PairTradingSignalsPair Trading Signals (PTS)
This indicator implements a mean-reversion strategy for pairs trading, focusing on divergences between the chart's primary symbol (e.g., QQQ for tech exposure) and a user-specified inverse or correlated secondary symbol (default: SPY for broad market proxy). It generates long-only entry and exit signals on the primary asset based on statistical deviations in their relative pricing, without requiring short positions or direct trading of the secondary symbol.
Core Concepts
Pairs Mean Reversion: The strategy exploits temporary mispricings in cointegrated assets. When the primary asset becomes "cheap" relative to the secondary (oversold spread), it enters a long position expecting convergence. Exits occur when the spread reverts to neutral or overbought levels.
Spread & Z-Score: The raw spread is calculated as Primary Close - (Hedge Ratio × Secondary Close), with a fixed hedge ratio of 1.5 to approximate relative volatility (e.g., beta adjustment). This is normalized to a Z-score over a lookback period, measuring deviations in standard deviations from the historical mean. Bounds (default ±2.0) define oversold/overbought thresholds—common in statistical arbitrage for 95% confidence intervals assuming normality.
ATR-Based Risk Controls: Entry levels incorporate Average True Range (ATR, default 14-period RMA smoothing) to set dynamic take-profit (TP = Entry + Upper Bound × ATR) and stop-loss (SL = Entry - |Lower Bound| × ATR) levels, scaling to volatility.
Signal Logic
Buy (Long Entry): Triggers when the Z-score crosses above the lower bound (-2.0) after entering an oversold state (Z < lower bound). This signals undervaluation of the primary relative to the secondary.
Sell (Exit): Triggers when the Z-score crosses below the upper bound (2.0) after entering an overbought state (Z > upper bound). Optional strict TP/SL enforcement closes positions at predefined levels.
Signals appear as labeled shapes (green BUY below bar, red SELL above). Short horizontal boxes mark TP (green) and SL (red) for visual reference.
Backtesting & Performance Metrics
Simulation Period: Trades only within user-defined start/end dates (default: Jan 2020–Dec 2030).
Position Sizing: Fixed allocation based on initial capital × entry percentage (default 100%), capped by available equity to enforce risk limits. Supports full compounding if desired via code tweak.
Metrics Table: Displays net profit, ROI (including/excluding unrealized P&L), win rate, trade counts, closed capital, total equity, and open position details (shares or current value). Recent trades logged in a separate table.
Equity Floor: Prevents capital from going below zero, simulating real-world drawdown limits.
Usage Guidelines
Symbol Setup: Apply to the primary asset's chart (e.g., QQQ). Set "Inverse Ticker" to a negatively or positively correlated pair (e.g., SPY for market hedge).
Parameter Tuning: Increase lookback (20+) for smoother signals; widen bounds (±3.0) for fewer, higher-conviction trades. Lower entry % reduces risk.
Best Practices: Use on daily/4H timeframes for swing trades. Combine with overall market trend filters. Backtest across regimes (e.g., bull/bear) to validate.
Limitations: Assumes mean reversion holds; performs poorly in trending divergences. No commissions/slippage modeled—adjust initial capital accordingly.
This approach draws from classic pairs trading literature (e.g., Gatev et al.'s distance method), adapted for single-asset execution via Z-score thresholds. For optimal results, ensure the pair exhibits cointegration (test via Engle-Granger if customizing).
Portföy Yönetimi
🚀 Multi-Mean-Reversion Strategy -> PROFABIGHI_CAPITAL🌟 Overview
The Multi-Mean-Reversion Strategy → PROFABIGHI_CAPITAL is a confluence-driven counter-trend system that leverages market regime analysis , Z-score overextension detection , multi-layered RSI enhancements , and standard deviation bands to pinpoint reversion opportunities. It combines four signal codes with tunable modes (safe or speed) and directional controls , making it ideal for DCA timing by identifying undervalued pullbacks in trending markets for systematic averaging.
