) - Bars to keep FVG boxes active
Max Active FVG Boxes: 10-200 (default: 40) - Maximum boxes on chart
FVG Base Opacity: 20-95% (default: 80%) - Transparency of FVG boxes
Peer Momentum Heatmap:
Peer Symbols: Comma-separated list of up to 6 symbols (e.g., "BTCUSD,ETHUSD")
Peer Timeframes: Comma-separated list of up to 4 timeframes (default: "60,240,D")
PMH RSI Length: 5-50 periods (default: 14)
PMH StochRSI Length: 5-50 periods (default: 14)
PMH StochRSI Smooth: 1-10 periods (default: 3)
Super Momentum Threshold: 0.2-0.95 (default: 0.55) - Threshold for surge detection
Clarity & Readability:
Liquidity Void Opacity: 5-90% (default: 30%)
Smart Money Footprint Opacity: 5-90% (default: 35%)
HUD Background Opacity: 40-95% (default: 70%)
Iridescent Field:
Field Opacity: 20-100% (default: 86%) - Background color intensity
Field Smooth Length: 10-200 bars (default: 34) - Smoothing for background gradient
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Alerts
The indicator provides seven alert conditions:
Liquidity Void Detected - Triggers when void conditions are met
Strong Order Flow - Triggers when normalized OFI exceeds imbalance ratio
Smart Money Activity - Triggers when accumulation or distribution detected
Price/Volume Divergence - Triggers when divergence conditions occur
Structure Shift - Triggers when structure polarity changes significantly
PMH Bull Surge - Triggers when PMH exceeds positive threshold (if enabled)
PMH Bear Surge - Triggers when PMH exceeds negative threshold (if enabled)
Bull/Bear Prismatic FVG - Triggers when new FVG is detected (if FVG display enabled)
---
Usage Considerations
Performance may vary on lower timeframes due to the volume heat map calculations scanning multiple bars. Consider reducing heat map lookback or levels if experiencing slowdowns.
The PMH feature requires data requests to other symbols/timeframes, which may impact performance. Limit the number of peer symbols and timeframes for optimal performance.
FVG boxes automatically expire after the persistence period to prevent chart clutter. The maximum box limit (default: 40) prevents excessive memory usage.
Color themes affect all visual elements. Choose a theme that provides good contrast with your chart background.
The indicator is designed for overlay display. All visual elements are positioned relative to price action.
Structure lines are drawn dynamically as new pivots form. On fast-moving markets, structure may update frequently.
Volume calculations assume typical volume data availability. Symbols without volume may show incomplete data for volume-dependent features.
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Technical Notes
Built on Pine Script v6 with dynamic request capability for PMH functionality.
Uses exponential moving averages (EMA) and weighted moving averages (WMA) for trail calculations to balance responsiveness and smoothness.
Volume profile calculation uses price level buckets. Higher levels provide finer granularity but require more computation.
Iridescent color engine uses a phase oscillator with sine wave calculations for smooth color transitions.
Box management includes automatic cleanup of expired boxes to maintain performance.
All visual elements use color gradients and transparency for smooth blending with price action.
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Customization Examples
Intraday Scalping Setup:
Analysis Depth: 30 bars
Heat Map Lookback: 100 bars
FVG Persistence: 150 bars
PMH Window: 15 bars
Fast color shift speed: 0.5+
Macro Structure Tracking:
Analysis Depth: 100+ bars
Heat Map Lookback: 300+ bars
FVG Persistence: 500+ bars
Structure Memory: 6-8 levels
Slower color shift speed: 0.2
---
Limitations
Volume heat map calculations may be computationally intensive on lower timeframes with high lookback values.
PMH requires valid symbol names and accessible timeframes. Invalid symbols or timeframes will return no data.
FVG detection requires at least 3 bars of history. Early bars may not show FVG boxes.
Structure lines connect points but do not predict future structure. They reflect historical pivot relationships.
Color themes are aesthetic choices and do not affect calculation logic.
The indicator does not provide trading signals. All visual elements are analytical tools that require interpretation in context of market conditions.
Open Source
This indicator is open source and available for modification and distribution. The code is published with Pine Script v6 compliance. Users are free to customize parameters, modify calculations, and adapt the visual elements to their trading needs.
For questions, suggestions, or anything please talk to me in private messages or comments below!
Would love to help!
- officialjackofalltrades
SNP420/TRCS_MASTERMicro Body Candle Highlighter is a visual tool for TradingView that continuously scans the active timeframe and highlights all candles with an extremely small body.
For every bar (including the currently forming one), the indicator compares the absolute distance between Open and Close to a user-defined threshold in ticks (default: 1 tick, based on syminfo.mintick).
If the candle’s body size is less than or equal to this threshold, the indicator draws a red frame around the candle – either around the body only or the full high-to-low range, depending on user settings.
Optionally, the indicator can also trigger alerts whenever such a “micro body” candle is detected, allowing traders to react immediately to potential indecision, pauses, or micro-reversals in price action.
author: SNP_420
project: FNXS
ps: Piece and love
Friday & Monday HighlighterFriday & Monday Institutional Range Marker — Know Where Big Firms Set the Trap!
🧠 Description
This indicator automatically highlights Friday and Monday sessions on your chart — days when institutional players and algorithmic firms (like Citadel, Jane Street, or Tower Research) quietly shape the upcoming week’s price structure.
🔍 Why Friday & Monday matter
Friday : Large institutions often book profits or hedge into the weekend. Their final-hour moves reveal the next week’s bias.
Monday : Big players rebuild positions, absorbing liquidity left behind by retail traders.
Together, these two days define the range traps and breakout zones that often control price action until midweek.
> In short, the Friday–Monday high and low often act as invisible walls — guiding scalpers, option sellers, and swing traders alike.
🧩 What this tool does
✅ Highlights Friday (red) and Monday (green) sessions
✅ Adds optional day labels above bars
✅ Works across all timeframes (best on 15min to 1hr charts)
✅ Helps you visually identify where institutions likely built their positions
Use it to quickly spot:
* Range boundaries that trap traders
* Gap zones likely to get filled
* High–low sweeps before reversals
⚙️ Recommended Use
1. Mark Friday’s high–low → Watch for liquidity sweeps on Monday.
2. When Monday holds above Friday’s high , breakout continuation is likely.
3. When Monday fails below Friday’s low , expect a reversal or trap.
4. Combine this with OI shifts, IV crush, and FII–DII flow data for confirmation.
⚠️ Disclaimer
This indicator is for **educational and analytical purposes only**.
It does **not constitute financial advice** or a trading signal.
Markets are dynamic — always perform your own research before trading or investing.
