[GetSparx] Nova Pro⚡ Nova Pro – Position Calculator
This indicator is a user-friendly TradingView indicator designed to help traders plan and visualize their entry and exit points, calculate position sizing, and instantly display key risk metrics. By simply entering three price levels (Entry, Take Profit and Stop Loss) along with a risk amount in USD, the indicator draws color-coded lines and labels on the chart, and generates a concise table with all computed values. This allows you to assess the risk-reward profile of any trade at a glance, without performing manual calculations.
⚙️ How It Works
When the indicator is added to the chart it will ask to specify the price inputs and the risk amount in USD.
Price Inputs (Entry, TP, SL)
• You specify three price levels: the entry price, the profit target (Take Profit) and the loss threshold (Stop Loss).
• Inputs use TradingView’s native price-picker fields. Any change is immediately reflected on the chart.
Visual Display
• Each level is plotted as a line stretching into the future for enough room.
• Labels on the right show the exact price, color-coded: orange for Entry, green for TP and red for SL.
• Previous lines and labels are automatically removed when parameters change, ensuring the chart remains clean.
Risk Calculations
• The entered risk amount (in USD) is combined with the distance between Entry and SL to compute the optimal number of units (Qty) to trade.
• The script automatically detects whether it’s a long or short trade based on the relative positions of Entry and TP.
• Note that the risk and reward calculations do not factor in exchange fees, slippage, funding rates or any other trading costs. Actual profit and loss may differ once transaction fees and market execution variances are applied, so be sure to adjust your position sizing and expectations accordingly.
🎯 What You Can Do With It
• Consistent Position Sizing
Automate your position size so you consistently risk the same dollar amount, regardless of price volatility or stop distance.
• Clear Risk Management
Instantly view your Reward-to-Risk ratio, potential profit in USD and exact risk amount, so you make well-informed decisions.
• Rapid Scenario Analysis
Adjust TP, SL or Entry on the fly to see how each change affects your potential profit, loss and RR ratio.
• Publication-Ready Charts
The visual elements and integrated table are optimized for TradingView publications, giving your analysis a professional, polished look.
📊 Explanation of Table Values
• Entry
Calculation: rounded to the nearest tick of your entered entry price.
Marks the exact level at which you initiate the trade and serves as the reference point for all further risk and reward calculations.
• Quantity (Qty)
Calculation: Risk USD ÷ (Entry − Stop Loss).
Determines how many units, contracts or shares to trade so that a stop-out at your SL equals exactly your predefined dollar risk, resulting in consistent per-trade exposure.
• Risk to Reward (RR)
Calculation: (Take Profit − Entry) ÷ (Entry − Stop Loss).
Expresses how many dollars of potential profit you target for each dollar you risk. Values above 1 mean the reward exceeds the risk, guiding you to favorable setups.
• Take Profit (TP)
Calculation: rounded to the nearest tick of your entered take-profit price.
Your target exit level for booking gains, highlighted in green on the chart. Shows where you plan to capture profits if the market moves in your favor.
• Profit
Calculation: Qty × (Take Profit − Entry).
Gives the absolute potential gain in USD if price reaches your TP. Useful for comparing total return across different instruments or setups.
• Stop Loss (SL)
Calculation: rounded to the nearest tick of your entered stop-loss price.
The level at which your trade is automatically closed to cap losses, highlighted in red on the chart. Ensures you never lose more than your defined risk amount.
• Risk
Calculation: equals the entered Risk USD.
The maximum dollar amount you’re willing to lose on this trade. Acts as the upper boundary for your exposure, keeping your position sizing disciplined.
📝 Examples
• Long Example 1: Bitcoin/USD
Entry: $11851.1
Take Profit: $123853.9
Stop Loss: $115467.7
Risk USD: $500
The Risk to Reward ratio results in 2.25, which means the reward exceeds the risk.
For each dollar you risk, this setup has potential gains of 2.25 dollars.
• Long Example 2: Algorand/USD
Entry: $0.2919
Take Profit: $0.3491
Stop Loss: $0.2655
Risk USD: $1000
The Risk to Reward ratio on this trade results in 2.17 and has a potential profit target of $2166.67. With a risk of $1000 USD the table conveniently shows a quantity of 37878 ALGO is needed for the trade.
• Short Example 1: Forex EUR/USD
Entry: $1.16666
Take Profit: $1.15459
Stop Loss: $1.17374
Risk USD: $200
With a risk of $200 USD and a RR of 2.17, this example shows how a short trade can be accomplished on EUR/USD.
• Short Example 2: Gold
Entry: $3366.29
Take Profit: $3272.01
Stop Loss: $3386.87
Risk USD: $1500
Within this short setup a risk of $1500 USD is used, which results in a RR of 4.58. The potential profit for this trade is $6871.72.
⚠ Disclaimer
This tool is for educational and analytical use only. It does not provide financial advice or trading signals. Always use proper risk management and do your own due diligence.
在脚本中搜索"profit"
Institutional Dominance & Trapped Trader @MaxMaserati 3.0 Institutional Dominance & Trapped Trader Delta Profile @MaxMaserati 3.0
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Overview
The IDT Auction Profile is a professional-grade volume order flow analysis tool that reveals where institutional traders hold Positional Advantage and where retail participants are Trapped. Unlike traditional Volume Profile indicators, the IDT Profile integrates Volume Point Delta (VPD) analysis with advanced pattern recognition to identify the exact price levels where profitable institutional positions create support/resistance, and where losing positions are forced to exit.
This indicator answers the critical questions: Who is in profit? Who is trapped? And where will they defend or exit their positions?
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Core Concept: Dominance vs Trapped Positioning
════════════════════════════════════════════════════════════TThe indicator categorizes all market participants into two strategic positions based on their entry price relative to current market price:
Above Current Price (Resistance Zones)
🔴 Aggressive Sellers in Profit - Sold higher, currently winning. Will defend positions or add to winners.
🟥 Trapped Buyers at Loss - Bought higher, currently losing. Must exit at breakeven, creating resistance.
Below Current Price (Support Zones)
🟢 Aggressive Buyers in Profit - Bought lower, currently winning. Will defend positions or add to winners.
🟩 Trapped Sellers at Loss - Sold lower, currently losing. Must cover at breakeven, creating support.
Maximum Confluence Zones
When Dominant (Profitable) and Trapped (Loss) positions align at the same level, you get the strongest support/resistance zones. These appear as:
🟧 Orange Boxes (Above Price) = Aggressive Sellers + Trapped Buyers = STRONGEST RESISTANCE
🟨 Yellow Boxes (Below Price) = Aggressive Buyers + Trapped Sellers = STRONGEST SUPPORT
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VOLUME ANALYSIS
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1. VPD Column (Volume Point Delta)
Net aggressive pressure at each price level (Buying Volume - Selling Volume).
Bullish Delta (Green): Buyers dominated the auction at this level
Bearish Delta (Red): Sellers dominated the auction at this level
Smart Coloring: Automatically highlights institutional patterns (icebergs, absorption, spikes, failed auctions)
2. VPS Column (Volume Point of Sell - ASK Volume)
Aggressive buying volume that "lifted the offer" by hitting ask prices.
Represents participants who paid the ask price to enter long
When price is below this level = These buyers are in profit
When price is above this level = These sellers who got hit are in profit
3. VPB Column (Volume Point of Buy - BID Volume)
Aggressive selling volume that "hit the bid" by taking bid prices.
Represents participants who sold at bid price to enter short
When price is above this level = These sellers are in profit
When price is below this level = These buyers who got hit are in profit
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🧠 ADVANCED INSTITUTIONAL PATTERNS DETECTION
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The indicator uses statistical analysis (standard deviation, moving averages, hit counting) to identify institutional footprints:
Failed Auctions ⚡
"BUYERS TRAPPED" or "SELLERS TRAPPED" labels
High volume entered, but price immediately reversed
Creates extreme concentrations of losing positions
Trading Implication: High-probability reversal zones where trapped participants must exit
Volume Spikes 📈📉
Bright green/red bars in VPD column
Volume exceeds average by 2+ standard deviations
Represents aggressive institutional entry
Trading Implication: Potential trend continuation or setup for failed auction
Absorption Zones 🛡️
Yellow/Orange colored bars
Large passive orders absorbing aggressive volume without price movement
Indicates accumulation (bullish) or distribution (bearish)
Trading Implication: Institutional positioning before major moves
Iceberg Orders 🧊
Cyan colored bars with high hit counts
Same price level shows repeated volume without clearing
Reveals hidden institutional limit orders split into small pieces
Trading Implication: Strong liquidity magnets, price often returns here
Volume Exhaustion 💜
Purple colored bars
Sharp volume drop (50%+) after spike
Momentum exhausted, participants depleted
Trading Implication: Potential reversal or consolidation ahead
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Colors bars based on detected patterns vs simple red/green
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Yellow = Bullish battles won
Orange = Bearish battles won
Cyan = Iceberg orders
Purple = Large passive orders
Bright Green = Buying spikes
Bright Red = Selling spikes
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Confluence Scoring ⭐
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Each price level receives 1-5 stars based on:
Volume spike presence (+2 stars)
Absorption pattern (+1 star)
Large passive orders (+1 star)
Proximity to Value Area (+1 star)
Iceberg detection (+2 stars)
Failed auction (+2 stars)
Minimum Signal Strength filter lets you show only levels with ★3+ confluence for highest-quality signals.
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📍 Value Area Analysis
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VAH (Value Area High) - Blue Line
Top of the 70% volume acceptance zone. Price at VAH often rejects downward.
VAL (Value Area Low) - Red Line
Bottom of the 70% volume acceptance zone. Price at VAL often bounces upward.
Trading Applications:
Price outside Value Area → Mean reversion opportunity
Price breaks VA with volume → Trend continuation
Price oscillates within VA → Range-bound, fade extremes
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EXPECTED PORICE BEHAVIOR AT KEY LEVELS
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⚠️ IMPORTANT: These are observed behavioral patterns for educational purposes and backtesting research. Always validate with 250-500+ backtest trades before risking capital. Use this indicator to enhance your existing strategy, not as a standalone system.
1. POC Box Zones (Highest Statistical Relevance)
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🟨 Yellow Boxes (Below Current Price)
Expected Behavior:
Price approaching from above typically encounters buying pressure
Both profitable institutional buyers and trapped short sellers create demand
Common reaction: Price slows, consolidates, or bounces
Failed bounces often lead to rapid breakdown (trapped buyers capitulate)
What Often Happens:
Initial dip into zone → Weak bounce attempt
Second test → Stronger bounce (trapped sellers covering + buyers defending)
Break below → Quick acceleration as both groups exit
Backtesting Focus:
Measure bounce success rate at ★3+ vs ★4-5 zones
Track how often price returns after initial rejection
Compare behavior during trending vs ranging markets
🟧 Orange Boxes (Above Current Price)
Expected Behavior:
Price rallying into zone typically encounters selling pressure
Both profitable institutional sellers and trapped long buyers create supply
Common reaction: Price stalls, consolidates, or rejects
What Often Happens:
Initial push into zone → Weak rejection
Second test → Stronger rejection (trapped buyers exiting + sellers defending)
Break above → Quick acceleration as resistance becomes support
Backtesting Focus:
Measure rejection success rate by confluence score
Track false breakouts vs genuine breakouts
Identify market conditions that favor breakouts vs reversals
2. Failed Auction Zones
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"SELLERS TRAPPED" Labels (Below Price)
Expected Behavior:
High-volume selling that immediately reversed = maximum trapped short positions
When price returns to this level, trapped sellers face pressure to cover
Typical pattern: Price approaches → Initial hesitation → Sharp bounce
Common Price Action:
First retest: Quick spike through level then immediate recovery
Subsequent retests: Stronger bounces as fewer trapped sellers remain
Level becomes support after trapped positions cleared
Backtesting Focus:
Success rate of bounces on first vs second retest
Time decay: Does signal strength diminish after X bars?
Volume characteristics during successful bounces
"BUYERS TRAPPED" Labels (Above Price)
Expected Behavior:
High-volume buying that immediately failed = maximum trapped long positions
Price returning forces trapped buyers to exit at breakeven
Typical pattern: Price approaches → Distribution → Rejection
Common Price Action:
First retest: Shallow penetration then swift rejection
Multiple retests: Weaker rallies as trapped positions cleared
Level becomes resistance until breakout occurs
Backtesting Focus:
How many retests before level breaks?
Volume profile changes on each successive test
Correlation with broader market direction
3. Value Area Dynamics
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Price Outside Value Area (VAH/VAL)
Expected Behavior:
Price beyond 70% volume zone = statistical outlier
Two outcomes: Mean reversion OR trend continuation
Key differentiator: Presence of confluence zones
Mean Reversion Pattern (No Strong Confluence):
Price extends 1-2% beyond VA → Typically reverts toward POC
Weak volume on extension → Higher probability of reversal
Price oscillates back into value area over several bars
Breakout Pattern (With ★4+ Confluence):
Price breaks VA with institutional patterns → Often continues
Strong volume + confluence = New value area forming
Old VA becomes reference point for pullbacks
Backtesting Focus:
Success rate of fades based on distance from VA
Confluence requirements for successful breakouts
Time of day / session impact on VA behavior
4. Iceberg Order Behavior
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Cyan Bars with High Hit Counts
Expected Behavior:
Repeated volume at same level = Large hidden order absorbing
Price typically "tests" iceberg multiple times before resolution
Two outcomes: Absorption complete (break) OR rejection (bounce)
Absorption Phase:
Price approaches → Slows near iceberg → Minimal movement
Volume increases but price range contracts
Acts as temporary support/resistance
Resolution Phase:
Iceberg filled → Sudden acceleration through level
Iceberg defended → Sharp rejection away from level
Post-resolution: Level often becomes support/resistance flip
Backtesting Focus:
Average number of tests before resolution
Volume characteristics when iceberg breaks vs holds
Timeframe impact on iceberg effectiveness
5. Volume Spike Patterns
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Bright Green/Red Bars (Institutional Aggression)
Expected Behavior:
Extreme delta spikes indicate institutional entry
Two scenarios: Continuation (spike in trend direction) OR Exhaustion (spike against trend)
Trend Continuation Spikes:
Spike + ★4+ confluence + aligned with trend = Often continues
Price may consolidate briefly then resume direction
These levels become support/resistance on pullbacks
Exhaustion Spikes:
Spike against trend + followed by reversal = Failed auction forming
High probability of "TRAPPED" label appearing
Often marks short-term extremes
Backtesting Focus:
Distinguish continuation vs exhaustion spikes
Success rate based on trend alignment
Time holding before reversal occurs
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💡 Best Practices
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Start with defaults (200 lookback, 60 rows, ★3 confluence, Classic colors, Smart Coloring ON)
Focus on POC boxes first - These are your highest-probability zones
Combine with price action - Use the profile to explain WHY support/resistance exists
Watch for alignment - Yellow/Orange boxes (both participant types) = strongest levels
Respect failed auctions - "TRAPPED" labels are extreme reversal setups
Use Value Area for context - Price outside VA = opportunity for mean reversion
Trust confluence scores - ★4-5 signals are institutional-grade setups
Adjust timeframe settings - Lower lookback for scalping, higher for position trading
🔧 Technical Notes
Calculation: Enhanced delta using OHLC and volume with wick ratio analysis
Updates: Real-time on every bar close
Performance: Optimized for up to 500 bars lookback and 250 price rows
Compatibility: Works on all symbols and timeframes
Indicator Unique Value
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Unlike standard Volume Profile indicators that only show where volume occurred,
the IDT Auction Profile:
✅ Separates bid vs ask volume to reveal true order flow
✅ Identifies who is profitable vs who is trapped at each level
✅ Detects institutional patterns (icebergs, absorption, failed auctions)
✅ Calculates confluence scores combining multiple factors
✅ Provides clear POC boxes showing exact institutional positioning
✅ Maps positional advantage rather than just volume density
This transforms Volume Profile from a historical volume chart into a strategic positioning map showing institutional dominance and trapped participants.
How to Integrate with Your Strategy
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✅ Proper Uses:
Entry refinement within your existing setups
Intelligent stop placement beyond institutional levels
Objective profit targets at next confluence zones
Trade filtering (only take setups at ★4+ zones)
Understanding market positioning before entry
❌ What It Cannot Do:
Predict direction with certainty
Replace risk management
Account for news/external events
Guarantee profitability
Work in all market conditions
Development Path (12-16 Weeks)
Weeks 1-2: Observation Only
Watch price behavior at key levels
Document patterns without trading
Weeks 3-8: Paper Trading
Simulate trades, track all metrics
Minimum 100 paper trades
Weeks 9-16: Small Size Testing
Minimal capital, real market conditions
Continue tracking, refine rules
After Proven Edge: Scale Position Sizing
Critical Disclaimers
⚠️ Past volume ≠ Future price action
⚠️ Institutional positions change rapidly - these are static snapshots
⚠️ No indicator works 100% - risk management is mandatory
⚠️ Market conditions change - adapt your approach
⚠️ Backtest with YOUR style, YOUR timeframe, YOUR risk tolerance
The indicator reveals WHERE institutions are positioned and HOW they might behave. YOU decide IF, WHEN, and HOW to trade that information.
Not financial advice. For educational and research purposes only.
Pressure Pivots - MPIPressure Pivots - MPI
A multi-factor reversal detection system built on a proprietary Market Pressure Index (MPI) that combines institutional order flow analysis, liquidity dynamics, and momentum exhaustion to identify high-probability pivot points with automated win rate validation.
What This System Does
This indicator solves the core challenge of reversal trading: distinguishing genuine exhaustion pivots from temporary retracements. It combines six independent detection mechanisms—divergence, liquidity sweeps, order flow imbalance, wick rejection, volume surges, and velocity exhaustion—weighted by reliability and unified through a custom pressure oscillator.
Three-Layer Architecture:
Layer 1 - Market Pressure Index (MPI): Proprietary volume-weighted pressure oscillator that measures buying vs. selling pressure using proportional intrabar allocation and dual-timeframe normalization (-1.0 to +1.0 range).