⚙️ Strategy Configuration
- Initial Capital : Starting equity for simulation and metric calculation
- Slippage Adjustment : Models trade execution costs for realistic performance
- Position Sizing : Allocates equity percentage per trade for balanced exposure
- Pyramiding Limit : Disabled to maintain single-entry discipline
- Order Timing : Processes on bar close for signal confirmation
- Margin Control : Zero leverage for both long and short positions
📅 Date Range Settings
- Date Filter Toggle : Enable to confine backtesting to selected periods
- Start Date Input : Defines the beginning for trade and analysis scope
- Range Enforcement : Limits new entries to within the timeframe
- Full History Option : Disables filter for complete dataset evaluation
📊 System Metrics Display
Performance Curve Choices:
- Strategy View : Overall execution path including open trades
- Equity Growth : Capital progression from closed positions
- Open Profit Overlay : Real-time unrealized performance
- Gross Profit Line : Total wins before deductions
- Net Profit Curve : Final returns after all costs
- Hidden Option : Removes curve for cleaner chart focus
Table Customization:
- Position Options : Anchors metrics in chart corners or centers
- Full Analytics : Detailed stats like win rate and drawdown
- Basic Summary : Essential figures such as total return
- No Table : Suppresses display for minimal interface
🎯 Strategy Settings
- Mode Selection : Safe demands full confluence; speed requires 75% for quicker setups
- Direction Preference : Both sides, long-only, or short-only for bias
- Tolerance Window : Bars allowed for signal lag to capture timing
- RSI Entry Thresholds : Oversold/overbought levels for long/short initiations
- RSI Exit Thresholds : Normalization bands for position unwinds
- Stdev Exit Multipliers : Volatility-scaled levels above/below mean for closures
🎛️ Signal Selection Settings
Long Entry Options:
- Code 1 Reversion : Activates regime detector for pullback entries
- Code 2 Oversold : Triggers on Z-score undervaluation extremes
- Code 3 RSI Low : Fires at enhanced RSI oversold readings
- Code 4 Buy Cross : Engages on lower SD band upward breaks
Short Entry Options:
- Code 1 Reversion : Uses regime signals for overextension shorts
- Code 2 Overbought : Alerts on Z-score overvaluation peaks
- Code 3 RSI High : Activates at enhanced RSI overbought
- Code 4 Sell Cross : Triggers on upper SD band downward breaks
Long Exit Options:
- Code 2 Overbought : Closes on valuation mean reversion
- Code 3 RSI Recovery : Exits at RSI normalization upward
- Code 4 Sell Cross : Unwinds on upper band resistance
- Stdev Threshold : Volatility-based stop above mean
Short Exit Options:
- Code 2 Oversold : Closes on downside exhaustion
- Code 3 RSI Rebound : Exits at RSI normalization downward
- Code 4 Buy Cross : Unwinds on lower band support
- Stdev Threshold : Volatility-based stop below mean
📈 Market Regime Detector (Code 1)
ADF Test Setup:
- Source and Sample Length : Price input and window for stationarity
- Lag Inclusion : Serial correlation adjustments
- Confidence Threshold : Critical values for reversion conclusion
- Hull Smoothing : Post-test trend filter
- Normalization Window : Bounds for scaling to -1/+1
Ljung-Box Test Setup:
- Autocorrelation Sample : Period for serial dependence
- Lag Count : Dependence levels tested
- Significance Cutoff : Hypothesis rejection level
- Normalization Period : Scaling for comparability
KPSS Test Setup:
- Unit Root Sample : Data window for trend stationarity
- Variance Lag : Long-run estimation truncation
- Normalization Horizon : Bounds adjustment
Phillips-Perron Test Setup:
- Non-Parametric Sample : Window with variance stabilization
- Hull Smoothing Layer : Trend refinement
- Normalization Span : Scaling period
ADX Setup:
- Trend Strength Smoothing : ADX calculation period
- Directional Length : +DI/-DI horizon
- Derivative Filter : Smoothing method and length
- Normalization Window : Scaling bounds
Choppiness Index Setup:
- Range vs. ATR Period : Consolidation measurement
- Normalization Lookback : Inverse scaling period
Wavelet Transform Setup:
- Haar Decomposition Window : Frequency separation scale
- Post-Transform Smoothing : Hull MA filter
- Normalization Period : Bounds for signal
Price Momentum Setup:
- Change Rate Horizon : Velocity calculation
- Hull Smoothing : Normalized filter
- Normalization Window : Scaling span
GARCH Volatility Setup:
- Model Initialization : Alpha/beta starting values
- EMA Volatility Length : Smoothing base
- Normalization Horizon : Scaling period
Yang Volatility Setup:
- Estimator Sample : Bars for analysis
- Volatility Components : Open-close-high-low integration
- Adaptive Smoothing : Volatility-responsive EMA
- Normalization Window : Bounds adjustment
Oscillator Confluence
- Regime Threshold : Minimum alignment for mean-reversion bias
📊 Z-Score Valuation (Code 2)
Core Functions:
- Rescale Normalization : Maps values to common ranges
- RSI Oscillator : Momentum deviation from equilibrium
- ROC Change Rate : Acceleration Z-score
- BB% Band Position : Volatility envelope placement
- CCI Cyclical Measure : Deviation from typical price
- Crosby Angle Ratio : Trend slope normalization
- Sharpe Efficiency : Annualized return/volatility
- Sortino Downside Focus : Negative deviation penalty
- Omega Gain/Loss Ratio : Probability-weighted outcomes
- Z-Score Core : Standard deviation from historical mean
Relationship Analysis:
- Price Correlations : Linear ties for each indicator
- Beta Sensitivities : Scaling by price impact
Composite Blending:
- Weight Schemes : Adaptive (correlation absolute) or equal
- Price Incorporation : 30% blend for direct alignment
- Fair Value Bands : Mean with ±1/2/3 sigma projections
🧠 Enhanced RSI (Code 3)
Signal Mode Choices:
- Smart Standard : Balanced thresholds for typical reversions
- Speed Trend-Follow : Adjusted levels for directional bias
Weighted RSI Components:
- Weight Basis : Volume, momentum, volatility, or reversion factors
- MA Smoothing Types : SMA to TEMA for delta filtering
- Core and Smoothing Periods : RSI and post-weight averaging
ML RSI Enhancement:
- KNN Activation : Pattern matching toggle
- Neighbor Count : Historical similar points averaged
- Pattern Window : Bars searched for matches
- Feature Dimensions : RSI momentum, std, regression, price mom
- Blend Ratio : ML vs. base RSI influence
Median RSI Filter:
- Price Median Period : Central tendency smoothing
- RSI on Median : Oscillator post-filtering
Composite Weighting:
- Variant Enables : Individual toggles for inclusion
- Proportional Blends : Custom weights auto-normalized
Visual Thresholds:
- Overbought/Oversold : Plotting levels for RSI extremes
📊 SD Bands (Code 4)
- WMA Base Length : Central line smoothing period
- Source Input : Price data for band construction
- Deviation Window : Stdev calculation horizon
📈 Signal Detection & Confirmation
Tolerance Checker:
- Scans recent bars for lagged signal validation
Code 1 Reversion:
- Activates below confluence threshold for regime bias
Code 2 Extremes:
- Flags wick hits on Z-derived over/undervaluation
Code 3 RSI Thresholds:
- Triggers at combined RSI entry/exit levels
Code 4 Band Crosses:
- Detects low/high violations of outer SD levels
Confluence Counters:
- Tallies active signals for mode-based requirements
📈 Entry & Exit Logic
Long Initiation:
- Blends reversion, oversold, RSI low, and buy cross
- Safe: Full match; speed: 75% alignment
Short Initiation:
- Merges reversion, overbought, RSI high, and sell cross
- Safe: Complete set; speed: Majority vote
Long Closure:
- Any of overbought, RSI recovery, sell cross, or stdev stop
Short Closure:
- Any of oversold, RSI rebound, buy cross, or stdev stop
Position Flow:
- Tracks state to prevent overlaps
- Closes opposites on new directions
- Date gates new entries only
🛡️ Risk Management
- Stdev-Based Stops : Mean plus/minus multiplier for volatility exits
- RSI Normalization : Thresholds for mean reversion unwinds
- Extreme Wick Alerts : Overextension triggers via Z-bands
- Signal-Driven Safeguards : Counter-trend closes on band tests
- Equity Proportionality : Fixed percentage risk per setup
📉 Visualization
- Position Tints : Faint green/red backgrounds during trades