SMA Vertical OffsetThis Indicator allow you to adjust the SMA offset vertically instead of horizontally
TCP | Market Session | Session Analyzer📌 TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
🔰 Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessions—and knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
🕒 Core Features
• Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
• Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
• Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
• Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
• Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
• Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
• Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
⚙️ Settings Panel
Customize everything to fit your trading style and schedule:
• Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
→ For example, enter Asia Start: 0, Asia End: 480 for 00:00–08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
• Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
• Timezone Selection:
Choose between using UTC or your chart’s local timezone for session calculations.
• Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
📊 Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
• Asia: Green Box
• Europe: Orange Box
• US: Blue Box
💡 Why Use This Tool?
• Perfect Timing: Don’t get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
• Pattern Recognition: Study how price behaves session-to-session to build better strategies.
• Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
• Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
🔍 Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows “Asia Session End: Trend Up”)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous high—label confirmed
Now you know who’s active, what the market just did, and what’s about to start—all in one glance.
✅ Why Traders Trust It
• Visual & Intuitive: Fully chart-based, no clutter, no guessing
• Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
• Non-Repainting: All labels and boxes stay as printed—no tricks
• Reliable: Tested across multiple exchanges, pairs, and timeframes
🧩 Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. It’s coded in Pine Script v6 for full compatibility with TradingView’s latest capabilities.
🔗 Resources
• Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
• More Tools: Explore our full library of indicators on
Order Blocks v2Order Blocks v2 – Smart OB Detection with Time & FVG Filters
Order Blocks v2 is an advanced tool designed to identify potential institutional footprints in the market by dynamically plotting bullish and bearish order blocks.
This indicator refines classic OB logic by combining:
Fractal-based break conditions
Time-level filtering (Power of 3)
Optional Fair Value Gap (FVG) confirmation
Real-time plotting and auto-invalidation
Perfect for traders using ICT, Smart Money, or algorithmic timing models like Hopplipka.
🧠 What the indicator does
Detects order blocks after break of bullish/bearish fractals
Supports 3-bar or 5-bar fractal structures
Allows OB detection based on close breaks or high/low breaks
Optionally confirms OBs only if followed by a Fair Value Gap within N candles
Filters OBs based on specific time levels (3, 7, 11, 14) — core anchors in many algorithmic models
Automatically deletes invalidated OBs once price closes through the zone
⚙️ How it works
The indicator:
Tracks local fractal highs/lows
Once a fractal is broken by price, it backtracks to identify the best OB candle (highest bullish or lowest bearish)
Validates the level by checking:
OB type logic (close or HL break)
Time stamp match with algorithmic time anchors (e.g. 3, 7, 11, 14 – known from the Power of 3 concept)
Optional FVG confirmation after OB
Plots OB zones as lines (body or wick-based) and removes them if invalidated by a candle close
This ensures traders see only valid, active levels — removing noise from broken or out-of-context zones.
🔧 Customization
Choose 3-bar or 5-bar fractals
OB detection type: close break or HL break
Enable/disable OBs only on times 3, 7, 11, 14 (Hopplipka style)
Optional: require nearby FVG for validation
Line style: solid, dashed, or dotted
Adjust OB length, width, color, and use body or wick for OB height
🚀 How to use it
Add the script to your chart
Choose your preferred OB detection mode and filters
Use plotted OB zones to:
Anticipate price rejections and reversals
Validate Smart Money or ICT-based entry zones
Align setups with algorithmic time sequences (3, 7, 11, 14)
Filter out invalid OBs automatically, keeping your chart clean
The tool is useful on any timeframe but performs best when combined with a liquidity-based or time-anchored trading model.
💡 What makes it original
Combines fractal logic with OB confirmation and time anchors
Implements time-based filtering inspired by Hopplipka’s interpretation of the "Power of 3"
Allows OB validation via optional FVG follow-up — rarely available in public indicators
Auto-cleans invalidated OBs to reduce clutter
Designed to reflect market structure logic used by institutions and algorithms
💬 Why it’s worth using
Order Blocks v2 simplifies one of the most nuanced parts of SMC: identifying clean and high-probability OBs.
It removes subjectivity, adds clear timing logic, and integrates optional confluence tools — like FVG.
For traders serious about algorithmic-level structure and clean setups, this tool delivers both logic and clarity.
⚠️ Important
This indicator:
Is not a signal generator or financial advice tool
Is intended for experienced traders using OB/SMC/time-based logic
Does not predict market direction — it provides visual structural levels only
Cumulative Intraday Volume with Long/Short LabelsThis indicator calculates a running total of volume for each trading day, then shows on the price chart when that total crosses levels you choose. Every day at 6:00 PM Eastern Time, the total goes back to zero so it always reflects only the current day’s activity. From that moment on, each time a new candle appears the indicator looks at whether the candle closed higher than it opened or lower. If it closed higher, the candle’s volume is added to the running total; if it closed lower, the same volume amount is subtracted. As a result, the total becomes positive when buyers have dominated so far today and negative when sellers have dominated.
Because futures markets close at 6 PM ET, the running total resets exactly then, mirroring the way most intraday traders think in terms of a single session. Throughout the day, you will see this running total move up or down according to whether more volume is happening on green or red candles. Once the total goes above a number you specify (for example, one hundred thousand contracts), the indicator will place a small “Long” label at that candle on the main price chart to let you know buying pressure has reached that level. Similarly, once the total goes below a negative number you choose (for example, minus one hundred thousand), a “Short” label will appear at that candle to signal that selling pressure has reached your chosen threshold. You can set these threshold numbers to whatever makes sense for your trading style or the market you follow.
Because raw volume alone never turns negative, this design uses candle direction as a sign. Green candles (where the close is higher than the open) add volume, and red candles (where the close is lower than the open) subtract volume. Summing those signed volume values tells you in a single number whether buying or selling has been stronger so far today. That number resets every evening, so it does not carry over any buying or selling from previous sessions.
Once you have this indicator on your chart, you simply watch the “summed volume” line as it moves throughout the day. If it climbs past your long threshold, you know buyers are firmly in control and a long entry might make sense. If it falls past your short threshold, you know sellers are firmly in control and a short entry might make sense. In quieter markets or times of low volume, you might use a smaller threshold so that even modest buying or selling pressure will trigger a label. During very active periods, a larger threshold will prevent too many signals when volume spikes frequently.
This approach is straightforward but can be surprisingly powerful. It does not rely on complex formulas or hidden statistical measures. Instead, it simply adds and subtracts daily volume based on candle color, then alerts you when that total reaches levels you care about. Over several years of historical testing, this formula has shown an ability to highlight moments when intraday sentiment shifts decisively from buyers to sellers or vice versa. Because the indicator resets every day at 6 PM, it always reflects only today’s sentiment and remains easy to interpret without carrying over past data. You can use it on any intraday timeframe, but it works especially well on five-minute or fifteen-minute charts for futures contracts.