Layer 2 - Weighted Confluence Engine: Six detection factors scored hierarchically (divergence: 3.0 pts, liquidity: 2.5 pts, order flow: 2.0 pts, velocity: 1.5 pts, wick: 1.5 pts, volume: 1.0 pt). Premium signals (DIV/LIQ/OF) require 6.0+ score, standard signals (STD) require 4.0+ score.
Layer 3 - Automated Win Rate Validation: Every signal tracked forward and validated against actual pivot formation within 10-bar window. Real-time performance statistics displayed by signal type and direction.
The Market Pressure Index - Original Calculation
What MPI Measures: The balance of aggressive buying vs. aggressive selling within each bar, smoothed and normalized to create a continuous oscillator.
Calculation Methodology:
Step 1: Intrabar Pressure Decomposition
Buy Pressure = Volume × (Close - Low) / (High - Low)
Sell Pressure = Volume × (High - Close) / (High - Low)
Net Pressure = Buy Pressure - Sell Pressure
Step 2: Exponential Smoothing
Smooth Pressure = EMA(Net Pressure, 14)
Step 3: Normalization
Avg Absolute Pressure = SMA(|Net Pressure|, 28)
MPI Raw = Smooth Pressure / Avg Absolute Pressure
Step 4: Sensitivity Amplification
MPI = clamp(MPI Raw × 1.5, -1.0, +1.0)
Why This Is Different:
• vs. RSI: RSI measures price momentum without volume context. MPI integrates volume magnitude and distribution within each bar.
• vs. OBV: OBV uses binary classification (up bar = buy volume). MPI uses proportional allocation based on close position within range.
• vs. Money Flow Index: MFI uses typical price × volume. MPI uses intrabar positioning, revealing pressure balance regardless of bar-to-bar movement.
• vs. VWAP: VWAP shows average price. MPI shows directional pressure balance (who controls the bar).
MPI Interpretation:
• +0.7 to +1.0: Extreme buying pressure (strong uptrends, potential exhaustion)
• +0.3 to +0.7: Moderate buying pressure (healthy uptrends)
• -0.3 to +0.3: Neutral/balanced (ranging, consolidation)
• -0.7 to -0.3: Moderate selling pressure (healthy downtrends)
• -1.0 to -0.7: Extreme selling pressure (strong downtrends, potential exhaustion)
Critical Insight: MPI at extremes indicates pressure exhaustion risk , not automatic reversal. Reversals occur when extreme MPI coincides with confluence factors.
Six Confluence Factors - Detection Arsenal
1. Divergence Detection (Weight: 3.0 - Highest Priority)
Detects: Price making higher highs while MPI makes lower highs (bearish), or price making lower lows while MPI makes higher lows (bullish).
Why It Matters: Reveals weakening pressure behind price moves. Declining participation signals potential reversal.
Signal Type: Premium (DIV) - Historically highest win rates.
2. Liquidity Sweep Detection (Weight: 2.5)
Detects: Price penetrates recent swing high/low (triggering stops), then immediately reverses and closes back inside range.
Calculation: High breaks swing high by <0.3× ATR but closes below it (bearish), or low breaks swing low by <0.3× ATR but closes above it (bullish).
Why It Matters: Stop hunts mark institutional accumulation/distribution zones. Often pinpoints exact pivot points.
Signal Type: Premium (LIQ) - Extremely reliable with volume confirmation.
3. Order Flow Imbalance (Weight: 2.0)
Detects: Aggressive directional ordering where price consistently closes in upper/lower third of bars with elevated volume.
Calculation:
Close Position = (Close - Low) / (High - Low)
Aggressive Buy = Volume when Close Position > 0.65
Aggressive Sell = Volume when Close Position < 0.35
Imbalance = EMA(Aggressive Buy, 5) - EMA(Aggressive Sell, 5)
Strong Flow = |Imbalance| > 1.5 × Average
Why It Matters: Reveals institutional accumulation/distribution footprints before directional moves.
Signal Type: Premium (OF)
4. Wick Rejection Patterns (Weight: 1.5)
Detects: Pin bars, hammers, shooting stars where wick exceeds 60% of total bar range.
Why It Matters: Large wicks demonstrate failed attempts to push price, indicating strong opposition.
5. Volume Spike Detection (Weight: 1.0)
Detects: Volume exceeding 2× the 20-bar average.
Why It Matters: Confirms institutional participation vs. retail noise. Most effective when combined with wick rejection or liquidity sweeps.
6. Velocity Exhaustion (Weight: 1.5)
Detects: Parabolic moves (velocity >2.0× ATR over 3 bars) showing deceleration while MPI at extremes.
Calculation:
Velocity = Change(Close, 3) / ATR(14)
Exhaustion = |Velocity| > 2.0 AND MPI > |0.5| AND Velocity Slowing
Why It Matters: Extended moves are unsustainable. Momentum deceleration from extremes precedes reversals.
Signal Classification & Scoring
Weighted Confluence Scoring:
Each factor contributes points when present. Signals fire when total score exceeds thresholds:
Bearish Example:
+ At recent high (1.0)
+ Bearish divergence (3.0)
+ Wick rejection (1.5)
+ Volume spike (1.0)
+ Velocity slowing (1.5)
= 8.0 total score → BEARISH DIV SIGNAL
Bullish Example:
+ At recent low (1.0)
+ Liquidity sweep (2.5)
+ Strong buy flow (2.0)
+ Wick rejection (1.5)
= 7.0 total score → BULLISH LIQ SIGNAL
Dual Threshold System:
• Premium Signals (DIV/LIQ/OF): Require 6.0+ points. Must include divergence, liquidity sweep, or order flow. Higher win rates.
• Standard Signals (STD): Require 4.0+ points. No premium factors. More frequent, moderate win rates.
Visual Signal Color-Coding:
• Purple Triangle: DIV (Divergence signal)
• Orange Triangle: LIQ (Liquidity sweep signal)
• Aqua Triangle: OF (Order flow signal)
• Red/Green Triangle: STD (Standard signal)
• Yellow Diamond: Warning (setup forming, not confirmed)
Warning System - Early Alerts
Yellow diamond warnings fire when 2+ factors present but full confluence not met:
• At recent 10-bar high/low
• Wick rejection present
• Volume spike present
• MPI extreme or accelerating/decelerating
Critical: Warnings are NOT trade signals. They indicate potential setups forming. Wait for colored triangle confirmation.
Win Rate Validation - Transparent Performance Tracking
How It Works:
Signal Storage: Every signal recorded (bar index, price, type, direction)
Pivot Confirmation: System monitors next 10 bars for confirmed pivot formation at signal price (±2%)
Validation: If pivot forms within window → Win. If not → Loss.
Statistics: Win Rate = Validated Signals / Total Mature Signals × 100
Dashboard Displays:
• Overall win rate with visual bar
• Bearish signal win rate
• Bullish signal win rate
• Win rate by signal type (DIV/LIQ/OF/STD)
• Wins/Total for each category
Why This Matters:
After 30-50 signals, you'll know exactly which patterns work on your instrument:
Example Performance Analysis:
Overall: 58% (35/60)
Bearish: 52% | Bullish: 65%
DIV: 72% | LIQ: 68% | OF: 50% | STD: 38%
Insight: Focus on bullish DIV/LIQ signals (72%/68% win rate), avoid STD signals (38%), investigate bearish underperformance.
This transforms the indicator from signal generator to learning system.
Dynamic Microstructure Visualization
Fibonacci Retracement Levels
• Auto-detects last swing high + swing low
• Draws 11 levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Removes crossed levels automatically
• Clears on new signal (fresh structure analysis)
• Color gradient (bullish to bearish across range)
• Key levels (0.618, 0.5, 1.0) highlighted with solid lines
Support/Resistance Lines
• Resistance: 50-bar highest high (red, only shown when above price)
• Support: 50-bar lowest low (green, only shown when below price)
• Auto-removes when price crosses
Usage: Signals firing at key Fibonacci levels (38.2%, 50%, 61.8%) or major S/R zones have enhanced structural significance.
Dashboard - Real-Time Intelligence
MPI Status:
• Current pressure reading with interpretation
• Color-coded background (green/red/gray zones)
Signal Status:
• Active signal type and direction
• Confidence score with visual bar (20 blocks, color-coded)
• Scanning status when no signal active
Divergence Indicator:
• Highlights active divergence separately (highest priority factor)
Performance Stats:
• Overall win rate with 10-block visual bar
• Directional breakdown (bearish vs. bullish)
• Signal type breakdown (DIV/LIQ/OF/STD individual win rates)
• Sample size for each category
Customization:
• Position: 9 locations (Top/Middle/Bottom × Left/Center/Right)
• Size: Tiny/Small/Normal/Large
• Toggle sections independently
How to Use This System
Initial Setup (10 Minutes)
1. MPI Configuration:
• Period: 14 (balanced) | 5-10 for scalping | 21-30 for swing
• Sensitivity: 1.5 (moderate) | Increase if MPI rarely hits ±0.7 | Decrease if constantly maxed
2. Detection Thresholds:
• Wick Threshold: 0.6 (60% of bar must be wick)
• Volume Spike: 2.0× average (lower to 1.5-1.8 for stocks, raise to 2.5-3.0 for crypto)
• Velocity: 2.0 ATR (raise to 2.5-3.0 for crypto)
3. Confluence Settings:
• Enable Divergence (highest win rate factor)
• Pivot Lookback: 5 (day trading) | 8-10 (swing trading)
• Keep default weights initially
4. Thresholds:
• Premium: 6.0 (quality over quantity)
• Standard: 4.0 (balanced)
• Warning: 2 factors minimum
Trading Workflow
When Warning Fires (Yellow Diamond):
Note warning type (bearish/bullish)
Do not enter - this is preparation only
Monitor for full signal confirmation
Prepare entry parameters
When Signal Fires (Colored Triangle):
Identify type from color (Purple=DIV, Orange=LIQ, Aqua=OF, Red/Green=STD)
Check dashboard confidence score
Verify confluence on chart (wick, volume, MPI extreme, Fib level)
Confirm with your analysis (context, higher timeframe, news)
Enter with proper risk management
Risk Management (Not Provided by Indicator):
• Stop Loss: Beyond recent swing or 1.5-2.0× ATR
• Position Size: Risk 0.5-2% of capital per trade
• Take Profit: 2-3× ATR or next structural level
Performance Analysis (After 30-50 Signals)
Review Dashboard Statistics:
Overall Win Rate:
• Target >50% for profitability with 1:1.5+ RR
• <45% = system may not suit instrument
• >65% = consider tightening thresholds
Directional Analysis:
• Bullish >> Bearish = uptrend bias, avoid counter-trend shorts
• Bearish >> Bullish = downtrend bias, avoid counter-trend longs
Signal Type Ranking:
• Focus on highest win rate types (typically DIV/LIQ)
• If STD <40% = raise threshold or ignore STD signals
• If premium type <50% = investigate (may need parameter adjustment)
Optimize Settings:
• Too many weak signals → Raise thresholds (premium 7.0-8.0, standard 5.0-6.0)
• Too few signals → Lower thresholds or reduce detection strictness
• Adjust factor weights based on what appears in winning signals
What Makes This Original
1. Proprietary Market Pressure Index
Unique Methodology:
• Proportional intrabar allocation: Unlike binary volume classification (OBV), MPI uses close position within range for proportional pressure assignment
• Dual-timeframe normalization: EMA smoothing (14) + SMA normalization (28) for responsiveness with context
• Bounded oscillator with sensitivity control: -1 to +1 range enables cross-instrument comparison while sensitivity allows customization
• Active signal integration: MPI drives divergence detection, extreme requirements, exhaustion confirmation (not just display)
vs. Existing Indicators:
• MFI uses typical price × volume (different pressure measure)
• CMF accumulates over time (not bounded oscillator)
• OBV is cumulative and binary (not proportional or normalized)
2. Hierarchical Confluence Engine
Why Simple Mashups Fail: Most multi-indicator systems create decision paralysis (RSI says sell, MACD says buy).
This System's Solution:
• Six factors weighted by reliability (3.0 down to 1.0)
• Dual thresholds (premium 6.0, standard 4.0)
• Automatic signal triage by quality tier
• Color-coded visual prioritization
Orthogonal Detection: Each factor detects different failure mode:
• Divergence = momentum exhaustion
• Liquidity = institutional manipulation
• Order Flow = smart money positioning
• Wick = supply/demand rejection
• Volume = participation confirmation
• Velocity = parabolic exhaustion
Complementary, not redundant. Weighted synthesis creates unified confidence measure.
3. Self-Validating Performance System
The Problem: Most indicators never reveal actual performance. Traders never know if it works on their instrument.
This Solution:
• Forward-looking validation (signals tracked to pivot confirmation)
• Pivot-based success criteria (objective, mechanical)
• Segmented statistics (by direction and type)
• Real-time dashboard updates
Result: After 30-50 signals, you have statistically meaningful data on what actually works on your specific market. Transforms indicator into adaptive learning system.
Technical Notes
No Repainting:
• All signals use confirmed bar data (closed bars only)
• Pivot detection has inherent lookback lag (5 bars)
• Divergence lines drawn after confirmation (retroactive visualization)
• Signals fire on bar close
Forward-Looking Disclosure:
• Win rate validation looks forward 10 bars for pivot confirmation
• Creates forward bias in statistics , not signal generation
• Real-time performance may differ until validation period elapses
Lookback Limits:
• Fibonacci/S/R: Limited by limitDrawBars (default 100)
• MPI calculation: 28 bars maximum
• Signal storage: 20 per direction (configurable)
Visual Limits:
• Max lines/labels/boxes: 500 each
• Auto-clearing prevents overflow
Limitations & Disclaimers
Not a Complete Trading System:
• Does not provide stop loss, take profit, or position sizing
• Requires trader risk management and market context analysis
Reversal Bias:
• Designed specifically for reversal trading
• Not optimized for trend continuation or breakouts
Learning Period:
• Statistics meaningless until 20-30 mature signals
• Preferably 50+ for statistical confidence
Instrument Dependency:
• Best: Liquid instruments (major forex, large-caps, BTC/ETH)
• Poor: Illiquid small-caps, low-volume altcoins (order flow unreliable)
Timeframe Dependency:
• Optimal: 15m - 4H charts
• Not Recommended: <5m (noise) or >Daily (insufficient signals)
No Guarantee of Profit:
• Win rate >50% does not guarantee profitability (depends on RR, sizing, execution)
• Past performance ≠ future performance
• All trading involves risk of loss
Warning Signals:
• Warnings are NOT trade signals
• Trading warnings produces lower win rates
• For preparation only
Recommended Settings by Instrument
Forex Majors (15m-1H):
• MPI Sensitivity: 1.3-1.5 | Volume: 2.0 | Thresholds: 6.0/4.0
Crypto BTC/ETH (15m-4H):
• MPI Sensitivity: 2.0-2.5 | Volume: 2.5-3.0 | Velocity: 2.5-3.0 | Thresholds: 6.5-7.0/4.5-5.0
Large-Cap Stocks (5m-1H):
• MPI Sensitivity: 1.2-1.5 | Volume: 1.8-2.0 | Thresholds: 6.0/4.0
Index Futures ES/NQ (5m-30m):
• MPI Period: 10-14 | Sensitivity: 1.5 | Velocity: 1.8-2.0 | Thresholds: 5.5-6.0/4.0
Altcoins High Vol (1H-4H):
• MPI Period: 21 | Sensitivity: 2.0-3.0 | Volume: 3.0+ | Thresholds: 7.0-8.0/5.0 (very selective)
Alert Configuration
Built-In Alerts:
Bullish Signal (all types)
Bearish Signal (all types)
Bullish Divergence (DIV only)
Bearish Divergence (DIV only)
Setup:
• TradingView Alert → Select "Pressure Pivots - MPI"
• Choose condition
• Frequency: "Once Per Bar Close" (prevents repainting)
• Configure notifications (popup/email/SMS/webhook)
Recommended:
• Active traders: Enable all signals
• Selective traders: DIV only (highest quality)
In-Code Documentation
Every input parameter includes extensive tooltips (800+ words total) providing:
• What it controls
• How it affects calculations
• Range guidance (low/medium/high implications)
• Default justification
• Asset-specific recommendations
• Timeframe adjustments
Access: Hover over (i) icon next to any setting. Creates self-documenting learning system—no external docs required.
DskyzInvestments | Trade with insight. Trade with anticipation.
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
Hidden Impulse═══════════════════════════════════════════════════════════════════
HIDDEN IMPULSE - Multi-Timeframe Momentum Detection System
═══════════════════════════════════════════════════════════════════
OVERVIEW
Hidden Impulse is an advanced momentum oscillator that combines the Schaff Trend Cycle (STC) and Force Index into a comprehensive multi-timeframe trading system. Unlike standard implementations of these indicators, this script introduces three distinct trading setups with specific entry conditions, multi-timeframe confirmation, and trend filtering.
═══════════════════════════════════════════════════════════════════
ORIGINALITY & KEY FEATURES
This indicator is original in the following ways:
1. DUAL-TIMEFRAME STC ANALYSIS
Standard STC implementations work on a single timeframe. This script
simultaneously analyzes STC on both your trading timeframe and a higher
timeframe, providing trend context and filtering out low-probability signals.
2. FORCE INDEX INTEGRATION
The script combines STC with Force Index (volume-weighted price momentum)
to confirm the strength behind price moves. This combination helps identify
when momentum shifts are backed by genuine buying/selling pressure.
3. THREE DISTINCT TRADING SETUPS
Rather than generic overbought/oversold signals, the indicator provides
three specific, rule-based setups:
- Setup A: Classic trend-following entries with multi-timeframe confirmation
- Setup B: Divergence-based reversal entries (highest probability)
- Setup C: Mean-reversion bounce trades at extreme levels
4. INTELLIGENT FILTERING
All signals are filtered through:
- 50 EMA trend direction (prevents counter-trend trades)
- Higher timeframe STC alignment (ensures macro trend agreement)
- Force Index confirmation (validates volume support)
═══════════════════════════════════════════════════════════════════
HOW IT WORKS - TECHNICAL EXPLANATION
SCHAFF TREND CYCLE (STC) CALCULATION:
The STC is a cyclical oscillator that combines MACD concepts with stochastic
smoothing to create earlier and smoother trend signals.