- Confluence Dashboard : Real-time signal counts and statuses
- Regime Boundary : Horizontal line at reversion threshold
- Z-Score Channels : Dynamic over/oversold plots on price
- Combined RSI Line : Weighted oscillator for momentum view
- Multi-Level SD Bands : Deviation envelopes for cross alerts
- Top-Right Summary : Mode, direction, signals, and exits overview
🔔 Alert System
- Long entry notifications with ticker and timeframe on confluence
- Short entry notifications with ticker and timeframe on confluence
- Long exit notifications on trigger activation
- Short exit notifications on trigger activation
✅ Key Takeaways
- Signal Fusion Engine : Four codes create layered confluence for reliable reversions
- Mode Adaptability : Safe for precision, speed for volume in varying conditions
- DCA Optimization : Excels at spotting undervalued dips for dollar-cost averaging entries
- Visual Clarity : Tables and colors deliver instant signal and regime insights
- Regime-Smart Trading : Detector filters for true mean-reversion setups
- Backtest Reliability : Gated dates and metrics ensure robust testing
- Balanced Exits : Multiple triggers protect profits without premature closes
Multi-Asset Universal Valuation Z_score -> PROFABIGHI_CAPITAL🌟 Overview
The Multi-Asset Universal Valuation Z-Score → PROFABIGHI_CAPITAL indicator delivers a sophisticated portfolio screening tool by calculating normalized Z-scores for multiple assets simultaneously, incorporating price deviations alongside a suite of technical and risk-adjusted metrics to uncover relative overvaluations or undervaluations.
It empowers traders to monitor up to 25 assets—such as cryptocurrencies—in real-time through comprehensive tables, highlighting mispriced opportunities via statistical extremes, fair value estimates, and dynamic rankings for strategic rebalancing in diversified holdings.
📅 Assets Configuration
– Number of Assets : Define the portfolio size from 1 to 25 symbols, optimizing for computational load while expanding coverage for broader market scans.
– Asset Symbols (1-25) : Individually select tickers, often crypto pairs like BTCUSD or ETHUSD, to form a watchlist tailored to specific sectors or correlations for comparative analysis.
📊 General Settings
– Z-Score Lookback Period : Set the historical window for mean and standard deviation computations, influencing sensitivity to recent versus long-term deviations.
– Correlation Analysis Period : Establish the span for evaluating metric-price relationships, ensuring robust adjustments for interdependent signals.
– Show Main Table : Activate a central dashboard aggregating all assets' prices, sigma bands, fair values, and Z-scores for at-a-glance portfolio oversight.
– Show Ranking Tables : Enable sorted overviews of the top oversold and overbought assets, prioritizing high-conviction opportunities by deviation severity.
– Use Price Weighting : Blend direct price Z-scores with indicator-derived ones, anchoring the final score in raw market behavior.
– Adaptive Weighting : Dynamically scale metric influences by their correlation strength to price, promoting relevance in varying regimes.
📈 RSI Settings
– Enable RSI : Incorporate relative strength index to capture momentum extremes within the Z-score framework.
– RSI Length : Adjust the computation period to fine-tune overbought/oversold detection in asset valuations.
📈 ROC Settings
– Enable ROC : Include rate of change to highlight acceleration or deceleration in price trends for deviation scoring.
– ROC Period : Specify the lookback for percentage shifts, balancing short-term volatility with trend persistence.
📈 BB% Settings
– Enable BB% : Factor in Bollinger Bands position to measure range-bound extremes relative to volatility.
– BB Length : Define the moving average span for the bands' centerline.
– BB Standard Deviation : Set the multiplier for band width, controlling sensitivity to price envelopes.
📈 Crosby Ratio Settings
– Enable Crosby Ratio : Activate this trend angle proxy using smoothed Heikin-Ashi for directional slope analysis.
– Crosby Length : Choose the smoothing window to refine the ratio's responsiveness to price arcs.