If you want a clear gauge of whether buyers or sellers are dominating in real time, and you prefer a rule-based method rather than a complex model, this indicator gives you exactly that. It shows net buying or selling pressure at a glance, resets each session like most intraday traders do, and marks the moments when that pressure crosses the levels you decide are important. By combining a daily reset with signed volume, you get a single number that tells you precisely what the crowd is doing at any given moment, without any of the guesswork or hidden calculations that more complicated indicators often carry.
$ADD LevelsThis Pine Script is designed to track and visualize the NYSE Advance-Decline Line (ADD). The Advance-Decline Line is a popular market breadth indicator, showing the difference between advancing and declining stocks on the NYSE. It’s often used to gauge overall market sentiment and strength.
1. //@version=5
This line tells TradingView to use Pine Script v5, the latest and most powerful version of Pine.
2. indicator(" USI:ADD Levels", overlay=false)
• This creates a new indicator called ” USI:ADD Levels”.
• overlay=false means it will appear in a separate pane, not on the main price chart.
3. add = request.security(...)
This fetches real-time data from the symbol USI:ADD (Advance-Decline Line) using a 1-minute timeframe. You can change the timeframe if needed.
add_symbol = input.symbol(" USI:ADD ", "Market Breadth Symbol")
add = request.security(add_symbol, "1", close)
4. Key Thresholds
These define the market sentiment zones:
Zone. Value. Meaning
Overbought +1500 Extremely bullish
Bullish +1000 Generally bullish trend
Neutral ±500 Choppy, unclear market
Bearish -1000 Generally bearish trend
Oversold -1500 Extremely bearish
5. Plot the ADD Line hline(...)
Draws static lines at +1500, +1000, +500, -500, -1000, -1500 for reference so you can visually assess where ADD stands.
6. Horizontal Threshold Lines bgcolor(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
7. Background Highlights alertcondition(...)
• Green background if ADD > +1500 → extremely bullish.
• Red background if ADD < -1500 → extremely bearish.
8. Alert Conditions. alertcondition(...)
Lets you create automatic alerts for:
• USI:ADD being very high or low.
• Crosses above +1000 (bullish trigger).
• Crosses below -1000 (bearish trigger).
You can use these to trigger trades or monitor sentiment shifts.
Summary: When to Use It
• Use this script in a market breadth dashboard.
• Combine it with price action and volume analysis.
• Monitor for ADD crosses to signal potential market reversals or momentum.
TCP | Money Management indicator | Crypto Version📌 TCP | Money Management Indicator | Crypto Version
A robust, multi-target risk and capital management indicator tailored for crypto traders. Whether you're trading spot, perpetual futures, or leverage tokens, this tool empowers you with precise control over risk, reward, and position sizing—directly on your chart. Eliminate guesswork and trade with confidence.
🔰 Introduction: Master Your Capital, Master Your Trades
Poor money management is the number one reason traders lose their accounts, even with solid strategies. The TCP Money Management Indicator, built by Trade City Pro (TCP), solves this problem by providing a structured, rule-based approach to capital allocation.
Want to dive deeper into the concept of money management? Check out our comprehensive tutorial on TradingView, " TradeCityPro Academy: Money Management ", to understand the principles that power this indicator and transform your trading mindset.
This indicator equips you to:
• Calculate optimal position sizes based on your capital, risk percentage, and leverage
• Set up to 5 customizable take-profit targets with partial close percentages
• Access real-time metrics like Risk-to-Reward (R/R), USD profit, and margin usage
• Trade with discipline, avoiding emotional or inconsistent decisions
💸 Money Management Formula
The indicator uses a professional capital allocation model:
Position Size = (Capital × Risk %) ÷ (Stop Loss % × Leverage)
From this, it calculates:
• Total risk amount in USD
• Optimal position size for your trade
• Margin required for each take-profit target
• Adjusted R/R for each target, accounting for partial position closures
🛠 How to Use
Enter Trade Parameters: Input your capital, risk %, leverage, entry price, and stop-loss price.
Set Take-Profit Targets: Enable 1 to 5 take-profit levels and specify the percentage of the position to close at each.
Real-Time Calculations: The indicator automatically computes:
• R/R ratio for each target
• Profit in USD for each partial close
• Margin used per target (in % and USD)
Visualize Your Trade:
• Price levels for entry, stop-loss, and take-profits are plotted on the chart.
• A dynamic info panel on the left side displays all key metrics.
🔄 Dynamic Adjustments: As each take-profit target is hit and a portion of the position is closed, the indicator recalculates the remaining position size, expected profit, R/R, and margin for subsequent targets. This ensures accuracy and reflects real-world trade behavior.
📊 Table Overview
The left-side panel provides a clear snapshot:
• Trade Setup: Capital, entry price, stop-loss, risk amount, and position size
• Per Target: Percentage closed, R/R, profit in USD, and margin used
• Summary: Total expected profit across all targets
⚙️ Settings Panel
• Total Capital ($): Your account size for the trade
• Risk per Trade (%): The percentage of capital you’re willing to risk
• Leverage: The leverage applied to the trade
• Entry/Stop-Loss Prices: Define your trade’s risk zone
• Take-Profit Targets (1–5): Set price levels and percentage to close at each
🔍 Use Case Example
Imagine you have $1,000 capital, risking 1%, using 10x leverage:
• Entry: $100 | Stop-Loss: $95
• TP1: $110 (close 50%) | TP2: $115 (close 50%)
The indicator calculates the exact position size, profit at each target, and margin allocation in real time, with all metrics displayed on the chart.
✅ Why Traders Love It
• Precision: No more manual calculations or guesswork
• Versatility: Works on all crypto pairs (BTC, ETH, altcoins, etc.)
• Flexibility: Perfect for scalping, swing trading, or futures strategies
• Universal: Compatible with all timeframes
• Transparency: Fully manual, with clear and reliable outputs
🧩 Built by Trade City Pro (TCP)
Developed by TCP, a trusted name in trading tools, used by over 150,000 traders worldwide. This indicator is coded in Pine Script v5, ensuring compatibility with TradingView’s platform.
🧾 Final Notes
• No Auto-Trading: This is a manual tool for disciplined traders
• No Repainting: All calculations are accurate and non-repainting
• Tested: Rigorously validated across major crypto pairs
• Publish-Ready: Built for seamless use on TradingView
🔗 Resources
• Money Management Tutorial: Learn the fundamentals of capital management with our detailed guide: TradeCityPro Academy: Money Management
• TradingView Profile: Explore more tools by TCP on TradingView
Volume Profile & Smart Money Explorer🔍 Volume Profile & Smart Money Explorer: Decode Institutional Footprints
Master the art of institutional trading with this sophisticated volume analysis tool. Track smart money movements, identify peak liquidity windows, and align your trades with major market participants.