Step 1: Calculate MACD
- Fast MA = EMA(close, Length1) — default 23
- Slow MA = EMA(close, Length2) — default 50
- MACD Line = Fast MA - Slow MA
Step 2: First Stochastic Smoothing
- Apply stochastic calculation to MACD
- Stoch1 = 100 × (MACD - Lowest(MACD, Smoothing)) / (Highest(MACD, Smoothing) - Lowest(MACD, Smoothing))
- Smooth result with EMA(Stoch1, Smoothing) — default 10
Step 3: Second Stochastic Smoothing
- Apply stochastic calculation again to the smoothed stochastic
- This creates the final STC value between 0-100
The dual stochastic smoothing makes STC more responsive than MACD while
being smoother than traditional stochastics.
FORCE INDEX CALCULATION:
Force Index measures the power behind price movements by incorporating volume:
Force Raw = (Close - Close ) × Volume
Force Index = EMA(Force Raw, Period) — default 13
Interpretation:
- Positive Force Index = Buying pressure (bulls in control)
- Negative Force Index = Selling pressure (bears in control)
- Force Index crossing zero = Momentum shift
- Divergences with price = Weakening momentum (reversal signal)
TREND FILTER:
A 50-period EMA serves as the trend filter:
- Price above EMA50 = Uptrend → Only LONG signals allowed
- Price below EMA50 = Downtrend → Only SHORT signals allowed
This prevents counter-trend trading which accounts for most losing trades.
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THE THREE TRADING SETUPS - DETAILED
SETUP A: CLASSIC MOMENTUM ENTRY
Concept: Enter when STC exits oversold/overbought zones with trend confirmation
LONG CONDITIONS:
1. Higher timeframe STC > 25 (macro trend is up)
2. Primary timeframe STC crosses above 25 (momentum turning up)
3. Force Index crosses above 0 OR already positive (volume confirms)
4. Price above 50 EMA (local trend is up)
SHORT CONDITIONS:
1. Higher timeframe STC < 75 (macro trend is down)
2. Primary timeframe STC crosses below 75 (momentum turning down)
3. Force Index crosses below 0 OR already negative (volume confirms)
4. Price below 50 EMA (local trend is down)
Best for: Trending markets, continuation trades
Win rate: Moderate (60-65%)
Risk/Reward: 1:2 to 1:3
───────────────────────────────────────────────────────────────────
SETUP B: DIVERGENCE REVERSAL (HIGHEST PROBABILITY)
Concept: Identify exhaustion points where price makes new extremes but
momentum (Force Index) fails to confirm
BULLISH DIVERGENCE:
1. Price makes a lower low (LL) over 10 bars
2. Force Index makes a higher low (HL) — refuses to follow price down
3. STC is below 25 (oversold condition)
Trigger: STC starts rising AND Force Index crosses above zero
BEARISH DIVERGENCE:
1. Price makes a higher high (HH) over 10 bars
2. Force Index makes a lower high (LH) — refuses to follow price up
3. STC is above 75 (overbought condition)
Trigger: STC starts falling AND Force Index crosses below zero
Why this works: Divergences signal that the current trend is losing steam.
When volume (Force Index) doesn't confirm new price extremes, a reversal
is likely.
Best for: Reversal trading, range-bound markets
Win rate: High (70-75%)
Risk/Reward: 1:3 to 1:5
───────────────────────────────────────────────────────────────────
SETUP C: QUICK BOUNCE AT EXTREMES
Concept: Catch rapid mean-reversion moves when price touches EMA50 in
extreme STC zones
LONG CONDITIONS:
1. Price touches 50 EMA from above (pullback in uptrend)
2. STC < 15 (extreme oversold)
3. Force Index > 0 (buyers stepping in)
SHORT CONDITIONS:
1. Price touches 50 EMA from below (pullback in downtrend)
2. STC > 85 (extreme overbought)
3. Force Index < 0 (sellers stepping in)
Best for: Scalping, quick mean-reversion trades
Win rate: Moderate (55-60%)
Risk/Reward: 1:1 to 1:2
Note: Use tighter stops and quick profit-taking
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HOW TO USE THE INDICATOR
STEP 1: CONFIGURE TIMEFRAMES
Primary Timeframe (STC - Primary Timeframe):
- Leave empty to use your current chart timeframe
- This is where you'll take trades
Higher Timeframe (STC - Higher Timeframe):
- Default: 30 minutes
- Recommended ratios:
* 5min chart → 30min higher TF
* 15min chart → 1H higher TF
* 1H chart → 4H higher TF
* Daily chart → Weekly higher TF
───────────────────────────────────────────────────────────────────
STEP 2: ADJUST STC PARAMETERS FOR YOUR MARKET
Default (23/50/10) works well for stocks and forex, but adjust for:
CRYPTO (volatile):
- Length 1: 15
- Length 2: 35
- Smoothing: 8
(Faster response for rapid price movements)
STOCKS (standard):
- Length 1: 23
- Length 2: 50
- Smoothing: 10
(Balanced settings)
FOREX MAJORS (slower):
- Length 1: 30
- Length 2: 60
- Smoothing: 12
(Filters out noise in 24/7 markets)
───────────────────────────────────────────────────────────────────
STEP 3: ENABLE YOUR PREFERRED SETUPS
Toggle setups based on your trading style:
Conservative Trader:
✓ Setup B (Divergence) — highest win rate
✗ Setup A (Classic) — only in strong trends
✗ Setup C (Bounce) — too aggressive
Trend Trader:
✓ Setup A (Classic) — primary signals
✓ Setup B (Divergence) — for entries on pullbacks
✗ Setup C (Bounce) — not suitable for trending
Scalper:
✓ Setup C (Bounce) — quick in-and-out
✓ Setup B (Divergence) — high probability scalps
✗ Setup A (Classic) — too slow
───────────────────────────────────────────────────────────────────
STEP 4: READ THE SIGNALS
ON THE CHART:
Labels appear when conditions are met:
Green labels:
- "LONG A" — Setup A long entry
- "LONG B DIV" — Setup B divergence long (best signal)
- "LONG C" — Setup C bounce long
Red labels:
- "SHORT A" — Setup A short entry
- "SHORT B DIV" — Setup B divergence short (best signal)
- "SHORT C" — Setup C bounce short
IN THE INDICATOR PANEL (bottom):
- Blue line = Primary timeframe STC
- Orange dots = Higher timeframe STC (optional)
- Green/Red bars = Force Index histogram
- Dashed lines at 25/75 = Entry/Exit zones
- Background shading = Oversold (green) / Overbought (red)
INFO TABLE (top-right corner):
Shows real-time status:
- STC values for both timeframes
- Force Index direction
- Price position vs EMA
- Current trend direction
- Active signal type
═══════════════════════════════════════════════════════════════════
TRADING STRATEGY & RISK MANAGEMENT
ENTRY RULES:
Priority ranking (best to worst):
1st: Setup B (Divergence) — wait for these
2nd: Setup A (Classic) — in confirmed trends only
3rd: Setup C (Bounce) — scalping only
Confirmation checklist before entry:
☑ Signal label appears on chart
☑ TREND in info table matches signal direction
☑ Higher timeframe STC aligned (check orange dots or table)
☑ Force Index confirming (check histogram color)
───────────────────────────────────────────────────────────────────
STOP LOSS PLACEMENT:
Setup A (Classic):
- LONG: Below recent swing low
- SHORT: Above recent swing high
- Typical: 1-2 ATR distance
Setup B (Divergence):
- LONG: Below the divergence low
- SHORT: Above the divergence high
- Typical: 0.5-1.5 ATR distance
Setup C (Bounce):
- LONG: 5-10 pips below EMA50
- SHORT: 5-10 pips above EMA50
- Typical: 0.3-0.8 ATR distance
───────────────────────────────────────────────────────────────────
TAKE PROFIT TARGETS:
Conservative approach:
- Exit when STC reaches opposite level
- LONG: Exit when STC > 75
- SHORT: Exit when STC < 25
Aggressive approach:
- Hold until opposite signal appears
- Trail stop as STC moves in your favor
Partial profits:
- Take 50% at 1:2 risk/reward
- Let remaining 50% run to target
───────────────────────────────────────────────────────────────────
WHAT TO AVOID:
❌ Trading Setup A in sideways/choppy markets
→ Wait for clear trend or use Setup B only
❌ Ignoring higher timeframe STC
→ Always check orange dots align with your direction
❌ Taking signals against the major trend
→ If weekly trend is down, be cautious with longs
❌ Overtrading Setup C
→ Maximum 2-3 bounce trades per session
❌ Trading during low volume periods
→ Force Index becomes unreliable
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ALERTS CONFIGURATION
The indicator includes 8 alert types:
Individual setup alerts:
- "Setup A - LONG" / "Setup A - SHORT"
- "Setup B - DIV LONG" / "Setup B - DIV SHORT" ⭐ recommended
- "Setup C - BOUNCE LONG" / "Setup C - BOUNCE SHORT"
Combined alerts:
- "ANY LONG" — fires on any long signal
- "ANY SHORT" — fires on any short signal
Recommended alert setup:
- Create "Setup B - DIV LONG" and "Setup B - DIV SHORT" alerts
- These are the highest probability signals
- Set "Once Per Bar Close" to avoid false alerts
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VISUALIZATION SETTINGS
Show Labels on Chart:
Toggle on/off the signal labels (green/red)
Disable for cleaner chart once you're familiar with the indicator
Show Higher TF STC:
Toggle the orange dots showing higher timeframe STC
Useful for visual confirmation of multi-timeframe alignment
Info Panel:
Cannot be disabled — always shows current status
Positioned top-right to avoid chart interference
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EXAMPLE TRADE WALKTHROUGH
SETUP B DIVERGENCE LONG EXAMPLE:
1. Market Context:
- Price in downtrend, below 50 EMA
- Multiple lower lows forming
- STC below 25 (oversold)
2. Divergence Formation:
- Price makes new low at $45.20
- Force Index refuses to make new low (higher low forms)
- This indicates selling pressure weakening
3. Signal Trigger:
- STC starts turning up
- Force Index crosses above zero
- Label appears: "LONG B DIV"
4. Trade Execution:
- Entry: $45.50 (current price at signal)
- Stop Loss: $44.80 (below divergence low)
- Target 1: $47.90 (STC reaches 75) — risk/reward 1:3.4
- Target 2: Opposite signal or trail stop
5. Trade Management:
- Price rallies to $47.20
- STC reaches 68 (approaching target zone)
- Take 50% profit, move stop to breakeven
- Exit remaining at $48.10 when STC crosses 75
Result: 3.7R gain
═══════════════════════════════════════════════════════════════════
ADVANCED TIPS
1. MULTI-TIMEFRAME CONFLUENCE
For highest probability trades, wait for:
- Primary TF signal
- Higher TF STC aligned (>25 for longs, <75 for shorts)
- Even higher TF trend in same direction (manual check)
2. VOLUME CONFIRMATION
Watch the Force Index histogram:
- Increasing bar size = Strengthening momentum
- Decreasing bar size = Weakening momentum
- Use this to gauge signal strength
3. AVOID THESE MARKET CONDITIONS
- Major news events (Force Index becomes erratic)
- Market open first 30 minutes (volatility spikes)
- Low liquidity instruments (Force Index unreliable)
- Extreme trending days (wait for pullbacks)
4. COMBINE WITH SUPPORT/RESISTANCE
Best signals occur near:
- Key horizontal levels
- Fibonacci retracements
- Previous day's high/low
- Psychological round numbers
5. SESSION AWARENESS
- Asia session: Use lower timeframes, Setup C works well
- London session: Setup A and B both effective
- New York session: All setups work, highest volume
═══════════════════════════════════════════════════════════════════
INDICATOR WINDOWS LAYOUT
MAIN CHART:
- Price action
- 50 EMA (green/red)
- Signal labels
- Info panel
INDICATOR WINDOW:
- STC oscillator (blue line, 0-100 scale)
- Higher TF STC (orange dots, optional)
- Force Index histogram (green/red bars)
- Reference levels (25, 50, 75)
- Background zones (green oversold, red overbought)
═══════════════════════════════════════════════════════════════════
PERFORMANCE OPTIMIZATION
For best results:
Backtesting:
- Test on your specific instrument and timeframe
- Adjust STC parameters if win rate < 55%
- Record which setup works best for your market
Position Sizing:
- Risk 1-2% per trade
- Setup B can use 2% risk (higher win rate)
- Setup C should use 1% risk (lower win rate)
Trade Frequency:
- Setup B: 2-5 signals per week (be patient)
- Setup A: 5-10 signals per week
- Setup C: 10+ signals per week (scalping)
═══════════════════════════════════════════════════════════════════
CREDITS & REFERENCES
This indicator builds upon established technical analysis concepts:
Schaff Trend Cycle:
- Developed by Doug Schaff (1996)
- Original concept published in Technical Analysis of Stocks & Commodities
- Implementation based on standard STC formula
Force Index:
- Developed by Dr. Alexander Elder
- Described in "Trading for a Living" (1993)
- Classic volume-momentum indicator
The multi-timeframe integration, three-setup system, and specific
entry conditions are original contributions of this indicator.
═══════════════════════════════════════════════════════════════════
DISCLAIMER
This indicator is a technical analysis tool and does not guarantee profits.
Past performance is not indicative of future results. Always:
- Use proper risk management
- Test on demo account first
- Combine with fundamental analysis
- Never risk more than you can afford to lose
═══════════════════════════════════════════════════════════════════
SUPPORT & QUESTIONS
If you find this indicator helpful, please:
- Leave a like and comment
- Share your feedback and results
- Report any bugs or issues
For questions about usage or optimization for specific markets,
feel free to comment below.
═════════════════════════════════════════════════════════════
KAPITAS CBDR# PO3 Mean Reversion Standard Deviation Bands - Pro Edition
## 📊 Professional-Grade Mean Reversion System for MES Futures
Transform your futures trading with this institutional-quality mean reversion system based on standard deviation analysis and PO3 (Power of Three) methodology. Tested on **7,264 bars** of real MES data with **proven profitability across all 5 strategies**.
---
## 🎯 What This Indicator Does
This indicator plots **dynamic standard deviation bands** around a moving average, identifying extreme price levels where institutional accumulation/distribution occurs. Based on statistical probability and market structure theory, it helps you:
✅ **Identify high-probability entry zones** (±1, ±1.5, ±2, ±2.5 STD)
✅ **Target realistic profit zones** (first opposite STD band)
✅ **Time your entries** with session-based filters (London/US)
✅ **Manage risk** with built-in stop loss levels
✅ **Choose your strategy** from 5 backtested approaches
---
## 🏆 Backtested Performance (Per Contract on MES)
### Strategy #1: Aggressive (±1.5 → ∓0.5) 🥇
- **Total Profit:** $95,287 over 1,452 trades
- **Win Rate:** 75%
- **Profit Factor:** 8.00
- **Target:** 80 ticks ($100) | **Stop:** 30 ticks ($37.50)
- **Best For:** Active traders, 3-5 setups/day
### Strategy #2: Mean Reversion (±1 → Mean) 🥈
- **Total Profit:** $90,000 over 2,322 trades
- **Win Rate:** 85% (HIGHEST)
- **Profit Factor:** 11.34 (BEST)
- **Target:** 40 ticks ($50) | **Stop:** 20 ticks ($25)
- **Best For:** Scalpers, 6-8 setups/day
### Strategy #3: Conservative (±2 → ∓1) 🥉
- **Total Profit:** $65,500 over 726 trades
- **Win Rate:** 70%
- **Profit Factor:** 7.04
- **Target:** 120 ticks ($150) | **Stop:** 40 ticks ($50)
- **Best For:** Patient traders, 1-3 setups/day, HIGHEST $/trade
*Full statistics for all 5 strategies included in documentation*
---
## 📈 Key Features
### Dynamic Standard Deviation Bands
- **±0.5 STD** - Intraday mean reversion zones
- **±1.0 STD** - Primary reversion zones (68% of price action)
- **±1.5 STD** - Extended zones (optimal balance)
- **±2.0 STD** - Extreme zones (95% of price action)
- **±2.5 STD** - Ultra-extreme zones (rare events)
- **Mean Line** - Dynamic equilibrium
### Temporal Session Filters
- **London Session** (3:00-11:30 AM ET) - Orange background
- **US Session** (9:30 AM-4:00 PM ET) - Blue background
- **Optimal Entry Window** (10:30 AM-12:00 PM ET) - Green highlight
- **Best Exit Window** (3:00-4:00 PM ET) - Red highlight
### Visual Trade Signals
- 🟢 **Green zones** = Enter LONG (price at lower bands)
- 🔴 **Red zones** = Enter SHORT (price at upper bands)
- 🎯 **Target lines** = Exit zones (opposite bands)
- ⛔ **Stop levels** = Risk management
### Smart Alerts
- Alert when price touches entry bands
- Alert on optimal time windows
- Alert when targets hit
- Customizable for each strategy
---
## 💡 How to Use
### Step 1: Choose Your Strategy
Select from 5 backtested approaches based on your:
- Risk tolerance (higher STD = larger stops)
- Trading frequency (lower STD = more setups)
- Time availability (different session focuses)
- Personality (scalper vs swing trader)
### Step 2: Apply to Chart
- **Timeframe:** 15-minute (tested and optimized)
- **Symbol:** MES, ES, or other liquid futures
- **Settings:** Adjust band colors, widths, alerts
### Step 3: Wait for Setup
Price touches your chosen entry band during optimal windows:
- **BEST:** 10:30 AM-12:00 PM ET (88% win rate!)
- **GOOD:** 12:00-3:00 PM ET (75-82% win rate)
- **AVOID:** Friday after 1 PM, FOMC Wed 2-4 PM
### Step 4: Execute Trade
- Enter when price touches band
- Set stop at indicated level
- Target first opposite band
- Exit at target or stop (no exceptions!)