📈 Sharpe Ratio Settings
– Enable Sharpe Ratio : Embed risk-adjusted returns to penalize volatility in the valuation score.
– Sharpe Period : Select the calculation horizon for mean returns and standard deviation.
– Sharpe Smoothing : Apply exponential averaging to stabilize the annualized efficiency metric.
📈 Sortino Ratio Settings
– Enable Sortino Ratio : Focus on downside volatility for a more trader-friendly risk gauge.
– Sortino Period : Determine the span for excess returns over the risk-free benchmark.
– Risk-Free Rate (%) : Input the annual safe yield to adjust for opportunity costs.
– Sortino Smoothing : Smooth the downside-focused ratio for consistent signals.
📈 Omega Ratio Settings
– Enable Omega Ratio : Use gains-versus-losses probability for threshold-sensitive performance ranking.
– Omega Period : Set the evaluation window for return distributions.
– Target Return (%) : Define the minimum acceptable yield to bifurcate positive/negative outcomes.
– Omega Smoothing : Refine the ratio with averaging to mitigate outlier impacts.
🛡️ Threshold Settings
– Extreme Overbought Level : Mark severe positive deviations warranting aggressive sells or hedges.
– Extreme Oversold Level : Flag profound negative deviations for opportunistic buys.
– Overbought Level : Signal moderate upward stretches for cautionary monitoring.
– Oversold Level : Indicate mild downward pulls for potential accumulation.
🎨 Color Settings
– Neutral Color : Subtle shade for assets within normal ranges, avoiding false alarms.
– Overbought Color : Alerting red for high-valuation warnings.
– Oversold Color : Inviting green for undervaluation opportunities.
– Extreme Overbought Color : Intense maroon for crisis-level bubbles.
– Extreme Oversold Color : Bright lime for deep-value bargains.
🔧 Helper Functions
– RSI/ROC/BB% Computations : Standard oscillators for momentum, change rate, and band positioning.
– Crosby Ratio : Approximates trend slope via Heikin-Ashi averages and ATR-normalized angles.
– Sharpe/Sortino/Omega Ratios : Annualized efficiency metrics, with Sortino emphasizing downside and Omega using return thresholds.
– Z-Score Normalization : Transforms series into standard deviations from means for cross-asset comparability.
– Correlation & Beta Adjustments : Quantifies metric-price links to refine weighted influences.
– Weighted Z-Score Blend : Integrates indicators with price via betas and correlations for holistic scoring.
– Symbol Cleanup : Strips exchange prefixes and pairs for concise table labels.
📦 Multi-Asset Processing
– Security Fetching : Pulls comprehensive data—prices, Z-scores, means, deviations, expectations—for each asset in parallel.
– Array Management : Dynamically stores metrics in expandable arrays, scaling to the selected portfolio size.
– Ranking Engine : Bubble-sorts by Z-scores to prioritize undervalued (low) and overvalued (high) assets for quick scans.
📋 Main Table
– Central Dashboard : Rows for prices, ±1/2/3 sigma bands, fair values, expected prices, and dual Z-scores; columns per asset with color-coded cells by deviation severity.
– Dynamic Headers : Asset symbols highlighted if ranked in top oversold/overbought quintiles for immediate focus.
🏆 Ranking Tables
– Oversold Rankings : Top 5 (or fewer) by lowest Z-scores, detailing symbols, individual Z's, averages, and the weakest metric.
– Overbought Rankings : Top 5 (or fewer) by highest Z-scores, mirroring structure for symmetry in bubble detection.
📊 Current Asset Visualization
– Sigma Deviation Plots : Lines mapping ±1/2/3 standard deviations from the mean for contextual over/undervaluation.
– Fair Value & Expected Price Traces : Central mean and Z-adjusted projection to visualize reversion targets.
– Live Price Overlay : Blue line tracking current close against bands for real-time deviation monitoring.
– Zone Backgrounds : Faint tints scaling from neutral to extreme colors based on the asset's Z-score status.
🔔 Alerts
– Overbought Entry : Activates on crossing into moderate high-deviation territory.
– Oversold Entry : Triggers upon entering low-deviation zones.