🌟 Key Features:
📊 Triple-Layer Volume Analysis
• Total Volume Patterns
• Directional Volume Split (Up/Down)
• Institutional Flow Detection
• Real-time Smart Money Tracking
• Historical Pattern Recognition
⚡ Smart Money Detection
• Institutional Trade Identification
• Large Block Order Tracking
• Smart Money Concentration Periods
• Whale Activity Alerts
• Volume Threshold Analysis
📈 Advanced Profiling
• Hourly Volume Distribution
• Directional Bias Analysis
• Liquidity Heat Maps
• Volume Pattern Recognition
• Custom Threshold Settings
🎯 Strategic Applications:
Institutional Trading:
• Track Big Player Movements
• Identify Accumulation/Distribution
• Follow Smart Money Flow
• Detect Institutional Trading Windows
• Monitor Block Orders
Risk Management:
• Identify High Liquidity Windows
• Avoid Thin Market Periods
• Optimize Position Sizing
• Track Market Participation
• Monitor Volume Quality
Market Analysis:
• Volume Pattern Recognition
• Smart Money Flow Analysis
• Liquidity Window Identification
• Institutional Activity Cycles
• Market Depth Analysis
💡 Perfect For:
• Professional Traders
• Volume Profile Traders
• Institutional Traders
• Risk Managers
• Algorithmic Traders
• Smart Money Followers
• Day Traders
• Swing Traders
📊 Key Metrics:
• Normalized Volume Profiles
• Institutional Thresholds
• Directional Volume Split
• Smart Money Concentration
• Historical Patterns
• Real-time Analysis
⚡ Trading Edge:
• Trade with Institution Flow
• Identify Optimal Entry Points
• Recognize Distribution Patterns
• Follow Smart Money Positioning
• Avoid Thin Markets
• Capitalize on Peak Liquidity
🎓 Educational Value:
• Understand Market Structure
• Learn Volume Analysis
• Master Institutional Patterns
• Develop Market Intuition
• Track Smart Money Flow
🛠️ Customization:
• Adjustable Time Windows
• Flexible Volume Thresholds
• Multiple Timeframe Analysis
• Custom Alert Settings
• Visual Preference Options
Whether you're tracking institutional flows in crypto markets or following smart money in traditional markets, the Volume Profile & Smart Money Explorer provides the deep insights needed to trade alongside the biggest players.
Transform your trading from retail guesswork to institutional precision. Know exactly when and where smart money moves, and position yourself ahead of major market shifts.
#VolumeProfile #SmartMoney #InstitutionalTrading #MarketAnalysis #TradingView #VolumeAnalysis #CryptoTrading #ForexTrading #TechnicalAnalysis #Trading #PriceAction #MarketStructure #OrderFlow #Liquidity #RiskManagement #TradingStrategy #DayTrading #SwingTrading #AlgoTrading #QuantitativeTrading
Highest High, Lowest Low, Midpoint for Selected Days [kiyarash]Highest High, Lowest Low, and Midpoint for Selected Days Indicator
This custom TradingView indicator allows you to visualize the highest high, lowest low, and the midpoint (average of the highest high and lowest low) over a custom-defined period. You can choose a starting date and specify how many days ahead you want to track the highest and lowest values. This is useful for identifying key levels in a trend and potential support or resistance zones.
How to Use:
Set the Starting Date:
In the settings, input the starting date from which you want to begin tracking the price range. This will be the reference point for your analysis.
Choose the Number of Days to Track:
Specify how many days you want to analyze from the selected starting date. For example, if you want to see the highest high and lowest low over the next 3 days, enter "3" in the settings.
Visualizing the Levels:
The indicator will automatically calculate the highest price and the lowest price over the selected period and draw three lines:
Red Line: Represents the Highest High within the selected period.
Green Line: Represents the Lowest Low within the selected period.
Blue Line: Represents the Midpoint, which is the average of the Highest High and Lowest Low.
Interpretation:
Highest High is a key resistance level, indicating the highest price reached within the specified period.
Lowest Low is a key support level, showing the lowest price during the same period.
Midpoint provides a reference for the average price, often acting as a neutral level between support and resistance.
This tool can help traders to quickly assess potential market ranges, identify breakout or breakdown points, and make informed decisions based on recent price action.
How to Apply:
Add the indicator to your chart.
Adjust the settings to choose your desired starting date and the number of days you want to analyze.
Observe the drawn lines for the Highest High, Lowest Low, and Midpoint levels, and use them to assist in your trading decisions.
Multi-Timeframe Stochastic Alert [tradeviZion]# Multi-Timeframe Stochastic Alert : Complete User Guide
## 1. Introduction
### What is the Multi-Timeframe Stochastic Alert?
The Multi-Timeframe Stochastic Alert is an advanced technical analysis tool that helps traders identify potential trading opportunities by analyzing momentum across multiple timeframes. It combines the power of the stochastic oscillator with multi-timeframe analysis to provide more reliable trading signals.
### Key Features and Benefits
- Simultaneous analysis of 6 different timeframes
- Advanced alert system with customizable conditions
- Real-time visual feedback with color-coded signals
- Comprehensive data table with instant market insights
- Motivational trading messages for psychological support
- Flexible theme support for comfortable viewing
### How it Can Help Your Trading
- Identify stronger trends by confirming momentum across multiple timeframes
- Reduce false signals through multi-timeframe confirmation
- Stay informed of market changes with customizable alerts
- Make more informed decisions with comprehensive market data
- Maintain trading discipline with clear visual signals
## 2. Understanding the Display
### The Stochastic Chart
The main chart displays three key components:
1. ** K-Line (Fast) **: The primary stochastic line (default color: green)
2. ** D-Line (Slow) **: The signal line (default color: red)
3. ** Reference Lines **:
- Overbought Level (80): Upper dashed line
- Middle Line (50): Center dashed line
- Oversold Level (20): Lower dashed line
### The Information Table
The table provides a comprehensive view of stochastic readings across all timeframes. Here's what each column means:
#### Column Explanations:
1. ** Timeframe **
- Shows the time period for each row
- Example: "5" = 5 minutes, "15" = 15 minutes, etc.