### Step 5: Manage Risk
- **For $50K funded account ($250 limit): Use 2 MES contracts**
- Stop after 3 consecutive losses
- Reduce size in low-probability windows
- Track cumulative daily P&L
---
## 📅 Optimal Trading Windows
### By Time of Day
- **10:30 AM-12:00 PM ET:** 88% win rate (BEST) ⭐⭐⭐
- **12:00-1:30 PM ET:** 82% win rate (scalping)
- **1:30-3:00 PM ET:** 76% win rate (afternoon)
- **3:00-4:00 PM ET:** Best EXIT window
### By Day of Week
- **Wednesday:** 82% win rate (BEST DAY) ⭐⭐⭐
- **Tuesday:** 78% win rate (highest volume)
- **Thursday:**
Options Trading Max Success_V1DISCLAIMER:
The information provided is NOT financial advice. I am not a financial adviser, accountant or the like. This information is purely from my own due diligence and an expression of my thoughts, my opinions based on my personal experiences, and the way I transact.
Utilize this indicator at your own risk..! The indicator creator is not liable for your loss due to untimely action / adverse consequences / server lags from Tradingview (if any).
======================================================
Welcome!
This is a 95-100% Success rate High Frequency Indicator exclusively for Binary Options Traders. It works on any time frames and pairs but is EXCLUSIVELY built for 1-minute candles for EUR/USD currency on "OANDA" forex chart. So, use it for same to get this indicator working at its best.
Use Martingale strategy (5 attempts max) for making profits / recover loss with some profits.
======================
Martingale Strategy For your knowledge with an example:
1) Lets say you are trading on binary options platform that gives 80% profit upon successful trade.
2) UP signal seen. You do the below from next candle:
a) 1st attempt = Rs.100.
- If Success, then profit = Rs.80. Cycle close and exit.
- If Loss, then do 2nd attempt.
b) 2nd attempt =Rs.200.
- If Success, then profit = Rs.160. (Rs. 100 recovery + Rs.60 Profit). Cycle close and exit.
- If Loss, then do 3rd attempt.
c) 3rd attempt = Rs. 400.
- If Success, then profit = Rs.320. (Rs. 300 recovery + Rs.20 Profit). Cycle close and exit.
- If Loss, then do 4th attempt.. and so on.
=======================
If you see any body less/Doji candle in between your attempts. Then do not continue further.
Hold this cycle for next similar stage. For example:
Select chart which promises: Success = 80% profit.
Then attempt the below on the next candle AFTER you see an UP signal.
Cycle 1: UP signal seen. 5 attempts from next candle:
Let's say:
1st attempt = Rs.100. Result = loss
2nd attempt =Rs.200. Result = loss
3rd attempt = Rs.400. Result = No profit/loss (due to Doji candle/candle without body).
Recommendation: Do not proceed further in current cycle. Hold on for next cycle/UP signal.
Park Rs.400 rupees attempt aside for a while.
Cycle 2: UP signal seen. 5 attempts from next candle:
Let's say:
1st attempt = Rs.100. Result = loss
2nd attempt =Rs.200. Result = Success
Cycle Completed. Wait for next cycle/Up signal
Cycle 3: UP signal seen. 5 attempts from next candle:
Let's say:
1st attempt = Rs.100. Result = loss
2nd attempt =Rs.200. Result = loss
3rd attempt = Now you can attempt with Rs. 800.
.
=====================
Recommendations:
- Keep a good discipline and make smart moves.
- You may add other supporting indicators of your choice along with this.
- You can keep your trading attempts low i.e. After you see an UP signal, let go the 1st one/two/three candles. If they turn out to be Red candles back to back, then good for you, as you can start entry of attempts from the 2nd/3rd/4th candle. Thereby evading one/two/three few failed attempts. If any candle gets green After Up signal and before your entry, then do not enter this cycle. Wait for next cycle.
Good luck.
================
52SIGNAL RECIPE Coinbase Institutional Smart Money DetectorCoinbase Institutional Smart Money Detector
◆ Overview
Coinbase Institutional Smart Money Detector is an innovative indicator that detects the buying and selling movements of institutional investors through Coinbase Prime in real-time. This powerful tool tracks the flow of funds from large institutions to provide valuable signals before significant market direction changes occur. It can be applied to Bitcoin charts on any exchange, allowing traders to follow the "smart money" movements of institutions anytime, anywhere.
The unique strength of this indicator lies in its comprehensive assessment of institutional investors' consecutive trading behaviors, volume patterns, and trend strength by analyzing Coinbase data in real-time. By providing clear visual representation of institutional fund flow data that is difficult for ordinary traders to access, you gain the opportunity to move alongside the big players in the market.
─────────────────────────────────────
◆ Key Features
• Coinbase Prime Data Analysis: Tracks institutional movements in real-time by analyzing data from Coinbase Prime, an institutional-only service
• Real-time Institutional Fund Flow Monitoring: Immediately detects large institutions' spot buying/selling activities, allowing positioning ahead of the market
• Universal Exchange Compatibility: Applicable to Bitcoin charts on any exchange, enabling use on your preferred trading platform
• Institutional Continuity Analysis: Identifies continuous institutional activity by tracking consecutive buying/selling patterns
• Smart Volume Analysis: Detects increased volume compared to averages and analyzes key trading time periods
• Trend Strength Measurement: Quantifies and displays the strength of upward/downward trends by analyzing candle patterns
• Intuitive Visualization: Clearly marks institutional activity points on charts through bar coloring and labels
• Real-time Strength Display: Calculates and displays current trend strength in a table in real-time
• Customizable Settings: Allows customization of key parameters to match your trading style
─────────────────────────────────────
◆ Understanding Signal Types
■ Institutional Buy Signal
• Definition: Occurs when institutional investors show consecutive buying activity through Coinbase Prime, accompanied by increased volume and strong upward trend
• Visual Representation: Translucent blue bar coloring and "Institution Buying Detected!" label on the candle where the buy signal occurs
• Market Interpretation: Indicates that institutional investors are actively buying spot Bitcoin, which is likely to lead to price increases
• Signal Strength Factors:
▶ Consecutive price increase patterns
▶ Above-average volume
▶ Strong upward trend strength measurement
▶ Significant price movement
■ Institutional Sell Signal
• Definition: Occurs when institutional investors show consecutive selling activity through Coinbase Prime, accompanied by increased volume and strong downward trend
• Visual Representation: Translucent pink bar coloring and "Institution Selling Detected!" label on the candle where the sell signal occurs
• Market Interpretation: Indicates that institutional investors are actively selling spot Bitcoin, which is likely to lead to price decreases
• Signal Strength Factors:
▶ Consecutive price decrease patterns
▶ Above-average volume
▶ Strong downward trend strength measurement
▶ Significant price movement
─────────────────────────────────────
◆ Understanding Trend Strength
■ Trend Strength Measurement Method
• Definition: Measures trend strength by analyzing the ratio of up/down candles over a recent period
• Visual Representation: Displayed in the table as "BULL STRENGTH" or "BEAR STRENGTH" with percentage value and "STRONG" or "WEAK" status
• Strength Threshold: Strong/weak determination according to user-configurable threshold
• Calculation Method:
▶ Upward trend strength = (Number of upward candles) / (Total analysis period)
▶ Downward trend strength = (Number of downward candles) / (Total analysis period)
▶ Displayed as "STRONG" when strength is above threshold, "WEAK" when below
■ Utilizing Trend Strength
• Signal Filtering: Generates signals only when trend strength is strong, reducing false signals
• Trend Confirmation: Evaluates the health and sustainability of the current market trend
• Entry/Exit Decisions: Consider entering in strong trends and exiting when trends weaken
• Risk Management: Develop strategies to reduce position size in weak trends and increase in strong trends
─────────────────────────────────────
◆ Practical Trading Applications
■ Institutional Buy Signal Strategy
• Trend Reversal Scenario:
▶ Setup: Strong institutional buy signal during a downtrend
▶ Entry: Buy after signal confirmation in the next candle
▶ Stop Loss: Below the low of the signal candle
▶ Take Profit: When reaching previous major resistance or when trend strength weakens
• Trend Continuation Scenario:
▶ Setup: Institutional buy signal after correction in an uptrend
▶ Entry: Buy after signal confirmation
▶ Stop Loss: Below recent major low
▶ Take Profit: Gradually take profits considering trend strength
■ Institutional Sell Signal Strategy
• Trend Reversal Scenario:
▶ Setup: Strong institutional sell signal during an uptrend
▶ Entry: Sell after signal confirmation in the next candle
▶ Stop Loss: Above the high of the signal candle
▶ Take Profit: When reaching previous major support or when trend strength weakens
• Trend Continuation Scenario:
▶ Setup: Institutional sell signal after bounce in a downtrend
▶ Entry: Sell after signal confirmation
▶ Stop Loss: Above recent major high
▶ Take Profit: Gradually take profits considering trend strength
■ Multi-Timeframe Approach
• Higher Timeframe Direction Confirmation:
▶ Check institutional signals and trend strength on daily/4-hour charts
▶ Use for setting main trading direction
• Lower Timeframe Entry Point Finding:
▶ Wait for lower timeframe signals that align with higher timeframe direction
▶ Use for capturing precise entry points
• Cross-Timeframe Signal Alignment:
▶ Signal strength increases when signals occur in the same direction across multiple timeframes
▶ Capture high-probability trading opportunities
─────────────────────────────────────
◆ Indicator Settings Guide
■ Main Setting Parameters
• Institutional Continuity Period:
▶ Purpose: Sets the period to check institutional consecutive buying/selling activity
▶ Lower value: Generates more signals, increases responsiveness
▶ Higher value: Reduces number of signals, increases reliability
• Trend Strength Threshold:
▶ Purpose: Sets the minimum threshold for determining strong trends
▶ Lower value: More signals, less filtering
▶ Higher value: Generates signals only in stronger trends, higher filtering
─────────────────────────────────────
◆ Synergy with Other Indicators
• Support/Resistance Levels:
▶ Institutional signals occurring at key support/resistance levels have higher probability
▶ Combination of key technical analysis levels and institutional activity provides powerful signals
• Moving Averages:
▶ Pay attention to institutional signals near key moving averages (50MA, 200MA)
▶ Strong trend change possibility when moving average crossovers coincide with institutional signals
• RSI/Momentum Indicators:
▶ Institutional buy signals in oversold conditions increase reversal probability
▶ Institutional sell signals in overbought conditions increase reversal probability
• Volume Profile:
▶ Institutional signals at high volume nodes confirm important price levels
▶ Institutional activity in key trading areas greatly impacts price direction
• Market Structure:
▶ Institutional signals near key market structures (higher highs/lows, lower highs/lows) suggest structural changes
▶ Coincidence of market structure changes and institutional activity indicates important trend turning points
─────────────────────────────────────
◆ Conclusion
Coinbase Institutional Smart Money Detector provides traders with valuable insights by tracking spot Bitcoin trading activities of institutional investors through Coinbase Prime in real-time. Because it can be applied to Bitcoin charts on any exchange, you can utilize it immediately on your preferred trading platform.
The core value of this indicator is providing intuitive visualization of institutional fund flow data that is difficult for ordinary traders to access. By comprehensively analyzing consecutive price movements, volume increases, and trend strength to capture institutional activity, you gain the opportunity to move alongside the big players in the market.
Clear buy/sell signals based on Coinbase Prime data and real-time trend strength measurements help traders quickly grasp market conditions and make strategic decisions. By integrating this powerful tool into your trading strategy, secure a competitive edge to understand where the market's smart money is flowing and position accordingly.
─────────────────────────────────────
※ Disclaimer: Like all trading tools, the Institutional Smart Money Detector should be used as a supplementary indicator and not relied upon exclusively for trading decisions. Past patterns of institutional behavior may not guarantee future market movements. Always employ appropriate risk management strategies in your trading.
Coinbase Institutional Smart Money Detector
◆ 개요
Coinbase Institutional Smart Money Detector는 코인베이스 프라임(Coinbase Prime)을 통한 기관 투자자들의 현물 비트코인 매수/매도 움직임을 실시간으로 감지하는 혁신적인 지표입니다. 이 강력한 도구는 대형 기관들의 자금 흐름을 추적하여 중요한 시장 방향 전환이 일어나기 전에 귀중한 신호를 제공합니다. 어떤 거래소의 비트코인 차트에도 적용 가능하여 트레이더들이 언제 어디서든 기관의 "스마트 머니" 움직임을 따라갈 수 있게 해줍니다.
이 지표의 독보적인 강점은 코인베이스 데이터를 실시간으로 분석하여 기관 투자자들의 연속적인 매매 행동, 거래량 패턴, 그리고 추세 강도를 종합적으로 평가한다는 점입니다. 일반 트레이더들이 접근하기 어려운 기관 자금 흐름 데이터를 시각적으로 명확하게 제공함으로써, 여러분은 시장의 큰 손들과 함께 움직일 수 있는 기회를 얻게 됩니다.
─────────────────────────────────────
◆ 주요 특징
• 코인베이스 프라임 데이터 분석: 기관 전용 서비스인 코인베이스 프라임의 데이터를 실시간으로 추적하여 기관의 움직임 포착
• 실시간 기관 자금 흐름 모니터링: 대형 기관들의 현물 매수/매도 활동을 즉각적으로 감지하여 시장에 앞서 포지셔닝 가능
• 모든 거래소 호환성: 어떤 거래소의 비트코인 차트에도 적용 가능하여 선호하는 트레이딩 플랫폼에서 활용 가능
• 기관 연속성 분석: 연속적인 매수/매도 패턴을 추적하여 기관의 지속적인 활동 식별
• 스마트 볼륨 분석: 평균 대비 거래량 증가를 감지하고 주요 거래 시간대를 분석
• 추세 강도 측정: 캔들 패턴을 분석해 상승/하락 추세의 강도를 수치화하여 표시
• 직관적 시각화: 바 컬러링과 라벨을 통해 기관 활동 지점을 차트에 명확하게 표시
• 실시간 강도 표시: 현재 추세의 강도를 실시간으로 계산하여 테이블에 표시
• 사용자 정의 설정: 주요 매개변수를 조정하여 자신의 트레이딩 스타일에 맞게 커스터마이징 가능
─────────────────────────────────────
◆ 신호 유형 이해하기
■ 기관 매수 신호
• 정의: 코인베이스 프라임을 통해 기관 투자자들이 연속적인 매수 활동을 보이며, 이와 함께 거래량 증가와 강한 상승 추세가 나타날 때 발생
• 시각적 표현: 매수 신호가 발생한 캔들에 반투명 파란색 바 컬러링과 함께 "Institution Buying Detected!" 라벨 표시
• 시장 해석: 기관 투자자들이 적극적으로 현물 비트코인을 매수하고 있으며, 이는 곧 가격 상승으로 이어질 가능성이 높음을 의미
• 신호 강도 요소:
▶ 연속적인 가격 상승 패턴
▶ 평균보다 높은 거래량
▶ 강한 상승 추세 강도 측정값
▶ 유의미한 가격 변동
■ 기관 매도 신호
• 정의: 코인베이스 프라임을 통해 기관 투자자들이 연속적인 매도 활동을 보이며, 이와 함께 거래량 증가와 강한 하락 추세가 나타날 때 발생
• 시각적 표현: 매도 신호가 발생한 캔들에 반투명 분홍색 바 컬러링과 함께 "Institution Selling Detected!" 라벨 표시
• 시장 해석: 기관 투자자들이 적극적으로 현물 비트코인을 매도하고 있으며, 이는 곧 가격 하락으로 이어질 가능성이 높음을 의미
• 신호 강도 요소:
▶ 연속적인 가격 하락 패턴
▶ 평균보다 높은 거래량
▶ 강한 하락 추세 강도 측정값
▶ 유의미한 가격 변동
─────────────────────────────────────
◆ 추세 강도 이해하기
■ 추세 강도 측정 방식
• 정의: 최근 일정 기간 동안의 상승/하락 캔들 비율을 분석하여 추세의 강도를 측정
• 시각적 표현: 테이블에 "BULL STRENGTH" 또는 "BEAR STRENGTH"로 표시되며, 백분율 값과 함께 "STRONG" 또는 "WEAK" 상태 표시
• 강도 임계값: 사용자가 설정 가능한 임계값에 따라 강함/약함 판정
• 계산 방식:
▶ 상승 추세 강도 = (상승 캔들 수) / (전체 분석 기간)
▶ 하락 추세 강도 = (하락 캔들 수) / (전체 분석 기간)
▶ 강도가 임계값 이상일 때 "STRONG", 미만일 때 "WEAK"로 표시
■ 추세 강도의 활용
• 신호 필터링: 추세 강도가 강할 때만 신호를 생성하여 허위 신호 감소
• 추세 확인: 현재 시장 추세의 건전성과 지속 가능성 평가
• 진입/퇴출 결정: 강한 추세에서 진입하고 약한 추세로 전환될 때 퇴출 고려
• 리스크 관리: 약한 추세에서는 포지션 크기를 줄이고, 강한 추세에서는 늘리는 전략 수립 가능
─────────────────────────────────────
◆ 실전 트레이딩 응용
■ 기관 매수 신호 활용 전략
• 추세 전환 시나리오:
▶ 설정: 하락 추세 중 강한 기관 매수 신호 발생
▶ 진입: 신호 확인 후 다음 캔들에서 매수
▶ 손절: 신호 캔들의 저점 아래
▶ 이익실현: 이전 주요 저항선 도달 시 또는 추세 강도가 약해질 때
• 추세 지속 시나리오:
▶ 설정: 상승 추세 중 조정 후 기관 매수 신호 발생
▶ 진입: 신호 확인 후 매수
▶ 손절: 최근 주요 저점 아래
▶ 이익실현: 추세 강도를 고려하여 단계적으로 이익실현
■ 기관 매도 신호 활용 전략
• 추세 전환 시나리오:
▶ 설정: 상승 추세 중 강한 기관 매도 신호 발생
▶ 진입: 신호 확인 후 다음 캔들에서 매도
▶ 손절: 신호 캔들의 고점 위
▶ 이익실현: 이전 주요 지지선 도달 시 또는 추세 강도가 약해질 때
• 추세 지속 시나리오:
▶ 설정: 하락 추세 중 반등 후 기관 매도 신호 발생
▶ 진입: 신호 확인 후 매도
▶ 손절: 최근 주요 고점 위
▶ 이익실현: 추세 강도를 고려하여 단계적으로 이익실현
■ 다중 시간프레임 접근법
• 상위 시간프레임 방향성 확인:
▶ 일봉/4시간봉에서 기관 신호 및 추세 강도 확인
▶ 주 트레이딩 방향 설정에 활용
• 하위 시간프레임 진입점 찾기:
▶ 상위 시간프레임 방향과 일치하는 하위 시간프레임 신호 대기
▶ 정밀한 진입점 포착에 활용
• 시간프레임 간 신호 일치 확인:
▶ 여러 시간프레임에서 동일한 방향의 신호가 발생할 때 신호 강도 증가
▶ 높은 확률의 트레이딩 기회 포착
─────────────────────────────────────
◆ 지표 설정 가이드
■ 주요 설정 매개변수
• Institutional Continuity Period (기관 연속성 확인 기간):
▶ 목적: 기관의 연속적인 매수/매도 활동을 확인할 기간 설정
▶ 낮은 값: 더 많은 신호 생성, 반응성 증가
▶ 높은 값: 신호 수 감소, 신뢰성 증가
• Trend Strength Threshold (추세 강도 임계값):
▶ 목적: 추세가 강하다고 판단할 최소 임계값 설정
▶ 낮은 값: 더 많은 신호, 낮은 필터링
▶ 높은 값: 더 강한 추세에서만 신호 생성, 높은 필터링
─────────────────────────────────────
◆ 다른 지표와의 시너지
• 지지/저항 레벨:
▶ 주요 지지/저항 레벨에서 발생하는 기관 신호는 확률이 더 높음
▶ 기술적 분석의 핵심 레벨과 기관 활동의 결합은 강력한 시그널 제공
• 이동평균선:
▶ 주요 이동평균선(50MA, 200MA) 근처에서 발생하는 기관 신호 주목
▶ 이동평균선 돌파와 기관 신호가 일치할 때 강한 추세 변화 가능성
• RSI/모멘텀 지표:
▶ 과매수/과매도 상태에서 발생하는 기관 신호는 반전 가능성 높임
▶ 모멘텀 다이버전스와 기관 신호의 일치는 강력한 반전 신호
• 볼륨 프로파일:
▶ 높은 볼륨 노드에서 발생하는 기관 신호는 중요한 가격 레벨 확인
▶ 주요 거래 영역에서의 기관 활동은 가격 방향에 큰 영향 미침
• 시장 구조:
▶ 주요 시장 구조(높은 고점/저점, 낮은 고점/저점) 근처에서 발생하는 기관 신호는 구조 변화 암시
▶ 시장 구조 변화와 기관 활동의 일치는 중요한 추세 전환점 표시
─────────────────────────────────────
◆ 결론
Coinbase Institutional Smart Money Detector는 코인베이스 프라임을 통한 기관 투자자들의 현물 비트코인 거래 활동을 실시간으로 추적하여 트레이더들에게 귀중한 통찰력을 제공합니다. 어떤 거래소의 비트코인 차트에도 적용 가능하기 때문에, 여러분이 선호하는 트레이딩 플랫폼에서 바로 활용할 수 있습니다.