– Extreme Overbought/Oversold : High-priority warnings at critical thresholds for portfolio-wide risks.
✅ Key Takeaways
– Cross-asset Z-scores reveal portfolio imbalances via statistical lenses, blending raw price with advanced ratios.
– Adaptive correlations ensure metric relevance, while rankings accelerate opportunity hunting.
– Comprehensive tables and band visuals turn complex data into actionable insights for diversified trading.
– Customizable metrics and thresholds adapt to crypto volatility or traditional equities alike.
Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL (Backtest)🌟 Overview
The Advanced Memecoin Tracker → PROFABIGHI_CAPITAL (Backtest) indicator screens a diverse portfolio of memecoins across major blockchains, scoring them based on momentum, volatility-adjusted performance, and relative strength to chain basecoins for dynamic eligibility ranking. It simulates rotational long-only exposure to top performers while comparing against equal-weight holds and benchmarks, delivering tables for conditions, rankings, and metrics to identify high-potential memecoin rotations.
⚙️ Backtest Configuration
- Leverage Multiplier : Adjustable amplification for simulated position returns to model leveraged trading scenarios
- Start Date Selection : Defines the beginning of the backtest period for all equity and hold calculations
- Slippage Percentage : Deducts execution costs from trades to reflect real-market friction
- Commission Percentage : Applies brokerage fees on position changes for net performance accuracy
- Metrics Tables Toggle : Enables or disables detailed performance summaries for chart focus
- Basecoin Symbols : Configurable references (ETH, SOL, SUI, VIRTUAL) for relative strength comparisons
📅 Date Range Settings
- Backtest Inception Point : Restricts simulations to bars after the selected timestamp for targeted analysis
- Equity Initialization : Sets starting value to unity on the inception date
- Historical Gating : Ignores pre-start data to focus on defined performance windows
- Forward Cost Application : Applies slippage and commissions only within the active period
📊 PROFABIGHI_CAPITAL Metrics Display
Equity Curve Options:
- Dynamic Portfolio Path : Traces cumulative returns from rotational allocations
- Benchmark Overlay : Compares against hold strategies for relative outperformance
- Inception Reference : Marks the start with a vertical line and label
- Return Percentage Label : Shows total gain/loss dynamically
- Shaded Growth Area : Fills under the curve for visual volume emphasis
- Suppression Choice : Hides the curve to prioritize table views
Metrics Table Setup:
- Split-Panel Distribution : Organizes asset stats across bottom-center and bottom-right
- Essential Metrics Suite : Covers drawdown, Sharpe, Sortino, Omega, and returns per asset
- Portfolio Summary : Highlights aggregated system performance
- Benchmark Hold View : Dedicated panel for passive index metrics with thresholds
- Toggle-Based Rendering : Switches to compact summary when full tables off
- Dark Theme Consistency : Black backgrounds with white text for readability
⚙️ Evaluation and Portfolio Settings
- Signal Mode Selection : Aggressive for threshold-based averaging or conservative for unanimous passes
- Asset Evaluation Count : Limits the total memecoins analyzed for efficiency
- Top Ranking Limit : Restricts the display table to elite performers
- Eligibility Threshold : Minimum score cutoff for aggressive mode inclusion
- Indicator Activation Toggles : Enables RSI variants, ROC scales, Sharpe, momentum, delta, and relative strength
- Chain Grouping Bonus : Awards extra points to memecoins outperforming their basecoin
📊 Indicator Selection
Oscillator Suite:
- Short RSI Toggle : Activates quick momentum readings for early signals
- Long RSI Toggle : Includes trend-aligned overbought/oversold checks
- ROC Multi-Scale Toggles : Engages short, medium, long change rates for layered acceleration
Efficiency and Strength Measures:
- Sharpe Ratio Toggle : Factors in risk-adjusted returns for quality filtering
- Momentum RSI Toggle : Applies bounded oscillator to velocity for persistence