2. ** K Value **
- The fast stochastic line value (0-100)
- Higher values indicate stronger upward momentum
- Lower values indicate stronger downward momentum
3. ** D Value **
- The slow stochastic line value (0-100)
- Helps confirm momentum direction
- Crossovers with K-line can signal potential trades
4. ** Status **
- Shows current momentum with symbols:
- ▲ = Increasing (bullish)
- ▼ = Decreasing (bearish)
- Color matches the trend direction
5. ** Trend **
- Shows the current market condition:
- "Overbought" (above 80)
- "Bullish" (above 50)
- "Bearish" (below 50)
- "Oversold" (below 20)
#### Row Explanations:
1. ** Title Row **
- Shows "🎯 Multi-Timeframe Stochastic"
- Indicates the indicator is active
2. ** Header Row **
- Contains column titles
- Dark blue background for easy reading
3. ** Timeframe Rows **
- Six rows showing different timeframe analyses
- Each row updates independently
- Color-coded for easy trend identification
4. **Message Row**
- Shows rotating motivational messages
- Updates every 5 bars
- Helps maintain trading discipline
### Visual Indicators and Colors
- ** Green Background **: Indicates bullish conditions
- ** Red Background **: Indicates bearish conditions
- ** Color Intensity **: Shows strength of the signal
- ** Background Highlights **: Appear when alert conditions are met
## 3. Core Settings Groups
### Stochastic Settings
These settings control the core calculation of the stochastic oscillator.
1. ** Length (Default: 14) **
- What it does: Determines the lookback period for calculations
- Higher values (e.g., 21): More stable, fewer signals
- Lower values (e.g., 8): More sensitive, more signals
- Recommended:
* Day Trading: 8-14
* Swing Trading: 14-21
* Position Trading: 21-30
2. ** Smooth K (Default: 3) **
- What it does: Smooths the main stochastic line
- Higher values: Smoother line, fewer false signals
- Lower values: More responsive, but more noise
- Recommended:
* Day Trading: 2-3
* Swing Trading: 3-5
* Position Trading: 5-7
3. ** Smooth D (Default: 3) **
- What it does: Smooths the signal line
- Works in conjunction with Smooth K
- Usually kept equal to or slightly higher than Smooth K
- Recommended: Keep same as Smooth K for consistency
4. ** Source (Default: Close) **
- What it does: Determines price data for calculations
- Options: Close, Open, High, Low, HL2, HLC3, OHLC4
- Recommended: Stick with Close for most reliable signals
### Timeframe Settings
Controls the multiple timeframes analyzed by the indicator.
1. ** Main Timeframes (TF1-TF6) **
- TF1 (Default: 10): Shortest timeframe for quick signals
- TF2 (Default: 15): Short-term trend confirmation
- TF3 (Default: 30): Medium-term trend analysis
- TF4 (Default: 30): Additional medium-term confirmation
- TF5 (Default: 60): Longer-term trend analysis
- TF6 (Default: 240): Major trend confirmation
Recommended Combinations:
* Scalping: 1, 3, 5, 15, 30, 60
* Day Trading: 5, 15, 30, 60, 240, D
* Swing Trading: 15, 60, 240, D, W, M
2. ** Wait for Bar Close (Default: true) **
- What it does: Controls when calculations update
- True: More reliable but slightly delayed signals
- False: Faster signals but may change before bar closes
- Recommended: Keep True for more reliable signals
### Alert Settings
#### Main Alert Settings
1. ** Enable Alerts (Default: true) **
- Master switch for all alert notifications
- Toggle this off when you don't want any alerts
- Useful during testing or when you want to focus on visual signals only
2. ** Alert Condition (Options) **
- "Above Middle": Bullish momentum alerts only
- "Below Middle": Bearish momentum alerts only
- "Both": Alerts for both directions
- Recommended:
* Trending Markets: Choose direction matching the trend
* Ranging Markets: Use "Both" to catch reversals
* New Traders: Start with "Both" until you develop a specific strategy
3. ** Alert Frequency **
- "Once Per Bar": Immediate alerts during the bar
- "Once Per Bar Close": Alerts only after bar closes
- Recommended:
* Day Trading: "Once Per Bar" for quick reactions
* Swing Trading: "Once Per Bar Close" for confirmed signals
* Beginners: "Once Per Bar Close" to reduce false signals
#### Timeframe Check Settings
1. ** First Check (TF1) **
- Purpose: Confirms basic trend direction
- Alert Triggers When:
* For Bullish: Stochastic is above middle line (50)
* For Bearish: Stochastic is below middle line (50)
* For Both: Triggers in either direction based on position relative to middle line
- Settings:
* Enable/Disable: Turn first check on/off
* Timeframe: Default 5 minutes
- Best Used For:
* Quick trend confirmation
* Entry timing
* Scalping setups
2. ** Second Check (TF2) **
- Purpose: Confirms both position and momentum
- Alert Triggers When:
* For Bullish: Stochastic is above middle line AND both K&D lines are increasing
* For Bearish: Stochastic is below middle line AND both K&D lines are decreasing
* For Both: Triggers based on position and direction matching current condition
- Settings:
* Enable/Disable: Turn second check on/off
* Timeframe: Default 15 minutes
- Best Used For:
* Trend strength confirmation
* Avoiding false breakouts
* Day trading setups
3. ** Third Check (TF3) **
- Purpose: Confirms overall momentum direction
- Alert Triggers When:
* For Bullish: Both K&D lines are increasing (momentum confirmation)
* For Bearish: Both K&D lines are decreasing (momentum confirmation)
* For Both: Triggers based on matching momentum direction
- Settings:
* Enable/Disable: Turn third check on/off
* Timeframe: Default 30 minutes
- Best Used For:
* Major trend confirmation
* Swing trading setups
* Avoiding trades against the main trend
Note: All three conditions must be met simultaneously for the alert to trigger. This multi-timeframe confirmation helps reduce false signals and provides stronger trade setups.