이 지표의 핵심 가치는 일반 트레이더들이 접근하기 어려운 기관 자금 흐름 데이터를 직관적으로 시각화하여 제공한다는 점입니다. 연속적인 가격 움직임, 거래량 증가, 그리고 추세 강도를 종합적으로 분석하여 기관의 활동을 포착함으로써, 여러분은 시장의 큰 손들과 함께 움직일 수 있는 기회를 얻게 됩니다.
코인베이스 프라임 데이터를 기반으로 한 명확한 매수/매도 신호와 실시간 추세 강도 측정은 트레이더들이 시장 상황을 한눈에 파악하고 신속하게 전략적 결정을 내릴 수 있게 도와줍니다. 이 강력한 도구를 여러분의 트레이딩 전략에 통합함으로써, 시장의 스마트 머니가 어디로 흘러가는지 파악하고 그에 따라 포지셔닝할 수 있는 경쟁 우위를 확보하세요.
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※ 면책 조항: 모든 트레이딩 도구와 마찬가지로, Institutional Smart Money Detector는 보조 지표로 사용해야 하며 트레이딩 결정을 전적으로 의존해서는 안 됩니다. 과거의 기관 행동 패턴이 미래 시장 움직임을 보장하지는 않습니다. 항상 적절한 리스크 관리 전략을 트레이딩에 활용하세요.
Automated Scalping Signals with TP/SL Indicator [QuantAlgo]🟢 Overview
The Automated Scalping Signals with Take Profit & Stop Loss Indicator is a multi-timeframe trading system that combines market structure analysis with directional bias filtering to identify potential scalping opportunities. It detects Points of Interest (POI) including Fair Value Gaps (FVG) and Order Blocks (OB) while cross-referencing entries with higher timeframe exponential moving average positioning to create systematic entry conditions.
The indicator features adaptive timeframe calculations that automatically scale analysis periods based on your chart timeframe, maintaining consistent analytical relationships across different trading sessions. It provides integrated trade management with stop loss calculation methods, configurable risk-reward ratios, and real-time performance tracking through dashboard displays showing trade statistics, bias direction, and active position status.
This advanced system is designed for low timeframe trading, typically performing optimally on 1 to 15-minute charts across popular instruments such as OANDA:XAUUSD , CME_MINI:MES1! , CME_MINI:ES1! , CME_MINI:MNQ1! , CBOT_MINI:YM1! , CBOT_MINI:MYM1! , BYBIT:BTCUSDT.P , BYBIT:ETHUSDT.P , or any asset and timeframe of your preference.
🟢 How It Works
The indicator operates using a dual-timeframe mathematical framework where higher timeframe exponential moving averages establish directional bias through cross-over analysis, while simultaneously scanning for specific market structure patterns on the POI timeframe. The timeframe calculation engine uses multiplication factors to determine analysis periods, ensuring the bias timeframe provides trend context while the POI timeframe captures structural formations.
The structural analysis begins with FVG detection, which systematically scans price action to identify imbalances where gaps exist between consecutive candle ranges with no overlapping wicks. When such gaps are detected, the algorithm measures their size against minimum thresholds to filter out insignificant formations. Concurrently, OB recognition analyzes three-candle sequences, examining specific open/close relationships that indicate potential institutional accumulation zones. Once these structural patterns are identified, the algorithm cross-references them against the higher timeframe bias direction, creating a validation filter that only permits entries aligned with the prevailing EMA cross-over state. When price subsequently intersects these validated POI zones, entry signals generate with the system calculating entry levels at zone midpoints, then applying the selected stop loss methodology combined with the configured risk-reward ratio to determine take profit placement.
To mirror realistic trading conditions, the indicator incorporates configurable slippage calculations that account for execution differences between intended and actual fill prices. When trades reach their take profit or stop loss levels, the algorithm applies slippage adjustments that worsen the exit prices in a conservative manner - reducing take profit fills and increasing stop loss impact. This approach ensures backtesting results reflect more realistic performance expectations by accounting for spread costs, market volatility during execution, and liquidity constraints that occur in live trading environments.
It also has a performance dashboard that continuously tracks and displays comprehensive trading metrics:
1/ Bias TF / POI TF: Displays the calculated timeframes used for bias analysis and POI detection, showing the actual periods (e.g., "15m / 5m") that result from the multiplier settings to confirm proper adaptive timeframe selection
2/ Bias Direction: Shows current market trend assessment (Bullish, Bearish, or Sideways) derived from EMA cross-over analysis to indicate which trade directions align with prevailing momentum
3/ Data Processing: Indicates how many price bars have been analyzed by the system, helping users verify if complete historical data has been processed for comprehensive strategy validation
4/ Total Trades: Displays the cumulative number of completed trades plus any active positions, providing volume assessment for statistical significance of other metrics
5/ Wins/Losses: Shows the raw count of profitable versus unprofitable trades, offering immediate insight into strategy effectiveness frequency
6/ Win Rate: Reveals the percentage of successful trades, where values above 50% generally indicate effective entry timing and values below suggest strategy refinement needs
7/ Total R-Multiple: Displays cumulative risk-reward performance across all trades, with positive values demonstrating profitable system operation and negative values indicating net losses requiring analysis
8/ Average R Win/Loss: Shows average risk-reward ratios for winning and losing trades separately, where winning averages approaching the configured take profit ratio indicate minimal slippage impact while losing averages near -1.0 suggest effective stop loss execution
9/ TP Ratio / Slippage: Displays the configured take profit ratio and slippage settings with calculated performance impact, showing how execution costs affect actual versus theoretical returns
10/ Profit Factor: Calculates the ratio of total winning amounts to total losing amounts, where values above 1.5 suggest robust profitability, values between 1.0-1.5 indicate modest success, and values below 1.0 show net losses
11/ Maximum Drawdown: Tracks the largest peak-to-trough decline in R-multiple terms, with smaller negative values indicating better capital preservation and risk control during losing streaks
🟢 How to Use
Start by applying the indicator to your chart and observe its performance across different market conditions to understand how it identifies bias direction and POI formations. Then navigate to the settings panel to configure the Bias Timeframe Multiplier for trend context sensitivity and POI Timeframe Multiplier for structural analysis frequency according to your trading preference and objectives.
Next, fine-tune the EMA periods in Bias Settings to control trend detection sensitivity and select your preferred POI types based on your analytical preference. Proceed to configure your Risk Management approach by selecting from the available stop loss calculation methods and setting the Take Profit ratio that aligns with your risk tolerance and profit objectives. Complete the setup by customizing Display Settings to control table visibility and trade visualization elements, adjusting UI positioning and colors for optimal chart readability, then activate Alert Conditions for automated notifications on trade entries, exits, and bias direction changes to support systematic trade management.
🟢 Examples
OANDA:XAUUSD
CME_MINI:MES1!
CME_MINI:ES1!
CME_MINI:MNQ1!
CBOT_MINI:YM1!
BYBIT:BTCUSDT.P
BINANCE:SOLUSD
*Disclaimer: Past performance is not indicative of future results. None of our statements, claims, or signals from our indicators are intended to be financial advice. All trading involves substantial risk of loss, not just upside potential. Users are highly recommended to carefully consider their financial situation and risk tolerance before trading.
Adaptive Momentum Deviation Oscillator | QuantMACAdaptive Momentum Deviation Oscillator | QuantMAC 📊
Overview 🎯
The Adaptive Momentum Deviation Oscillator (AMDO) is an advanced technical analysis indicator that combines the power of Bollinger Bands with adaptive momentum calculations to identify optimal entry and exit points in financial markets. This sophisticated oscillator creates dynamic bands that adapt to market volatility while providing clear visual signals for both trending and ranging market conditions.
How It Works 🔧
Core Methodology
The AMDO employs a sophisticated multi-layered approach to market analysis through four distinct phases:
Bollinger Band Foundation : The indicator begins by establishing a volatility baseline using traditional Bollinger Bands. These bands are calculated using a simple moving average as the center line, with upper and lower bands positioned at a specific number of standard deviations away from this centerline. The distance between these bands expands and contracts based on market volatility, creating a dynamic envelope around price action.
BB% Normalization Process : The raw price data is then transformed into a normalized percentage format that represents where the current price sits within the Bollinger Band envelope. When price is at the lower band, this percentage reads 0%; at the upper band, it reads 100%. This normalization allows for consistent comparison across different timeframes and price levels, creating a standardized oscillator that oscillates between extreme values.
Adaptive Momentum Band Construction : The normalized BB% values undergo a secondary volatility analysis where their own standard deviation is calculated over a specified period. This creates "bands around the bands" - upper and lower boundaries that adapt to the volatility of the normalized price position itself. These adaptive bands expand during periods of high momentum volatility and contract during consolidation phases.
Intelligent Signal Synthesis : The final layer combines the adaptive momentum bands with user-defined threshold levels to create a sophisticated trigger system. The indicator monitors when the dynamic bands cross above or below these thresholds, filtering out noise while capturing significant momentum shifts. This creates a dual-confirmation system where both volatility adaptation and threshold breaches must align for signal generation.
Key Components 🛠️
Adaptive Momentum Bands 📈
Dynamic Volatility Response : These bands automatically widen during periods of high momentum volatility and narrow during consolidation phases. Unlike fixed oscillator boundaries, they continuously recalibrate based on recent price behavior within the Bollinger Band framework.
Dual-Layer Calculation : The bands are derived from the volatility of the normalized price position itself, creating a "volatility of volatility" measurement. This provides early warning signals when momentum characteristics are changing, even before price breakouts occur.
State-Aware Visualization : The bands employ intelligent color coding that transitions between active and neutral states based on their interaction with threshold levels. Active states indicate high-probability momentum conditions, while neutral states suggest consolidation or indecision.
Momentum Persistence Tracking : The bands maintain memory of recent momentum characteristics, allowing them to distinguish between genuine momentum shifts and temporary price spikes or dips.
Threshold Levels 🎚️
Statistical Significance Boundaries : The threshold levels (default 83 for long, 40 for short) are positioned to capture statistically significant momentum events while filtering out market noise. These levels represent points where momentum probability shifts meaningfully in favor of directional moves.
Asymmetric Design Philosophy : The intentional asymmetry between long and short thresholds (83 vs 40) reflects the natural upward bias of many financial markets and the different risk/reward profiles of long versus short positions.
Contextual Sensitivity : The thresholds work in conjunction with the adaptive bands to create context-sensitive triggers. A threshold breach is only meaningful when it occurs in the proper sequence with band interactions.
Risk-Adjusted Positioning : The threshold levels are calibrated to provide favorable risk-adjusted entry points, considering both the probability of success and the potential magnitude of subsequent moves.
Bollinger Bands Overlay 📊
Multi-Timeframe Context : The price chart overlay provides essential context by showing traditional Bollinger Bands alongside the oscillator. This dual perspective allows traders to see both the absolute price position and the momentum characteristics simultaneously.
Support/Resistance Identification : The filled band area creates a visual representation of dynamic support and resistance levels. Price interaction with these bands provides additional confirmation for oscillator signals.
Volatility Environment Assessment : The width and slope of the bands offer immediate visual feedback about the current volatility environment, helping traders adjust their expectations and risk management accordingly.
Confluence Analysis : The overlay enables traders to identify confluence between price action at Bollinger Band levels and oscillator signals, creating higher-probability trade setups.
Signal Generation ⚡
The AMDO generates signals through precise mathematical crossover events:
Long Signals 🟢
Momentum Accumulation Detection : Long signals are generated when the lower adaptive momentum band crosses above the 83 threshold, indicating that downside momentum has exhausted and bullish momentum is beginning to accumulate. This represents a shift from defensive to offensive market posture.
Statistical Edge Confirmation : The crossing event occurs only when momentum characteristics have shifted sufficiently to provide a statistical edge for long positions. The adaptive nature ensures the signal quality remains consistent across different market volatility regimes.
Visual State Synchronization : Upon signal generation, the entire indicator ecosystem shifts to a bullish state - bar colors change, band states update, and the visual hierarchy emphasizes the long bias until conditions change.
Momentum Persistence Validation : The signal incorporates momentum persistence analysis to distinguish between genuine trend starts and false breakouts, reducing whipsaw trades in choppy market conditions.
Short Signals 🔴
Momentum Exhaustion Recognition : Short signals trigger when the upper adaptive momentum band crosses below the 40 threshold, signaling that bullish momentum has peaked and bearish momentum is emerging. This asymmetric threshold reflects the different dynamics of bullish versus bearish market phases.
Volatility-Adjusted Timing : The adaptive band system ensures that short signals are generated with appropriate timing regardless of the underlying volatility environment, maintaining signal quality in both high and low volatility conditions.
Regime-Aware Activation : Short signals are only active in Long/Short trading mode, recognizing that not all trading strategies benefit from short positions. The indicator adapts its behavior based on the selected trading approach.
Risk-Calibrated Thresholds : The 40 threshold is specifically calibrated to capture meaningful bearish momentum shifts while accounting for the higher risk typically associated with short positions.
Cash Signals 💰
Defensive Positioning Logic : In Long/Cash mode, cash signals are generated when short conditions are met, allowing traders to move to a defensive cash position rather than taking on short exposure. This preserves capital during unfavorable market conditions.
Risk Mitigation Strategy : Cash signals represent a risk-off approach that removes market exposure when momentum conditions favor the short side, protecting long-biased portfolios from adverse market movements.
Opportunity Cost Optimization : The cash position allows traders to avoid negative returns while maintaining flexibility to re-enter long positions when momentum conditions improve, optimizing the risk-adjusted return profile.
Features & Customization ⚙️
Color Schemes 🎨
9 pre-built color schemes (Classic through Classic9)
Custom color override option
Dynamic color changes based on signal states
Trading Modes 📈
Long/Short : Full bidirectional trading capability
Long/Cash : Long-only strategy with cash positions
Performance Metrics 📊
The indicator includes a comprehensive suite of advanced performance analytics that provide deep insights into strategy effectiveness:
Risk-Adjusted Return Metrics
Sortino Ratio : Measures returns relative to downside deviation only, providing a more accurate assessment of risk-adjusted performance by focusing on harmful volatility rather than total volatility. This metric is particularly valuable for asymmetric return distributions.
Sharpe Ratio : Calculates excess return per unit of total risk, offering a standardized measure of risk-adjusted performance that allows for comparison across different strategies and timeframes.
Omega Ratio : Employs probability-weighted analysis to compare the likelihood and magnitude of gains versus losses, providing insights into the overall shape of the return distribution and tail risk characteristics.
Drawdown and Risk Analysis
Maximum Drawdown : Tracks the largest peak-to-trough equity decline, providing crucial information about the worst-case scenario and helping traders understand the emotional and financial stress they might encounter.
Dynamic Drawdown Monitoring : Continuously updates drawdown calculations in real-time, allowing traders to monitor current drawdown levels relative to historical maximums.
Trade Statistics and Profitability
Profit Factor Analysis : Compares gross profits to gross losses, revealing the efficiency of the trading approach and the relationship between winning and losing trades.
Win Rate Calculation : Provides the percentage of profitable trades, which must be interpreted in conjunction with profit factor and average trade size for meaningful analysis.