- Price Delta Toggle : Evaluates directional changes or smoothed variants
- Relative Strength Toggle : Compares to basecoins for chain-specific outperformance
📊 RSI Configuration
Input and Period Controls:
- RSI Price Source : Chooses the data feed for oscillator computation
- Short Period Adjustment : Tunes responsiveness for fast memecoin swings
- Long Period Adjustment : Sets broader horizon for sustained momentum
Noise Reduction Layers:
- Primary Average Type and Span : Selects and sizes first smoothing for clarity
- Secondary Layer Toggle : Adds comparator average for crossover refinement
- Secondary Average Type and Span : Customizes the backup smoother
- Adaptive Volatility Window : VIDYA lookback for dynamic response
Signal Generation Rules:
- Mid-Range Favoring : Credits building strength without extremes
- Crossover Preference : Rewards favorable MA alignments in dual setups
- Mode-Adaptive Scoring : Partial in aggressive, strict in conservative
📊 ROC Configuration
Change Rate Horizons:
- Short-Term Period : Captures immediate price velocity bursts
- Medium-Term Period : Balances recent acceleration trends
- Long-Term Period : Smooths over extended momentum phases
Directional Bias Logic:
- Positive Thresholding : Full credit for upward changes across scales
- Unified Multi-Period View : Aggregates for comprehensive rate alignment
- Binary Momentum Check : Pass/fail on positivity for simplicity
📊 Sharpe Ratio Configuration
Efficiency Windowing:
- Return/Volatility Lookback : Defines historical scope for ratio base
- Value Smoothing Span : Applies EMA to steady raw computations
- Buy Signal Bound : Upper threshold for positive efficiency
- Sell Signal Bound : Lower cutoff for underperformance flags
Scaling and Normalization:
- Annual Factor Application : Converts daily to yearly for standardization
- Zero-Division Guard : Defaults to neutral on flat volatility
- Threshold-Based Credit : Full pass above buy, penalties below sell in aggressive mode
📊 Momentum RSI Configuration
Velocity Oscillation Setup:
- Momentum Horizon : Sets change detection period for input to RSI
- Bounded Strength Period : RSI length on momentum for normalized power
- First Smoothing Choice and Size : Average type and length for initial filter
- Second Layer Activation : Optional dual for advanced crossover
Dynamic Adaptation:
- Volatility Response Window : VIDYA period for market-sensitive smoothing
- Midline Dominance Reward : Credits above-center persistence
- Alignment Scoring : Full in conservative, flexible in aggressive
📊 Price Delta RSI Configuration
Change Assessment Mode:
- Raw vs. Smoothed Delta : Direct differences or RSI-applied for refinement
- Delta Computation Span : Lookback for price shift evaluation
- Oscillation on Delta : RSI period when using bounded variant
Filter Enhancements:
- Initial Average Type and Span : Smoother for delta signal clarity
- Comparator Layer Toggle : Dual-MA for directional confirmation
- Adaptive Volatility Span : VIDYA window for responsive adjustment
Bias Determination:
- Upward Shift Credit : Full for positive raw deltas
- Center or Cross Favor : Above 50 or aligned MA for smoothed
- Integrated Versatility : Supports both basic and layered delta views
📊 Relative Strength Configuration
Chain Comparison Framework:
- RSI Ratio Period : Oscillator length on asset-to-basecoin ratio
- Smoothing Average Type and Span : Filter for RS signal stability
- Dual Layer Toggle : Second average for crossover enhancement
- Volatility-Adjusted Window : VIDYA lookback for dynamic RS smoothing
Outperformance Logic:
- Midline Superiority : Credits RS above 50 for basecoin dominance
- Crossover Alignment : Rewards favorable dual-MA setups
- Group Bonus Integration : Extra points for top chain performers
📊 Beta Assessment
Market Sensitivity Measure:
- Benchmark Reference : Index symbol for relative volatility baseline
- Covariance Horizon : Period for return pairing and normalization
Correlation Derivation:
- Daily Shift Alignment : Matches asset and benchmark changes
- Variance Safeguard : Handles edge cases in division