#### Alert Combinations Examples
1. ** Conservative Setup **
- Enable all three checks
- Use "Once Per Bar Close"
- Timeframe Selection Example:
* First Check: 15 minutes
* Second Check: 1 hour (60 minutes)
* Third Check: 4 hours (240 minutes)
- Wider gaps between timeframes reduce noise and false signals
- Best for: Swing trading, beginners
2. ** Aggressive Setup **
- Enable first two checks only
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
- Closer timeframes for quicker signals
- Best for: Day trading, experienced traders
3. ** Balanced Setup **
- Enable all checks
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
* Third Check: 1 hour (60 minutes)
- Balanced spacing between timeframes
- Best for: All-around trading
### Visual Settings
#### Alert Visual Settings
1. ** Show Background Color (Default: true) **
- What it does: Highlights chart background when alerts trigger
- Benefits:
* Makes signals more visible
* Helps spot opportunities quickly
* Provides visual confirmation of alerts
- When to disable:
* If using multiple indicators
* When preferring a cleaner chart
* During manual backtesting
2. ** Background Transparency (Default: 90) **
- Range: 0 (solid) to 100 (invisible)
- Recommended Settings:
* Clean Charts: 90-95
* Multiple Indicators: 85-90
* Single Indicator: 80-85
- Tip: Adjust based on your chart's overall visibility
3. ** Background Colors **
- Bullish Background:
* Default: Green
* Indicates upward momentum
* Customizable to match your theme
- Bearish Background:
* Default: Red
* Indicates downward momentum
* Customizable to match your theme
#### Level Settings
1. ** Oversold Level (Default: 20) **
- Traditional Setting: 20
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 10): More conservative
* Higher values (e.g., 30): More aggressive
- Trading Applications:
* Potential bullish reversal zone
* Support level in uptrends
* Entry point for long positions
2. ** Overbought Level (Default: 80) **
- Traditional Setting: 80
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 70): More aggressive
* Higher values (e.g., 90): More conservative
- Trading Applications:
* Potential bearish reversal zone
* Resistance level in downtrends
* Exit point for long positions
3. ** Middle Line (Default: 50) **
- Purpose: Trend direction separator
- Applications:
* Above 50: Bullish territory
* Below 50: Bearish territory
* Crossing 50: Potential trend change
- Trading Uses:
* Trend confirmation
* Entry/exit trigger
* Risk management level
#### Color Settings
1. ** Bullish Color (Default: Green) **
- Used for:
* K-Line (Main stochastic line)
* Status symbols when trending up
* Trend labels for bullish conditions
- Customization:
* Choose colors that stand out
* Match your trading platform theme
* Consider color blindness accessibility
2. ** Bearish Color (Default: Red) **
- Used for:
* D-Line (Signal line)
* Status symbols when trending down
* Trend labels for bearish conditions
- Customization:
* Choose contrasting colors
* Ensure visibility on your chart
* Consider monitor settings
3. ** Neutral Color (Default: Gray) **
- Used for:
* Middle line (50 level)
- Customization:
* Should be less prominent
* Easy on the eyes
* Good background contrast
### Theme Settings
1. **Color Theme Options**
- Dark Theme (Default):
* Dark background with white text
* Optimized for dark chart backgrounds
* Reduces eye strain in low light
- Light Theme:
* Light background with black text
* Better visibility in bright conditions
- Custom Theme:
* Use your own color preferences
2. ** Available Theme Colors **
- Table Background
- Table Text
- Table Headers
Note: The theme affects only the table display colors. The stochastic lines and alert backgrounds use their own color settings.
### Table Settings
#### Position and Size
1. ** Table Position **
- Options:
* Top Right (Default)
* Middle Right
* Bottom Right
* Top Left
* Middle Left
* Bottom Left
- Considerations:
* Chart space utilization
* Personal preference
* Multiple monitor setups
2. ** Text Sizes **
- Title Size Options:
* Tiny: Minimal space usage
* Small: Compact but readable
* Normal (Default): Standard visibility
* Large: Enhanced readability
* Huge: Maximum visibility
- Data Size Options:
* Recommended: One size smaller than title
* Adjust based on screen resolution
* Consider viewing distance
3. ** Empowering Messages **
- Purpose:
* Maintain trading discipline
* Provide psychological support
* Remind of best practices
- Rotation:
* Changes every 5 bars
* Categories include:
- Market Wisdom
- Strategy & Discipline
- Mindset & Growth
- Technical Mastery
- Market Philosophy
## 4. Setting Up for Different Trading Styles
### Day Trading Setup
1. **Timeframes**
- Primary: 5, 15, 30 minutes
- Secondary: 1H, 4H
- Alert Settings: "Once Per Bar"
2. ** Stochastic Settings **
- Length: 8-14
- Smooth K/D: 2-3
- Alert Condition: Match market trend
3. ** Visual Settings **
- Background: Enabled
- Transparency: 85-90
- Theme: Based on trading hours
### Swing Trading Setup
1. ** Timeframes **
- Primary: 1H, 4H, Daily
- Secondary: Weekly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 14-21
- Smooth K/D: 3-5
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Optional
- Transparency: 90-95
- Theme: Personal preference
### Position Trading Setup
1. ** Timeframes **
- Primary: Daily, Weekly
- Secondary: Monthly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 21-30
- Smooth K/D: 5-7
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Disabled
- Focus on table data
- Theme: High contrast
## 5. Troubleshooting Guide
### Common Issues and Solutions
1. ** Too Many Alerts **
- Cause: Settings too sensitive
- Solutions:
* Increase timeframe intervals
* Use "Once Per Bar Close"
* Enable fewer timeframe checks
* Adjust stochastic length higher
2. ** Missed Signals **
- Cause: Settings too conservative
- Solutions:
* Decrease timeframe intervals
* Use "Once Per Bar"
* Enable more timeframe checks
* Adjust stochastic length lower
3. ** False Signals **
- Cause: Insufficient confirmation
- Solutions:
* Enable all three timeframe checks
* Use larger timeframe gaps
* Wait for bar close
* Confirm with price action
4. ** Visual Clarity Issues **
- Cause: Poor contrast or overlap
- Solutions:
* Adjust transparency
* Change theme settings
* Reposition table
* Modify color scheme
### Best Practices
1. ** Getting Started **
- Start with default settings
- Use "Both" alert condition
- Enable all timeframe checks
- Wait for bar close
- Monitor for a few days
2. ** Fine-Tuning **
- Adjust one setting at a time
- Document changes and results
- Test in different market conditions
- Find your optimal timeframe combination
- Balance sensitivity with reliability
3. ** Risk Management **
- Don't trade against major trends
- Confirm signals with price action
- Use appropriate position sizing
- Set clear stop losses
- Follow your trading plan
4. ** Regular Maintenance **
- Review settings weekly
- Adjust for market conditions
- Update color scheme for visibility
- Clean up chart regularly
- Maintain trading journal
## 6. Tips for Success
1. ** Entry Strategies **
- Wait for all timeframes to align
- Confirm with price action
- Use proper position sizing
- Consider market conditions
2. ** Exit Strategies **
- Trail stops using indicator levels
- Take partial profits at targets
- Honor your stop losses
- Don't fight the trend
3. ** Psychology **
- Stay disciplined with settings
- Don't override system signals
- Keep emotions in check
- Learn from each trade
4. ** Continuous Improvement **
- Record your trades
- Review performance regularly
- Adjust settings gradually
- Stay educated on markets
INTELLECT_city - US Presidential Elections Dates (USA)(EN)
It is interesting to compare Halvings Cycles and Presidential elections.
This indicator shows all presidential elections in the USA from the period 2008, and future ones to the date 2044. The indicator will automatically show all future dates of presidential elections.