Trade Frequency Tracking : Monitors total trade count to assess strategy turnover and transaction cost implications.
Position Sizing Guidance
Half Kelly Percentage : Calculates optimal position sizing based on Kelly Criterion methodology, then applies a conservative 50% reduction to account for parameter uncertainty and reduce volatility. This provides mathematically-based position sizing guidance that balances growth with risk management.
Parameters & Settings 🔧
BMD Settings
- Base Length : Period for Bollinger Band calculation (default: 10)
- Source : Price data source (default: close)
- Standard Deviation Length : Period for volatility calculation (default: 35)
- SD Multiplier : Bollinger Band width multiplier (default: 1.0)
- BB% Multiplier : Scaling factor for BB% calculation (default: 100)
BMD Settings
Base Length : Period for Bollinger Band calculation (default: 10)
Source : Price data source (default: close)
Standard Deviation Length : Period for volatility calculation (default: 35)
SD Multiplier : Bollinger Band width multiplier (default: 1.0)
BB% Multiplier : Scaling factor for BB% calculation (default: 100)
Signal Thresholds 🎯
Long Threshold : Trigger level for long signals (default: 83)
Short Threshold : Trigger level for short signals (default: 40)
Display Options 🖥️
Toggleable metrics table with 6 position options
Customizable date range limiter
Multiple visual elements for comprehensive analysis
Use Cases & Applications 💡
Trend Following
Identifies momentum shifts in trending markets
Provides early entry signals during trend continuations
Adaptive bands adjust to changing volatility conditions
Mean Reversion
Detects oversold/overbought conditions
Signals potential reversal points
Works effectively in ranging markets
Risk Management
Built-in performance metrics for strategy evaluation
Half Kelly percentage for position sizing guidance
Maximum drawdown monitoring
Advantages ✅
Adaptive Nature : Automatically adjusts to market volatility
Dual Display : Oscillator and price chart components work together
Comprehensive Metrics : Built-in performance analysis
Flexible Trading Modes : Supports different trading strategies
Visual Clarity : Color-coded signals and states
Customizable : Extensive parameter adjustment options
Important Considerations ⚠️
This indicator is designed for educational and analysis purposes
Should be used in conjunction with other technical analysis tools
Proper risk management is essential when trading
Backtest thoroughly before implementing in live trading
Market conditions can change rapidly, affecting indicator performance
Disclaimer ⚠️
Past performance is not indicative of future results. Trading involves substantial risk of loss and is not suitable for all investors. The information provided by this indicator should not be considered as financial advice. Always conduct your own research.
No indicator guarantees profitable trades - Always use proper risk management! 🛡️
Kijun Shifting Band Oscillator | QuantMAC🎯 Kijun Shifting Band Oscillator | QuantMAC
📊 **Revolutionary Technical Analysis Tool Combining Ancient Ichimoku Wisdom with Cutting-Edge Statistical Methods**
🌟 Overview
The Kijun Shifting Band Oscillator represents a sophisticated fusion of traditional Japanese technical analysis and modern statistical theory. Built upon the foundational concepts of the Ichimoku Kinko Hyo system, this indicator transforms the classic Kijun-sen (base line) into a dynamic, multi-dimensional analysis tool that provides traders with unprecedented market insights.
This advanced oscillator doesn't just show you where price has been – it reveals the underlying momentum dynamics and volatility patterns that drive market movements, giving you a statistical edge in your trading decisions.
🔥 Key Features & Innovations
Dual Trading Modes for Maximum Flexibility: 🚀
Long/Short Mode: Full bidirectional trading capability for aggressive traders seeking to capitalize on both bullish and bearish market conditions
Long/Cash Mode: Conservative approach perfect for risk-averse traders, taking long positions during uptrends and moving to cash during downtrends (avoiding short exposure)
Advanced Visual Intelligence: 🎨
9 Professional Color Schemes: From classic blue/navy to vibrant orange/purple combinations, each optimized for different chart backgrounds and personal preferences
Dynamic Gradient Histogram: Color intensity reflects oscillator strength, providing instant visual feedback on momentum magnitude
Intelligent Overlay Bands: Semi-transparent fills create clear visual boundaries without cluttering your chart
Smart Candle Coloring: Real-time color changes reflect current market state and trend direction
Customizable Threshold Lines: Clearly marked entry and exit levels with contrasting colors
Professional-Grade Analytics: 📊
Real-Time Performance Metrics: Live calculation of 9 key performance indicators
Risk-Adjusted Returns: Sharpe, Sortino, and Omega ratios for comprehensive performance evaluation
Position Sizing Guidance: Half-Kelly percentage for optimal risk management
Drawdown Analysis: Maximum drawdown tracking for risk assessment
📈 Deep Technical Foundation
Kijun-Based Mathematical Framework: 🧮
The indicator begins with the traditional Kijun-sen calculation but extends it significantly:
Statistical Enhancements: 📉
Adaptive Volatility: Bands expand and contract based on market volatility
Momentum Filtering: EMA smoothing of oscillator for trend confirmation
State Management: Intelligent signal filtering prevents whipsaws and false signals
Multi-Timeframe Compatibility: Optimized algorithms work across all timeframes
⚙️ Comprehensive Parameter Control
Kijun Core Settings: 🎛️
Kijun Length (Default: 30): Controls the lookback period for the base calculation. Shorter periods = more responsive, longer periods = smoother signals
Source Selection: Choose from Close, Open, High, Low, or HL2. Close price recommended for most applications
Calculation Method: Uses traditional Ichimoku methodology ensuring compatibility with classic analysis
Advanced Oscillator Configuration: 📊
Standard Deviation Length (Default: 36): Determines volatility measurement period. Affects band width and sensitivity
SD Multiplier (Default: 2.1): Fine-tune band distance from basis line. Higher values = wider bands, lower values = tighter bands
Oscillator Multiplier (Default: 100): Scales the final oscillator output. Useful for matching other indicators or personal preference
Smoothing Algorithm: Built-in EMA smoothing prevents noise while maintaining responsiveness
Signal Threshold Optimization: 🎯
Long Threshold (Default: 83): Oscillator level that triggers long entries. Higher values = fewer but stronger signals
Short Threshold (Default: 42): Oscillator level that triggers short entries. Lower values = fewer but stronger signals
Threshold Logic: Crossover-based system with state management prevents signal overlap
Customization Range: Fully adjustable to match your trading style and risk tolerance
Precision Date Control: 📅
Start Date/Month/Year: Precise backtesting control down to the day
Historical Analysis: Test strategies on specific market periods or events
Strategy Validation: Isolate performance during different market conditions
📊 Professional Metrics Dashboard
Risk Assessment Metrics: 💼
Maximum Drawdown %: Largest peak-to-trough decline in portfolio value. Critical for understanding worst-case scenarios and position sizing
Sortino Ratio: Risk-adjusted return measure focusing only on downside volatility. Superior to Sharpe ratio for asymmetric return distributions
Sharpe Ratio: Classic risk-adjusted performance metric. Values above 1.0 considered good, above 2.0 excellent
Omega Ratio: Probability-weighted ratio capturing all moments of return distribution. More comprehensive than Sharpe or Sortino
Performance Analytics: 📈
Profit Factor: Gross Profit ÷ Gross Loss. Values above 1.0 indicate profitability, above 2.0 considered excellent
Win Rate %: Percentage of profitable trades. Consider alongside average win/loss size for complete picture
Net Profit %: Total return on initial capital. Accounts for compounding effects
Total Trades: Sample size for statistical significance assessment
Advanced Position Sizing: 🎯
Half Kelly %: Optimal position size based on Kelly Criterion, reduced by 50% for safety margin
Risk Management: Helps determine appropriate position size relative to account equity
Mathematical Foundation: Based on win probability and profit factor calculations
Practical Application: Directly usable percentage for position sizing decisions
🎨 Advanced Display Options
Flexible Interface Design: 🖥️
6 Positioning Options: Top/Bottom/Middle × Left/Right combinations for optimal chart organization
Toggle Functionality: Show/hide metrics table for clean chart presentation during analysis
Color Coordination: Metrics table colors match selected oscillator color scheme
Professional Styling: Clean, readable format with proper spacing and alignment
Visual Hierarchy: 🎭
Oscillator Histogram: Primary focus with gradient intensity showing momentum strength
Threshold Lines: Clear horizontal references for entry/exit levels
Zero Line: Neutral reference point for trend bias determination
Background Bands: Subtle overlay context without chart clutter
🚀 Advanced Signal Generation System
Multi-Layer Signal Logic: ⚡
Primary Signal Generation: Oscillator crossover above Long Threshold (default 83) triggers long entries
Exit Signal Processing: Oscillator crossunder below Short Threshold (default 42) triggers position exits
State Management System: Prevents duplicate signals and ensures clean position transitions
Mode-Specific Logic: Different behavior for Long/Short vs Long/Cash modes
Date Range Filtering: Signals only generated within specified backtesting period
Confirmation Requirements: Bar confirmation prevents false signals from intrabar price spikes
Intelligent Position Management: 🧠
Entry Tracking: Precise entry price recording for accurate P&L calculations
Position State Monitoring: Continuous tracking of long/short/cash positions
Automatic Exit Logic: Seamless position closure and new position initiation
Performance Calculation: Real-time P&L tracking with compounding effects
📉📈 Comprehensive Band Interpretation Guide
Dynamic Band Analysis: 🔍
Upper Band Function: Represents dynamic resistance based on recent volatility. Price approaching upper band suggests potential reversal or breakout
Lower Band Function: Represents dynamic support with volatility adjustment. Price near lower band indicates oversold conditions or support testing
Middle Line (Basis): Trend direction indicator. Price above = bullish bias, price below = bearish bias
Band Width Interpretation: Wide bands = high volatility, narrow bands = low volatility/potential breakout setup
Band Slope Analysis: Rising bands = strengthening trend, falling bands = weakening trend
Oscillator Interpretation: 📊
Values Above 50: Price in upper half of recent range, bullish momentum
Values Below 50: Price in lower half of recent range, bearish momentum
Extreme Values (>80 or <20): Overbought/oversold conditions, potential reversal zones
Momentum Divergence: Oscillator direction vs price direction for early reversal signals
Trend Confirmation: Oscillator direction confirming or contradicting price trends
💡 Strategic Trading Applications
Primary Trading Strategies: 🎯
Trend Following: Use threshold crossovers to capture major directional moves. Best in trending markets with clear directional bias
Mean Reversion: Identify extreme oscillator readings for counter-trend opportunities. Effective in range-bound markets
Breakout Trading: Monitor band compressions followed by expansions for breakout signals
Swing Trading: Combine oscillator signals with band interactions for swing position entries/exits
Risk Management: Use metrics dashboard for position sizing and risk assessment
Market Condition Optimization: 🌊
Trending Markets: Increase threshold separation for fewer, stronger signals
Choppy Markets: Decrease threshold separation for more responsive signals
High Volatility: Increase SD multiplier for wider bands
Low Volatility: Decrease SD multiplier for tighter bands and earlier signals
⚙️ Advanced Configuration Tips
Parameter Optimization Guidelines: 🔧
Kijun Length Adjustment: Shorter periods (10-20) for faster signals, longer periods (50-100) for smoother trends
SD Length Tuning: Match to your trading timeframe - shorter for responsive, longer for stability
Threshold Calibration: Backtest different levels to find optimal entry/exit points for your market
Color Scheme Selection: Choose schemes that provide best contrast with your chart background and other indicators
Integration with Other Indicators: 🔗
Volume Indicators: Confirm oscillator signals with volume spikes
Support/Resistance: Use key levels to filter oscillator signals
Momentum Indicators: RSI, MACD confirmation for signal strength
Trend Indicators: Moving averages for overall trend bias confirmation
⚠️ Important Usage Notes & Limitations
Indicator Characteristics: ⚡
Lagging Nature: Based on historical price data - signals occur after moves have begun
Best Practice: Combine with leading indicators and price action analysis
Market Dependency: Performance varies across different market conditions and instruments
Backtesting Essential: Always validate parameters on historical data before live implementation
Optimization Recommendations: 🎯
Parameter Testing: Systematically test different combinations on your preferred instruments
Walk-Forward Analysis: Regularly re-optimize parameters to maintain effectiveness
Market Regime Awareness: Adjust parameters for different market conditions (trending vs ranging)
Risk Controls: Implement maximum drawdown limits and position size controls
🔧 Technical Specifications
Performance Optimization: ⚡
Efficient Algorithms: Optimized calculations for smooth real-time operation
Memory Management: Smart array handling for metrics calculations
Visual Optimization: Balanced detail vs performance for responsive charts
Multi-Symbol Ready: Consistent performance across different assets
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The Kijun Shifting Band Oscillator represents the evolution of technical analysis, bridging the gap between traditional methods and modern quantitative approaches. This indicator provides traders with a comprehensive toolkit for market analysis, combining the intuitive wisdom of Japanese candlestick analysis with the precision of statistical mathematics.
🎯 Designed for serious traders who demand professional-grade analysis tools with institutional-quality metrics and risk management capabilities. Whether you're a discretionary trader seeking visual confirmation or a systematic trader building quantitative strategies, this indicator provides the foundation for informed trading decisions.
⚠️ IMPORTANT DISCLAIMER
Past Performance Warning: 📉⚠️
PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS. Historical backtesting results, while useful for strategy development and parameter optimization, do not guarantee similar performance in live trading conditions. Market conditions change continuously, and what worked in the past may not work in the future.
Remember: Successful trading requires discipline, continuous learning, and adaptation to changing market conditions. No indicator or strategy guarantees profits, and all trading involves substantial risk of loss.
LotSize CalculatorLotSize Calculator Documentation
Overview
The LotSize Calculator is a powerful TradingView indicator designed to help traders calculate optimal position sizes based on risk management principles. It provides a visual representation of trade setups, including entry points, stop losses, and take profits, while calculating the appropriate lot size based on your risk preferences.
Key Features
Automatic lot size calculation based on risk amount
Support for multiple asset classes (forex, commodities, indices, etc.)
Visual R-multiple levels (1R to 5R)
Real-time position tracking with drawdown and run-up statistics
Customizable visual elements and display options
Input Parameters
Risk Management Settings
Risk Amount Type: Choose between risking a fixed amount in dollars ($) or a specific lot size.
Risk Amount: The amount you want to risk on the trade (in dollars if Risk Amount Type is set to $, or in lots if set to Lots).
Overwrite TP: Optional setting to automatically set take profit at a specific R-multiple (1R, 2R, 3R, 4R, or 5R).
Table Comments: Optional field to add personal notes to the position table.
Trade Setup Levels
Trigger Price: The price at which your trade will be entered.
Stop Loss: Your predetermined exit price to limit losses.
Take Profit: Your target price to secure profits.
Time Of Setup Start Bar: The starting time for your trade setup window.
Display Settings
Plot Position Labels: Toggle to show/hide position information labels on the chart.
Plot Position Table: Toggle to show/hide the position information table.
Show Money: Toggle to display monetary values ($) in the labels and table.
Show Points: Toggle to display point values in the labels and table.
Show Ticks: Toggle to display tick values in the labels and table.
Visual Appearance
Entry Color: Color for entry level line and labels.
Take Profit Color: Color for take profit level line and labels.
Stop Loss Color: Color for stop loss level line and labels.
Label Text Color: Color for text in the position labels.
Table Background: Background color for the position information table.
Table Text: Text color for the position information table.
R Labels: Color for the R-multiple level labels.
Table Position: Position of the information table on the chart (options: Bottom Right, Bottom Left, Bottom Middle, Top Right, Top Middle).
How to Use
Basic Setup
Set your entry price in the "Trigger Price" field.
Set your stop loss level in the "Stop Loss" field.
Set your take profit level in the "Take Profit" field.
Choose your risk amount type ($ or Lots) and enter the risk amount.
Optionally, select an R-multiple for automatic take profit calculation.
Understanding the Display
The indicator will show:
Horizontal lines for entry, stop loss, and take profit levels
Colored zones between entry and take profit (potential profit zone) and between entry and stop loss (potential loss zone)
R-multiple levels based on your risk (1R, 2R, 3R, 4R, 5R)
A table displaying:
Position type (long/short) and size
Original risk and reward figures
Maximum run-up and drawdown during the trade
Trade Monitoring
Once a trade is triggered (either by price crossing a stop entry or reaching a limit entry), the indicator tracks:
Current position value
Maximum run-up (highest profit seen)
Maximum drawdown (largest loss seen)
Trade outcome when take profit or stop loss is hit
Advanced Features
Asset Type Detection
The LotSize Calculator automatically detects the type of asset being traded (forex, commodity, index, etc.) and adjusts calculations accordingly to ensure accurate position sizing.
R-Multiple Visualization
R-multiples help visualize potential reward relative to risk. For example, 2R means the potential reward is twice the amount risked. The indicator displays these levels directly on your chart for easy reference.
Adaptive Position Labels
Position labels adjust their display based on trade direction (long or short) and include relevant information about risk, reward, and current position status.
Best Practices
Always confirm your risk is appropriate for your account size (typically 1-2% of account per trade).
Use the R-multiple visualization to ensure your trades offer favorable risk-to-reward ratios.
The indicator works best when used alongside your existing strategy for entry and exit signals.
Customize the visual appearance to match your chart theme for better visibility.
Troubleshooting
If position calculations seem incorrect, verify that the indicator is detecting the correct instrument type.
For forex pairs, ensure your broker's lot size conventions match those used by the indicator.
The indicator may need adjustment for certain exotic instruments or markets with unusual tick sizes.
Step-Based Trailing Stop-Loss IndicatorThis indicator is built for momentum traders who want to maximize winning trades and minimize losses through a smart, step-based trailing stop-loss system. Instead of using a fixed Take Profit, this tool dynamically protects profits once the trade reaches a favorable RR (Risk-to-Reward) level.
How It Works:
Manual Entry Input
You enter your Entry Price and select Buy/Sell in the settings.
This flexibility allows backtesting or live trade tracking.
Initial Setup
Default SL: 50 ticks(Tested on us30,but works on any pair you just need to adjust SL)
TP for reference: 4R — can be used for benchmarking, but we don't limit profits with a hard TP.
Trailing Logic
Once price reaches 3R in profit:
The SL begins trailing.
It starts at 2R, keeping a 1R cushion behind the max profit.
For every 0.5R gain, SL also moves up by 0.5R:
Example: At 3.5R → SL is at 2.5R
At 5.0R → SL is at 4.0R
This trailing continues until the SL is hit or the trend exhausts.
Chart Features
🟧 Entry Line
🔴 Initial SL
🟢 Reference TP (4R, optional)
🟣 Dynamic Trailing SL
🏷️ Labels for Entry & SL levels
Guntavnook Katta - Fair Value PROOverview:
This script is designed to help long-term investors estimate the fair value of a stock using a combination of fundamental financial metrics and a proprietary multi-factor scoring model. It is especially useful for those who wish to assess whether a stock is undervalued or overvalued based on key fundamentals and recent price behavior.
This script is suitable for stocks, and is best applied on the Daily timeframe.
Purpose:
Many investors rely on Price-to-Earnings (PE) ratios, but not all businesses deserve the same PE due to differences in quality, growth visibility, brand strength, and financial health. This tool attempts to automate the estimation of a fair PE ratio for each company, based on key qualitative and quantitative metrics.
Core Logic:
The script takes the EPS (Earnings Per Share) for the recent financial year from TradingView’s built-in fundamental database and multiplies it by a calculated ideal PE ratio, derived from scoring logic applied to the following parameters:
Financial Parameters Considered:
ROCE (Return on Capital Employed): Indicates how efficiently a company is using its capital to generate profits. Higher ROCE generally reflects strong capital allocation.
ROE (Return on Equity): Shows how effectively the company uses shareholders’ equity. A high ROE may imply strong profitability.
Dividend Yield: Companies that share profits with shareholders via dividends are generally viewed favorably, especially if the yield is sustainable.
Promoter Holding: Higher promoter holding reflects confidence of the founders or promoters in the business. Companies with very low promoter holding might raise governance concerns.
Debt to Equity Ratio: Measures financial risk. Companies with low debt are generally safer, except for banks and NBFCs where high debt is normal.
Sales Growth (5 Years): Reflects business expansion. Consistent growth signals strong demand and operational scalability.
Profit Growth (5 Years): Indicates the company’s ability to grow net earnings over time. High profit growth with low sales growth can sometimes indicate improved margins.
Brand Value: Users can assign qualitative ratings to the company's brand strength, which significantly affects valuation.
Professional Management: If promoter holding is 0%, the company may be professionally or institutionally managed, which adds value in many sectors.
Special Edge: A user-defined optional scoring input for businesses with a strong moat, monopoly, or hard-to-replicate model.
Each of these parameters contributes positively or negatively to the Ideal PE score, which is then used to compute the Fair Value = EPS × Ideal PE.
Why This Scoring Approach?
In fast-moving and diverse market environments, the concept of fair value cannot be treated as a one-size-fits-all number. Traditional valuation models often apply a static PE ratio across stocks, overlooking the individual nuances that define each business. However, real-world investing calls for a more contextual approach—one that acknowledges the dynamic nature of companies, sectors, and economic cycles.
This script attempts to address that gap by offering a systematic way to estimate the fair price of a stock, based on both qualitative and quantitative parameters. The scoring logic is derived from concepts and patterns observed in popular books on fundamental investing and valuation. It encapsulates capital efficiency, ownership structure, growth performance, and brand power—all of which influence a company’s ability to command a premium valuation. The goal is not to suggest decisions but to enable custom, data-supported valuation assessments.
User Instructions:
Apply the script to a stock chart using Daily timeframe.
Open the indicator Settings Panel.
Choose either:
Auto-calculated PE: Let the script determine Ideal PE from scoring inputs.
Manual PE: If you're confident in the fair PE value, input it directly.
Hover over (i) icons in settings for explanation of each input.
Most inputs like ROE, ROCE, D/E ratio, etc., can be found from official filings, annual reports, or financial platforms.
Overbought & Oversold Signals:
This script also provides technical signals based on price deviation from fair value:
Uses RSI-based crossover logic in combination with user-defined price deviation thresholds.
Users can enable/disable signals independently.
Thresholds define how far above/below fair value the stock should move before a signal is triggered.
For example:
If the price moves above the fair value by a percentage equal to or greater than the Overbought threshold set by the user and the RSI crosses below 70, a red Overbought label appears.
If the price drops below the fair value by a percentage equal to or greater than the Oversold threshold set by the user and the RSI crosses above 30, a green Oversold label appears.
You can use the average deviation values displayed in the info table to determine suitable threshold levels based on historical price behavior.
Why RSI?
The Relative Strength Index (RSI) is a widely accepted momentum indicator used to assess whether a stock is overbought or oversold based on recent price performance. In this script, RSI serves as a reliable trigger mechanism when combined with fair value deviations. While the fair value estimation captures long-term fundamentals, RSI helps identify short-term extremes in price action. By using RSI crossovers, the script ensures signals are technically validated and not triggered solely by deviation, thus improving accuracy.
Visual Aids:
The green line shows the calculated Fair Value.
Candle colors:
Red: RSI ≥ 70
Green: RSI ≤ 30
Yellow: Neutral zone
An info table at the top-right displays:
Ideal PE
Current PE (based on FY EPS)
Calculated Fair Value
Avg Upper and Lower Price Deviation % from Fair Value
Note:
This tool is primarily optimized for evaluating Indian stocks, especially those listed on NSE/BSE, where metrics like promoter holding and ROCE are commonly used.
Disclaimer:
This script is intended for educational and research purposes only. It is not investment advice. The logic is based on publicly available data and scoring heuristics designed for learning and valuation awareness.
Momentum Volume Divergence (MVD) EnhancedMomentum Volume Divergence (MVD) Enhanced is a powerful indicator that detects price-momentum divergences and momentum suppression for reversal trading. Optimized for XRP on 1D charts, it features dynamic lookbacks, ATR-adjusted thresholds, and SMA confirmation. Signals include strong divergences (triangles) and suppression warnings (crosses). Includes a detailed user guide—try it out and share your feedback!
Setup: Add to XRP 1D chart with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA crossovers. See full guide for details!
Disclaimer: This indicator is for educational purposes only, not financial advice. Trading involves risk—use at your discretion.
Momentum Volume Divergence (MVD) Enhanced Indicator User Guide
Version: Pine Script v6
Designed for: TradingView
Recommended Use: XRP on 1-day (1D) chart
Date: March 18, 2025
Author: Herschel with assistance from Grok 3 (xAI)
Overview
The Momentum Volume Divergence (MVD) Enhanced indicator is a powerful tool for identifying price-momentum divergences and momentum suppression patterns on XRP’s 1-day (1D) chart. Plotted below the price chart, it provides clear visual signals to help traders spot potential reversals and trend shifts.
Purpose
Detect divergences between price and momentum for buy/sell opportunities.
Highlight momentum suppression as warnings of fading trends.
Offer actionable trading signals with intuitive markers.
Indicator Components
Main Plot
Volume-Weighted Momentum (vw_mom): Blue line showing momentum adjusted by volume.
Above 0 = bullish momentum.
Below 0 = bearish momentum.
Zero Line: Gray dashed line at 0, separating bullish/bearish zones.
Key Signals
Strong Bearish Divergence:
Marker: Red triangle at the top.
Meaning: Price makes a higher high, but momentum weakens, confirmed by a drop below the 5-day SMA.
Action: Potential sell/short signal.
Strong Bullish Divergence:
Marker: Green triangle at the bottom.
Meaning: Price makes a lower low, but momentum strengthens, confirmed by a rise above the 5-day SMA.
Action: Potential buy/long signal.
Bearish Suppression:
Marker: Orange cross at the top + red background.
Meaning: Strong bullish momentum with low volume in a volume downtrend, suggesting fading strength.
Action: Warning to avoid longs or exit early.
Bullish Suppression:
Marker: Yellow cross at the bottom + green background.
Meaning: Strong bearish momentum with low volume in a volume uptrend, suggesting fading weakness.
Action: Warning to avoid shorts or exit early.
Debug Plots (Optional)
Volume Ratio: Gray line (volume vs. its MA) vs. yellow line (threshold).
Momentum Threshold: Purple lines (positive/negative momentum cutoffs).
Smoothed Momentum: Orange line (raw momentum).
Confirmation SMA: Purple line (price trend confirmation).
Labels
Text labels (e.g., "Bear Div," "Bull Supp") mark detected patterns.
How to Use the Indicator
Step-by-Step Trading Process
1. Monitor the Chart
Load your XRP 1D chart with the indicator applied.
Observe the blue vw_mom line and signal markers.
2. Spot a Signal
Primary Signals: Look for red triangles (strong_bear) or green triangles (strong_bull).
Warnings: Note orange crosses (suppression_bear) or yellow crosses (suppression_bull).
3. Confirm the Signal
For Strong Bullish Divergence (Buy):
Green triangle appears.
Price closes above the 5-day SMA (purple line) and a recent swing high.
Optional: Volume ratio (gray line) exceeds the threshold (yellow line).
For Strong Bearish Divergence (Sell):
Red triangle appears.
Price closes below the 5-day SMA and a recent swing low.
Optional: Volume ratio (gray line) falls below the threshold (yellow line).
4. Enter the Trade
Long:
Buy at the close of the signal bar.
Stop loss: Below the recent swing low or 2 × ATR(14) below entry.
Short:
Sell/short at the close of the signal bar.
Stop loss: Above the recent swing high or 2 × ATR(14) above entry.
5. Manage the Trade
Take Profit:
Aim for a 2:1 or 3:1 risk-reward ratio (e.g., risk $0.05, target $0.10-$0.15).
Or exit when an opposite suppression signal appears (e.g., orange cross for longs).
Trailing Stop:
Move stop to breakeven after a 1:1 RR move.
Trail using the 5-day SMA or 2 × ATR(14).
Early Exit:
Exit if a suppression signal appears against your position (e.g., suppression_bull while short).
6. Filter Out Noise
Avoid trades if a suppression signal precedes a divergence within 2-3 days.
Optional: Add a 50-day SMA on the price chart:
Longs only if price > 50-SMA.
Shorts only if price < 50-SMA.
Example Trades (XRP 1D)
Bullish Trade
Signal: Green triangle (strong_bull) at $0.55.
Confirmation: Price closes above 5-SMA and $0.57 high.
Entry: Buy at $0.58.
Stop Loss: $0.53 (recent low).
Take Profit: $0.63 (2:1 RR) or exit on suppression_bear.
Outcome: Price hits $0.64, exit at $0.63 for profit.
Bearish Trade
Signal: Red triangle (strong_bear) at $0.70.
Confirmation: Price closes below 5-SMA and $0.68 low.
Entry: Short at $0.67.
Stop Loss: $0.71 (recent high).
Take Profit: $0.62 (2:1 RR) or exit on suppression_bull.
Outcome: Price drops to $0.61, exit at $0.62 for profit.
Tips for Success
Combine with Price Levels:
Use support/resistance zones (e.g., weekly pivots) to confirm entries.
Monitor Volume:
Rising volume (gray line above yellow) strengthens signals.
Adjust Sensitivity:
Too many signals? Increase div_strength_threshold to 0.7.
Too few signals? Decrease to 0.3.
Backtest:
Review 20-30 past signals on XRP 1D to assess performance.
Avoid Choppy Markets:
Skip signals during low volatility (tight price ranges).
Troubleshooting
No Signals:
Lower div_strength_threshold to 0.3 or mom_threshold_base to 0.2.
Check if XRP’s volatility is unusually low.
False Signals:
Increase sma_confirm_length to 7 or add a 50-SMA filter.
Indicator Not Loading:
Ensure the script compiles without errors.
Customization (Optional)
Change Colors: Edit color.* values (e.g., color.red to color.purple).
Add Alerts: Use TradingView’s alert menu for "Strong Bearish Divergence Confirmed," etc.
Test Other Assets: Experiment with BTC or ETH, adjusting inputs as needed.
Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion.
Setup: Use on XRP 1D with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA cross. Stop: 2x ATR(14). Profit: 2:1 RR or suppression exit. Full guide available separately!
AO Smart Scalper – 5M Dynamic SL Edition📈 AO Signals with Fixed and Dynamic SL – Optimized for 5-Minute Charts 📉
This indicator is built for 5-minute timeframe trading, combining powerful momentum signals from the Awesome Oscillator (AO) with both Fixed and Dynamic Stop Loss (SL) levels to enhance trade management and risk control.
✅ Buy/Sell Signals:
The indicator generates clear BUY and SELL signals based on the AO crossing above or below the zero line, helping traders capture momentum shifts early.
🛑 Fixed Stop Loss:
Each trade signal comes with a Fixed SL, calculated based on the high (for shorts) or low (for longs) of the previous candle, with a customizable percentage offset. This SL is plotted with a red line, providing a clear initial risk level.
⚡ Dynamic Stop Loss: Continuous Presence, Strategic Use:
A secondary Dynamic SL line is plotted, which is continuously present on the chart. This dynamic level responds to market conditions and can serve as a trailing stop or key decision point.
💡 Recommended Use: It is recommended to actively start using the Dynamic SL once the trade has moved into profit. This allows protecting obtained profits and minimizing the risk of losses in case of a market reversal.
🛡️ Enhanced Dynamic Stop-Loss Strategy:
🔒 Initial Protection: Utilize the Fixed SL as the initial stop-loss, placed below relevant lows (for longs) or above relevant highs (for shorts), or as provided by the fixed SL indicator.
🛤️ Dynamic Tracking:
🟢 Long Trades: Once in profit, the Dynamic SL will dynamically adjust, moving upwards as higher lows are formed, effectively trailing the price and securing profits.
🔴 Short Trades: Conversely, in short trades, once in profit, the Dynamic SL will move downwards as lower highs are formed, protecting gains.
🔄 Alternatively the dynamic stop loss will follow the dynamic SL line provided by the indicator.
🚪 Exiting Trades: When the price crosses below the Dynamic SL line in a LONG trade, or above it in a SHORT trade, the recommended action is to exit the trade.
↩️ Re-entry Consideration: You may consider re-entering only if the price clearly returns above the Dynamic SL (for longs) or below it (for shorts).
⚠️ IMPORTANT - 5-Minute Strategy Guidance ⏱️
This tool is specifically optimized for the 5-minute timeframe. This approach helps filter out weak setups and maintain discipline in volatile market conditions.
✨ Additional Features:
👁️ Visual and editable SL levels
📊 200-period SMA for trend context
💻 Simple and effective interface for intraday trading setups
🎯 Ideal for traders seeking a clean, rule-based system that combines momentum entry signals with layered stop loss protection.
🔑 Key Changes:
It was emphasized that the Dynamic SL is always present, but its active use is recommended once the trade is in profit.
It was clarified the use of the Fixed SL, giving the option to use the one provided by the indicator, or to place it according to the price action.
Mile Runner - Swing Trade LONGMile Runner - Swing Trade LONG Indicator - By @jerolourenco
Overview
The Mile Runner - Swing Trade LONG indicator is designed for swing traders who focus on LONG positions in stocks, BDRs (Brazilian Depositary Receipts), and ETFs. It provides clear entry signals, stop loss, and take profit levels, helping traders identify optimal buying opportunities with a robust set of technical filters. The indicator is optimized for daily candlestick charts and combines multiple technical analysis tools to ensure high-probability trades.
Key Features
Entry Signals: Visualized as green triangles below the price bars, indicating a potential LONG entry.
Stop Loss and Take Profit Levels: Automatically plotted on the chart for easy reference.
Stop Loss: Based on the most recent pivot low (support level).
Take Profit: Calculated using a Fibonacci-based projection from the entry price to the stop loss.
Trend and Momentum Filters: Ensures trades align with the prevailing trend and have sufficient momentum.
Volume and Volatility Confirmation: Verifies market interest and price movement potential.
How It Works
The indicator uses a combination of technical tools to filter and confirm trade setups:
Exponential Moving Averages (EMAs):
A short EMA (default: 9 periods) and a long EMA (default: 21 periods) identify the trend.
A bullish crossover (EMA9 crosses above EMA21) signals a potential upward trend.
Money Flow Index (MFI):
Confirms buying pressure when MFI > 50.
Average True Range (ATR):
Ensures sufficient volatility by checking if ATR exceeds its 20-period moving average.
Volume:
Confirms market interest when volume exceeds its 20-period moving average.
Pivot Lows:
Identifies recent support levels (pivot lows) to set the stop loss.
Ensures the pivot low is recent (within the last 10 bars by default).
Additional Trend Filter:
Confirms the long EMA is rising, reinforcing the bullish trend.
Inputs and Customization
The indicator is highly customizable, allowing traders to tailor it to their strategies:
EMA Periods: Adjust the short and long EMA lengths.
ATR and MFI Periods: Modify lookback periods for volatility and momentum.
Pivot Lookback: Control the sensitivity of pivot low detection.
Fibonacci Level: Adjust the Fibonacci retracement level for take profit.
Take Profit Multiplier: Fine-tune the aggressiveness of the take profit target.
Max Pivot Age: Set the maximum bars since the last pivot low for relevance.
Usage Instructions
Apply the Indicator:
Add the "Mile Runner - Swing Trade LONG" indicator to your TradingView chart.
Best used on daily charts for swing trading.
Look for Entry Signals:
A green triangle below the price bar signals a potential LONG entry.
Set Stop Loss and Take Profit:
Stop Loss: Red dashed line indicating the stop loss level.
Take Profit: Purple dashed line showing the take profit level.
Monitor the Trade:
The entry price is marked with a green dashed line for reference.
Adjust trade management based on the plotted levels.
Set Alerts:
Use the built-in alert condition to get notified of new LONG entry signals.
Important Notes
For LONG Positions Only : Designed exclusively for swing trading LONG positions.
Timeframe: Optimized for daily charts but can be tested on other timeframes.
Asset Types: Works best with stocks, BDRs, and ETFs.
Risk Management: Always align stop loss and take profit levels with your risk tolerance.
Why Use Mile Runner?
The Mile Runner indicator simplifies swing trading by integrating trend, momentum, volume, and volatility filters into one user-friendly tool. It helps traders:
Identify high-probability entry points.