--
To apply it to your chart it is very easy:
Select:
1) Exchange: BITSTAMP
2) Pair BTC \ USD (Without "T" at the end)
3) Timeframe 1 day
4) In the Browser, switch the chart to Logarithmic (on the right bottom, click the "L" button)
or on mobile, switch to "Logarithmic" we look on the chart: "Gear" - and switch to "Logarithmic"
------------------
(RU)
Интересно сопоставить Циклы Halvings и Президентские выборы.
Данный индикатор показывает все президентские выборы в США с периода 2008 года, и будущие к дате 2044 года. Индикатор будет автоматически показывать все будущие даты .
--
Что бы применить у себя на графике это очень легко:
Выберите:
1) Биржа: BITSTAMP
2) Пара BTC \ USD (Без "T" в конце)
3) Timeframe 1 дневной
4) В Браузере переключить график на Логарифмический (с право внизу кнопка "Л")
или на мобильно переключить на "Логарифмический" ищем на графике: "Шестеренку" — и переключаем на "Логарифмический"
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(DE)
Es ist interessant, die Halbierungszyklen und die Präsidentschaftswahlen zu vergleichen.
Dieser Indikator zeigt alle US-Präsidentschaftswahlen seit 2008 und zukünftige bis zum Datum 2044. Der Indikator zeigt automatisch alle zukünftigen Präsidentschaftswahltermine an.
--
Es ist sehr einfach, dies auf Ihr Diagramm anzuwenden:
Wählen:
1) Austausch: BITSTAMP
2) Paar BTC \ USD (Ohne das „T“ am Ende)
3) Zeitrahmen 1 Tag
4) Schalten Sie im Browser das Diagramm auf Logarithmisch um (die Schaltfläche „L“ unten rechts).
oder auf dem Mobilgerät auf „Logarithmisch“ umschalten, in der Grafik nach „Getriebe“ suchen – und auf „Logarithmisch“ umschalten
Fisher Transform on RSIOverview
The Fisher Transform on RSI indicator combines the Relative Strength Index (RSI) with the Fisher Transform to offer a refined tool for identifying market turning points and trends. By applying the Fisher Transform to the RSI, this indicator converts RSI values into a Gaussian normal distribution, enhancing the precision of detecting overbought and oversold conditions. This method provides a clearer and more accurate identification of potential market reversals than the standard RSI.
Key/Unique Features
Fisher Transform Applied to RSI : Transforms RSI values into a Gaussian normal distribution, improving the detection of overbought and oversold conditions.
Smoothing : Applies additional smoothing to the Fisher Transform, reducing noise and providing clearer signals.
Signal Line : Includes a signal line to identify crossover points, indicating potential buy or sell signals.
Custom Alerts : Built-in alert conditions for bullish and bearish crossovers, keeping traders informed of significant market movements.
Visual Enhancements : Background color changes based on crossover conditions, offering immediate visual cues for potential trading opportunities.
How It Works
RSI Calculation : The indicator calculates the Relative Strength Index (RSI) based on the selected source and period length.
Normalization : The RSI values are normalized to fit within a range of -1 to 1, which is essential for the Fisher Transform.
Fisher Transform : The normalized RSI values undergo the Fisher Transform, converting them into a Gaussian normal distribution.
Smoothing : The transformed values are smoothed using a simple moving average to reduce noise and provide more reliable signals.
Signal Line : A signal line, which is a simple moving average of the smoothed Fisher Transform, is plotted to identify crossover points.
Alerts and Visuals : Custom alert conditions are set for bullish and bearish crossovers, and the background color changes to indicate these conditions.
Usage Instructions
Trend Identification : Use the Fisher Transform on RSI to identify overbought and oversold conditions with enhanced precision, aiding in spotting potential trend reversals.
Trade Signals : Monitor the crossovers between the smoothed Fisher Transform and the signal line. A bullish crossover suggests a potential buying opportunity, while a bearish crossover indicates a potential selling opportunity.
Alerts : Set custom alerts based on the built-in conditions to receive notifications when important crossover events occur, ensuring you never miss a trading opportunity.
Visual Cues : Utilize the background color changes to quickly identify bullish (green) and bearish (red) conditions, providing immediate visual feedback on market sentiment.
Complementary Analysis : Combine this indicator with other technical analysis tools and indicators to enhance your overall trading strategy and make more informed decisions.
Markov Chain Trend IndicatorOverview
The Markov Chain Trend Indicator utilizes the principles of Markov Chain processes to analyze stock price movements and predict future trends. By calculating the probabilities of transitioning between different market states (Uptrend, Downtrend, and Sideways), this indicator provides traders with valuable insights into market dynamics.
Key Features
State Identification: Differentiates between Uptrend, Downtrend, and Sideways states based on price movements.
Transition Probability Calculation: Calculates the probability of transitioning from one state to another using historical data.
Real-time Dashboard: Displays the probabilities of each state on the chart, helping traders make informed decisions.
Background Color Coding: Visually represents the current market state with background colors for easy interpretation.
Concepts Underlying the Calculations
Markov Chains: A stochastic process where the probability of moving to the next state depends only on the current state, not on the sequence of events that preceded it.
Logarithmic Returns: Used to normalize price changes and identify states based on significant movements.
Transition Matrices: Utilized to store and calculate the probabilities of moving from one state to another.
How It Works
The indicator first calculates the logarithmic returns of the stock price to identify significant movements. Based on these returns, it determines the current state (Uptrend, Downtrend, or Sideways). It then updates the transition matrices to keep track of how often the price moves from one state to another. Using these matrices, the indicator calculates the probabilities of transitioning to each state and displays this information on the chart.
How Traders Can Use It
Traders can use the Markov Chain Trend Indicator to:
Identify Market Trends: Quickly determine if the market is in an uptrend, downtrend, or sideways state.
Predict Future Movements: Use the transition probabilities to forecast potential market movements and make informed trading decisions.
Enhance Trading Strategies: Combine with other technical indicators to refine entry and exit points based on predicted trends.
Example Usage Instructions
Add the Markov Chain Trend Indicator to your TradingView chart.
Observe the background color to quickly identify the current market state:
Green for Uptrend, Red for Downtrend, Gray for Sideways
Check the dashboard label to see the probabilities of transitioning to each state.
Use these probabilities to anticipate market movements and adjust your trading strategy accordingly.
Combine the indicator with other technical analysis tools for more robust decision-making.
Market Cipher B by WeloTradesMarket Cipher B by WeloTrades: Detailed Script Description
//Overview//
"Market Cipher B by WeloTrades" is an advanced trading tool that combines multiple technical indicators to provide a comprehensive market analysis framework. By integrating WaveTrend, RSI, and MoneyFlow indicators, this script helps traders to better identify market trends, potential reversals, and trading opportunities. The script is designed to offer a holistic view of the market by combining the strengths of these individual indicators.