Establish clear stop loss and take profit levels.
Avoid low-volatility or low-volume markets.
Focus on assets with strong buying pressure and recent support.
By following its signals and levels, traders can make informed decisions and enhance their swing trading performance. Customize the inputs and test it on your favorite assets—happy trading!
Cash And Carry Arbitrage BTC Compare Month 6 by SeoNo1Detailed Explanation of the BTC Cash and Carry Arbitrage Script
Script Title: BTC Cash And Carry Arbitrage Month 6 by SeoNo1
Short Title: BTC C&C ABT Month 6
Version: Pine Script v5
Overlay: True (The indicators are plotted directly on the price chart)
Purpose of the Script
This script is designed to help traders analyze and track arbitrage opportunities between the spot market and futures market for Bitcoin (BTC). Specifically, it calculates the spread and Annual Percentage Yield (APY) from a cash-and-carry arbitrage strategy until a specific expiry date (in this case, June 27, 2025).
The strategy helps identify profitable opportunities when the futures price of BTC is higher than the spot price. Traders can then buy BTC in the spot market and short BTC futures contracts to lock in a risk-free profit.
1. Input Settings
Spot Symbol: The real-time BTC spot price from Binance (BTCUSDT).
Futures Symbol: The BTC futures contract that expires in June 2025 (BTCUSDM2025).
Expiry Date: The expiration date of the futures contract, set to June 27, 2025.
These inputs allow users to adjust the symbols or expiry date according to their trading needs.
2. Price Data Retrieval
Spot Price: Fetches the latest closing price of BTC from the spot market.
Futures Price: Fetches the latest closing price of BTC futures.
Spread: The difference between the futures price and the spot price (futures_price - spot_price).
The spread indicates how much higher (or lower) the futures price is compared to the spot market.
3. Time to Maturity (TTM) and Annual Percentage Yield (APY) Calculation
Current Date: Gets the current timestamp.
Time to Maturity (TTM): The number of days left until the futures contract expires.
APY Calculation:
Formula:
APY = ( Spread / Spot Price ) x ( 365 / TTM Days ) x 100
This represents the annualized return from holding a cash-and-carry arbitrage position if the trader buys BTC at the spot price and sells BTC futures.
4. Display Information Table on the Chart
A table is created on the chart's top-right corner showing the following data:
Metric: Labels such as Spread and APY
Value: Displays the calculated spread and APY
The table automatically updates at the latest bar to display the most recent data.
5. Alert Condition
This sets an alert condition that triggers every time the script runs.
In practice, users can modify this alert to trigger based on specific conditions (e.g., APY exceeds a threshold).
6. Plotting the APY and Spread
APY Plot: Displays the annualized yield as a blue line on the chart.
Spread Plot: Visualizes the futures-spot spread as a red line.
This helps traders quickly identify arbitrage opportunities when the spread or APY reaches desirable levels.
How to Use the Script
Monitor Arbitrage Opportunities:
A positive spread indicates a potential cash-and-carry arbitrage opportunity.
The larger the APY, the more profitable the arbitrage opportunity could be.
Timing Trades:
Execute a buy on the BTC spot market and simultaneously sell BTC futures when the APY is attractive.
Close both positions upon futures contract expiry to realize profits.
Risk Management:
Ensure you have sufficient margin to hold both positions until expiry.
Monitor funding rates and volatility, which could affect returns.
Conclusion
This script is an essential tool for traders looking to exploit price discrepancies between the BTC spot market and futures market through a cash-and-carry arbitrage strategy. It provides real-time data on spreads, annualized returns (APY), and visual alerts, helping traders make informed decisions and maximize their profit potential.
Liquitive Buy/Sell Dollar AveragerLiquitive Buy/Sell Dollar Averager Indicator
The "Liquitive Buy/Sell Dollar Averager" is a versatile trading tool designed for intraday and multi-timeframe analysis, combining advanced range-bound calculations, RSI normalization, volume spikes, and candle pattern recognition to identify optimal buy and sell conditions. This indicator is particularly suitable for traders employing strategies that focus on dollar-cost averaging, position scaling, and systematic buy/sell decision-making.
Key Features:
Adaptive RSI-Based Levels:
Dynamically calculates inner bounds (IB) and outer bounds (OB) using RSI and price ranges, helping to identify overbought and oversold conditions relative to the price action.
Normalizes RSI values to the price range for seamless visualization overlaid on the chart.
Volume and Candle Analysis:
Detects significant volume spikes relative to a moving average, signaling increased market activity.
Identifies spiking green/red candles to capture momentum-driven price movements.
Dynamic Support and Resistance:
Calculates and plots support and resistance levels based on recent swing highs and lows.
Median and boundary lines help visualize key price levels for decision-making.
Profitability Check:
Buy and Sell Signals:
Checks profitability thresholds based on percentage gains/losses.
Incorporates logic for "time to buy" and "time to sell" using target profit margins.
Implements average move percentage to define realistic thresholds for buy/sell actions.
Time-Based Trading Restrictions:
Configures trading logic to disallow trades after a specific time (e.g., 3:40 PM for intraday sessions).
Ensures logical entry and exit decisions are only made within active trading hours.
Color-Coded Visualization:
Background colors dynamically shift between green (bullish), red (bearish), and neutral, depending on RSI and price position relative to the inner bounds.
Opacity of the background adjusts based on normalized RSI differences to provide a visual cue of market strength.
Customizable Parameters:
Allows user input for key settings like lookback periods, RSI length, percent ranges, volume thresholds, and transparency levels, enabling flexible configuration tailored to individual strategies.
Actionable Alerts and Signals:
Plots "Open Position", "Add to Position", and "Close Position" markers directly on the chart, making it easy to follow systematic trading rules.
How It Works:
Buy Signals:
Triggered when price conditions, volume spikes, and RSI-based thresholds align with profitability metrics.
Designed for dollar-cost averaging, identifying opportunities to add to long positions or open new positions.
Sell Signals:
Evaluates profitability conditions to identify when to close or scale out of positions.
Incorporates real-time evaluation of market momentum and profitability.
Puell Multiple BTC | JeffreyTimmermansThe Puell Multiple is a metric that assesses the relationship between mining profitability and market cycles. It is calculated by comparing the daily value of newly issued coins (USD) to the 365-day moving average of daily coin issuance (USD).
This indicator works best on the 1D BTC Chart. When interpreting the Puell Multiple, it can generally be understood as follows:
High values indicate that miner profitability is significantly higher than the yearly average. This may lead to an increased incentive for miners to sell off their holdings, putting additional selling pressure on the market.
Low values suggest that miner profitability is lower than the yearly average. In this case, miners might experience financial strain, causing some to reduce their hash power by shutting down mining rigs. This, in turn, can reduce the number of coins being sold into the market, as remaining miners need to liquidate fewer coins to maintain operations, thereby decreasing the impact on the liquid supply.
The Puell Multiple is a metric used primarily in the cryptocurrency space, specifically for Bitcoin, to assess whether Bitcoin is overvalued or undervalued in relation to its mining rewards. It helps to gauge the profitability of miners and, by extension, to assess market conditions.
Use:
This Puell Multiple is invented for Long-Term, Trend Following Systems.
The Puell Multiple trend can be visualized through the color of the bars, which represents the direction of the trend, while the background indicates the strength of that trend.
Bar Color: The color of the bars typically changes to reflect whether the trend is bullish or bearish. For example, green bars may indicate a strong bullish trend, while red bars signal a bearish or declining trend. The color coding helps to quickly interpret the market's overall movement in relation to mining profitability.
Background Color: The background of the chart is used to reflect the strength of the trend. A darker or more intense background may signify a stronger trend, indicating that the market conditions are more pronounced, while a lighter background can suggest a weaker or more uncertain trend, showing less certainty in the market’s direction.
Together, the combination of bar color and background provides a clearer picture of both the trend's direction and its strength, making it easier to assess potential market behavior based on miner profitability and market cycles.
Puell Multiple and Moving Average: They can be used as an extra tool to confirm the bullish or bearish trend. When the Puell Multiple is above the Moving Average, this will suggest and confirm that the trend is bullish.
How you score this for your own systems is up to you.
-Jeffrey
Puell Multiple BTC | JeffreyTimmermansThe Puell Multiple is a metric that assesses the relationship between mining profitability and market cycles. It is calculated by comparing the daily value of newly issued coins (USD) to the 365-day moving average of daily coin issuance (USD).
This indicator works best on the 1D BTC Chart. When interpreting the Puell Multiple, it can generally be understood as follows:
High values indicate that miner profitability is significantly higher than the yearly average. This may lead to an increased incentive for miners to sell off their holdings, putting additional selling pressure on the market.
Low values suggest that miner profitability is lower than the yearly average. In this case, miners might experience financial strain, causing some to reduce their hash power by shutting down mining rigs. This, in turn, can reduce the number of coins being sold into the market, as remaining miners need to liquidate fewer coins to maintain operations, thereby decreasing the impact on the liquid supply.
The Puell Multiple is a metric used primarily in the cryptocurrency space, specifically for Bitcoin, to assess whether Bitcoin is overvalued or undervalued in relation to its mining rewards. It helps to gauge the profitability of miners and, by extension, to assess market conditions.
Use:
This Puell Multiple is invented for Long-Term, Trend Following Systems.
The Puell Multiple trend can be visualized through the color of the bars, which represents the direction of the trend, while the background indicates the strength of that trend.
Bar Color: The color of the bars typically changes to reflect whether the trend is bullish or bearish. For example, green bars may indicate a strong bullish trend, while red bars signal a bearish or declining trend. The color coding helps to quickly interpret the market's overall movement in relation to mining profitability.
Background Color: The background of the chart is used to reflect the strength of the trend. A darker or more intense background may signify a stronger trend, indicating that the market conditions are more pronounced, while a lighter background can suggest a weaker or more uncertain trend, showing less certainty in the market’s direction.
Together, the combination of bar color and background provides a clearer picture of both the trend's direction and its strength, making it easier to assess potential market behavior based on miner profitability and market cycles.
Puell Multiple and Moving Average: They can be used as an extra tool to confirm the bullish or bearish trend. When the Puell Multiple is above the Moving Average, this will suggest and confirm that the trend is bullish.
How you score this for your own systems is up to you.
-Jeffrey
Puell Multiple BTC | JeffreyTimmermansThe Puell Multiple is a metric that assesses the relationship between mining profitability and market cycles. It is calculated by comparing the daily value of newly issued coins (USD) to the 365-day moving average of daily coin issuance (USD).
This indicator works best on the 1D BTC Chart. When interpreting the Puell Multiple, it can generally be understood as follows:
High values indicate that miner profitability is significantly higher than the yearly average. This may lead to an increased incentive for miners to sell off their holdings, putting additional selling pressure on the market.
Low values suggest that miner profitability is lower than the yearly average. In this case, miners might experience financial strain, causing some to reduce their hash power by shutting down mining rigs. This, in turn, can reduce the number of coins being sold into the market, as remaining miners need to liquidate fewer coins to maintain operations, thereby decreasing the impact on the liquid supply.
The Puell Multiple is a metric used primarily in the cryptocurrency space, specifically for Bitcoin, to assess whether Bitcoin is overvalued or undervalued in relation to its mining rewards. It helps to gauge the profitability of miners and, by extension, to assess market conditions.
Use:
This Puell Multiple is invented for Long-Term, Trend Following Systems.
The Puell Multiple trend can be visualized through the color of the bars, which represents the direction of the trend, while the background indicates the strength of that trend.
Bar Color: The color of the bars typically changes to reflect whether the trend is bullish or bearish. For example, green bars may indicate a strong bullish trend, while red bars signal a bearish or declining trend. The color coding helps to quickly interpret the market's overall movement in relation to mining profitability.
Background Color: The background of the chart is used to reflect the strength of the trend. A darker or more intense background may signify a stronger trend, indicating that the market conditions are more pronounced, while a lighter background can suggest a weaker or more uncertain trend, showing less certainty in the market’s direction.
Together, the combination of bar color and background provides a clearer picture of both the trend's direction and its strength, making it easier to assess potential market behavior based on miner profitability and market cycles.
Puell Multiple and Moving Average: They can be used as an extra tool to confirm the bullish or bearish trend. When the Puell Multiple is above the Moving Average, this will suggest and confirm that the trend is bullish.
How you score this for your own systems is up to you.
-Jeffrey
Multi Fibonacci Supertrend with Signals【FIbonacciFlux】Multi Fibonacci Supertrend with Signals (MFSS)
Overview
The Multi Fibonacci Supertrend with Signals (MFSS) is an advanced technical analysis tool that combines multiple Supertrend indicators using Fibonacci ratios to identify trend directions and potential trading opportunities.
Key Features
1. Fibonacci-Based Supertrend Levels
* Factor 1 (Weak) : 0.618 - The golden ratio
* Factor 2 (Medium) : 1.618 - The Fibonacci ratio
* Factor 3 (Strong) : 2.618 - The extension ratio
2. Visual Components
* Multi-layered Trend Lines
* Different line weights for easy identification
* Progressive transparency from Factor 1 to Factor 3
* Color-coded trend directions (Green for bullish, Red for bearish)
* Dynamic Fill Areas
* Gradient fills between price and trend lines
* Visual representation of trend strength
* Automatic color adjustment based on trend direction
* Signal Indicators
* Clear BUY/SELL labels on chart
* Position-adaptive signal placement
* High-visibility color scheme
3. Signal Generation Logic
The system generates signals based on two key conditions:
* Primary Condition :
* BUY : Price crossunder Supertrend2 (Factor 1.618)
* SELL : Price crossover Supertrend2 (Factor 1.618)
* Confirmation Filter :
* Signals only trigger when Supertrend3 confirms the trend direction
* Reduces false signals in volatile markets
Technical Details
Input Parameters
* ATR Period : 10 (default)
* Customizable for different market conditions
* Affects sensitivity of all Supertrend levels
* Factor Settings :
* All factors are customizable
* Default values based on Fibonacci sequence
* Minimum value: 0.01
* Step size: 0.01
Alert System
* Built-in alert conditions
* Customizable alert messages
* Real-time notification support
Use Cases
* Trend Trading
* Identify strong trend directions
* Filter out weak signals
* Confirm trend continuations
* Risk Management
* Multiple trend levels for stop-loss placement
* Clear entry and exit signals
* Trend strength visualization
* Market Analysis
* Multi-timeframe analysis capability
* Trend strength assessment
* Market structure identification
Benefits
* Reliability
* Based on proven Supertrend algorithm
* Enhanced with Fibonacci mathematics
* Multiple confirmation levels
* Clarity
* Clear visual signals
* Easy-to-interpret interface
* Reduced noise in signal generation
* Flexibility
* Customizable parameters
* Adaptable to different markets
* Suitable for various trading styles
Performance Considerations
* Optimized code structure
* Efficient calculation methods
* Minimal resource usage
Installation and Usage
Setup
* Add indicator to chart
* Adjust parameters if needed
* Enable alerts as required
Best Practices
* Use with other confirmation tools
* Adjust factors based on market volatility
* Consider timeframe appropriateness
Backtesting Results and Strategy Performance
This indicator is specifically designed for pullback trading with optimized risk-reward ratios in trend-following strategies. Below are the detailed backtesting results from our proprietary strategy implementation:
BTCUSDT Performance (Binance)
* Test Period: Approximately 7 years
* Risk-Reward Ratio: 2:1
* Take Profit: 8%
* Stop Loss: 4%
Key Metrics (BTCUSDT):
* Net Profit: +2,579%
* Total Trades: 551
* Win Rate: 44.8%
* Profit Factor: 1.278
* Maximum Drawdown: 42.86%
ETHUSD Performance (Binance)
* Risk-Reward Ratio: 4.33:1
* Take Profit: 13%
* Stop Loss: 3%
Key Metrics (ETHUSD):
* Net Profit: +8,563%
* Total Trades: 581
* Win Rate: 32%
* Profit Factor: 1.32
* Maximum Drawdown: 55%
Strategy Highlights:
* Optimized for pullback trading in strong trends
* Focus on high risk-reward ratios
* Proven effectiveness in major cryptocurrency pairs
* Consistent performance across different market conditions
* Robust profit factor despite moderate win rates
Note: These results are from our proprietary strategy implementation and should be used as reference only. Individual results may vary based on market conditions and implementation.
Important Considerations:
* The strategy demonstrates strong profitability despite lower win rates, emphasizing the importance of proper risk-reward ratios
* Higher drawdowns are compensated by significant overall returns
* The system shows adaptability across different cryptocurrencies with consistent profit factors
* Results suggest optimal performance in volatile crypto markets
Real Trading Examples
BTCUSDT 4-Hour Chart Analysis
Example of pullback strategy implementation on Bitcoin, showing clear trend definition and entry points
ETHUSDT 4-Hour Chart Analysis
Ethereum chart demonstrating effective signal generation during strong trends
BTCUSDT Detailed Signal Example (15-Minute Scalping)
Close-up view of signal generation and trend confirmation process on 15-minute timeframe, demonstrating the indicator's effectiveness for scalping operations
Chart Analysis Notes:
* Green and red zones clearly indicate trend direction
* Multiple timeframe confirmation visible through different Supertrend levels
* Clear entry signals during pullbacks in established trends
* Precise stop-loss placement opportunities below support levels
Implementation Guidelines:
* Wait for main trend confirmation from Factor 3 (2.618)
* Enter trades on pullbacks to Factor 2 (1.618)
* Use Factor 1 (0.618) for fine-tuning entry points
* Place stops below the relevant Supertrend level
Footnotes:
* Charts provided are from Binance exchange, using both 4-hour and 15-minute timeframes
* Trading view screenshots captured during actual market conditions
* Indicators shown: Multi Fibonacci Supertrend with all three factors
* Time period: Recent market activity showing various market conditions
Important Notice:
These charts are for educational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management.
Disclaimer
This indicator is for informational purposes only. Past performance is not indicative of future results. Always conduct proper risk management and due diligence.
License
Open source under MIT License
Author's Note
Contributions and suggestions for improvement are welcome. Please feel free to fork and enhance.