//Key Features and Originality//
WaveTrend Analysis:
WaveTrend Channel (WT1 and WT2): The core of this script is the WaveTrend indicator, which uses the smoothed average of typical price to identify overbought and oversold conditions. WT1 and WT2 are calculated to track market momentum and cyclical price movements.
Major Divergences (🐮/🐻): The script detects and highlights major bullish and bearish divergences automatically, providing traders with visual cues for potential reversals. This helps in making informed decisions based on divergence patterns.
Relative Strength Index (RSI):
RSI Levels: RSI is used to measure the speed and change of price movements, with specific levels indicating overbought and oversold conditions.
Customizable Levels: Users can configure the overbought and oversold thresholds, allowing for a tailored analysis based on individual trading strategies.
MoneyFlow Indicator:
Fast and Slow MoneyFlow: This indicator tracks the flow of capital into and out of the market, offering insights into the underlying market strength. It includes configurable periods and multipliers for both fast and slow MoneyFlow.
Vertical Positioning: The script allows users to adjust the vertical position of MoneyFlow plots to maintain a clear and uncluttered chart.
Stochastic RSI:
Stochastic RSI Levels: This combines the RSI and Stochastic indicators to provide a momentum oscillator that is sensitive to price changes. It is used to identify overbought and oversold conditions within a specified period.
Customizable Levels: Traders can set specific levels for more precise analysis.
//How It Works//
The script integrates these indicators through advanced algorithms, creating a synergistic effect that enhances market analysis. Here’s a detailed explanation of the underlying concepts and calculations:
WaveTrend Indicator:
Calculation: WaveTrend is based on the typical price (average of high, low, and close) smoothed over a specified channel length. WT1 and WT2 are derived from this typical price and further smoothed using the Average Channel Length. The difference between WT1 and WT2 indicates momentum, helping to identify cyclical market trends.
RSI (Relative Strength Index):
Calculation: RSI calculates the average gains and losses over a specified period to measure the speed and change of price movements. It oscillates between 0 and 100, with levels set to identify overbought (>70) and oversold (<30) conditions.
MoneyFlow Indicator:
Calculation: MoneyFlow is derived by multiplying price changes by volume and smoothing the results over specified periods. Fast MoneyFlow reacts quickly to price changes, while Slow MoneyFlow offers a broader view of capital movement trends.
Stochastic RSI:
Calculation: Stochastic RSI is computed by applying the Stochastic formula to RSI values, which highlights the RSI’s relative position within its range over a given period. This helps in identifying momentum shifts more precisely.
//How to Use the Script//
Display Settings:
Users can enable or disable various components like WaveTrend OB & OS levels, MoneyFlow plots, and divergence alerts through checkboxes.
Example: Turn on "Show Major Divergence" to see major bullish and bearish divergence signals directly on the chart.
Adjust Channel Settings:
Customize the data source, channel length, and smoothing periods in the "WaveTrend Channel SETTINGS" group.
Example: Set the "Channel Length" to 10 for a more responsive WaveTrend line or adjust the "Average Channel Length" to 21 for smoother trends.
Set Overbought & Oversold Levels:
Configure levels for WaveTrend, RSI, and Stochastic RSI in their respective settings groups.
Example: Set the WaveTrend Overbought Level to 60 and Oversold Level to -60 to define critical thresholds.
Money Flow Settings:
Adjust the periods and multipliers for Fast and Slow MoneyFlow indicators, and set their vertical positions for better visualization.
Example: Set the Fast Money Flow Period to 9 and Slow Money Flow Period to 12 to capture both short-term and long-term capital movements.
//Justification for Combining Indicators//
Enhanced Market Analysis:
Combining WaveTrend, RSI, and MoneyFlow provides a more comprehensive view of market conditions. Each indicator brings a unique perspective, making the analysis more robust.
WaveTrend identifies cyclical trends, RSI measures momentum, and MoneyFlow tracks capital movement. Together, they provide a multi-dimensional analysis of the market.
Improved Decision-Making:
By integrating these indicators, the script helps traders make more informed decisions. For example, a bullish divergence detected by WaveTrend might be validated by an RSI moving out of oversold territory and supported by increasing MoneyFlow.
Customization and Flexibility:
The script offers extensive customization options, allowing traders to tailor it to their specific needs and strategies. This flexibility makes it suitable for different trading styles and timeframes.
//Conclusion//
The indicator stands out due to its innovative combination of WaveTrend, RSI, and MoneyFlow indicators, offering a well-rounded tool for market analysis. By understanding how each component works and how they complement each other, traders can leverage this script to enhance their market analysis and trading strategies, making more informed and confident decisions.
Remember to always backtest the indicator first before implying it to your strategy.
Heikin Ashi ROC Percentile Strategy**User Guide for the "Heikin Ashi ROC Percentile Strategy"**
This strategy, "Heikin Ashi ROC Percentile Strategy", is designed to provide an easy-to-use framework for trading based on the Heikin Ashi Rate of Change (ROC) and its percentiles.
Here's how you can use it:
1. **Setting the Start Date**: You can set the start date for the strategy in the user inputs at the top of the script. The variable `startDate` defines the point from which the script begins executing trades. Simply input the desired date in the format "YYYY MM DD". For example, to start the strategy from March 3, 2023, you would enter `startDate = timestamp("2023 03 03")`.
2. **Adjusting the Midline, Lookback Period, and Stop Loss Level**: The `zerohLine`, `rocLength`, and `stopLossLevel` inputs allow you to adjust the baseline for ROC, the lookback period for the SMA and ROC, and the level at which the strategy stops the loss, respectively. By tweaking these parameters, you can fine-tune the strategy to better suit your trading style or the particular characteristics of the asset you are trading.
3. **Understanding the Trade Conditions**: The script defines conditions for entering and exiting long and short positions based on crossovers and crossunders of the ROC and the upper and lower "kill lines". These lines are defined as certain percentiles of the ROC's highest and lowest values over a specified lookback period. When the ROC crosses above the lower kill line, the script enters a long position; when it crosses below the upper kill line, it exits the position. Similarly, when the ROC crosses below the upper kill line, the script enters a short position; when it crosses above the lower kill line, it exits the position.
In my testing, this strategy performed best on a day and hour basis. However, I encourage you to experiment with different timeframes and settings to see how the strategy performs under various conditions. Remember, there's no one-size-fits-all approach to trading; what works best will depend on your specific circumstances, goals, and risk tolerance.
If you find other useful applications for this strategy, please let me know in the comments. Your feedback is invaluable in helping to refine and improve this tool. Happy trading!