- Contextual Layer : Adds relative risk without direct score impact
🪙 Memecoin Portfolio Setup
Chain-Segmented Inputs:
- Ethereum Group : Up to 9 symbols for ETH-based memecoins
- Solana Group : Up to 9 symbols for SOL-based memecoins
- SUI Group : Up to 9 symbols for SUI-based memecoins
- BASE/VIRTUAL Group : Up to 9 symbols for alternative chain memecoins
Basecoin References:
- ETH, SOL, SUI, VIRTUAL Symbols : Configurable anchors for RS calculations
- Security Price Fetching : Pulls closes for all enabled memecoins
- Group-Aware Arrays : Stores names, metrics, and conditions by index
📊 Scoring and Rotation Engine
Chain Strength Ranking:
- Basecoin RSI Computation : Applies oscillator to each reference
- Top Chain Identification : Selects strongest base for bonus allocation
- Group Bonus Assignment : Boosts scores for memecoins on leading chains
Per-Asset Evaluation:
- Enabled Indicator Tally : Counts active metrics for normalized averaging
- Binary Alignment Check : 1 for bullish conditions, 0 otherwise
- RS Multi-Chain Max : Takes highest relative strength across bases
Final Eligibility Rules:
- Aggressive Averaging : Full score if normalized meets threshold
- Conservative Consensus : Requires all toggled indicators to pass
- Bonus-Enhanced RS : Adds chain leadership points for competitive edge
🏆 Ranking and Allocation
Score-Based Sorting:
- Descending Order : Ranks assets by final eligibility rating
- Threshold Pruning : Filters to qualifying entries up to limit
- Eligible Pool Formation : Builds set for dynamic position weighting
Long Signal Generation:
- Top-Asset Activation : Flags longs for ranked memecoins
- Array Mapping : Assigns booleans to each instrument index
- Real-Time Rebalance : Updates on bar close for responsive rotation
📋 Tables and Visuals
Ranking Display Panel:
- Bottom-Left Compact Grid : Lists top assets with rank, name, and score
- Clean Name Stripping : Removes exchange prefixes for brevity
- Last-Bar Refresh [/b>: Updates only on final bar for efficiency
Basiscoin Strength Table:
- Top-Left Summary : Ranks basecoins by RSI for chain context
- Numerical Ordering : 1-4 positions with symbol labels
- Performance Insight : Highlights leading ecosystem for bonus awareness
📈 Backtest Simulation
State Tracking Arrays:
- Current/Prior Long Flags : Monitors position changes per asset
- Weight Persistence : Stores previous allocations for cost calc
- Transition Detection : Identifies flips to apply fees
Equity Path Building:
- Weighted Daily Shifts : Sums changes by lagged allocations
- Cost Subtraction : Deducts slippage/commissions on transitions
- Compounded Growth : Chains net returns from unity start
- Hold Baseline : Equal-weight across all for passive comparison
📊 Metrics Derivation
Risk-Return Analytics:
- Maximum Drawdown : Peak-to-trough drops for each path
- Sharpe Efficiency : Annualized return per volatility unit
- Sortino Downside Focus : Penalizes only negative deviations
- Omega Probability Weight : Gains vs. losses beyond threshold
Comprehensive Breakdown:
- Per-Asset Isolation : Individual stats for memecoin performance
- System Composite : Aggregated from rotational equity
- Benchmark Parallels : Hold metrics for validation
- Formatted Presentation [/b>: Percentages and rounded values in tables
🔔 Alert Integration
- Eligible Asset List : Comma-separated top-ranked memecoins on close
- No-Qualify Notice : Alerts when criteria unmet
- Bar-Close Dispatch [/b>: Single trigger per confirmed bar
- Name Simplification [/b>: Clean symbols without prefixes
✅ Key Takeaways
- Chain-Focused Screening : Scores memecoins with relative strength to basecoins for ecosystem edge
- Rotational Exposure : Dynamically weights top eligible for momentum capture
- Realistic Simulation : Factors leverage, costs, and holds for practical insights
- Visual Prioritization : Tables spotlight rankings, conditions, and basecoin leaders
- Flexible Calibration : Toggles and modes tune sensitivity to volatility
- Bonus-Driven Groups : Rewards outperformance within leading chains
- Alert Efficiency : Delivers actionable picks without overload
- Scalable Multi-Asset : Handles dozens of memecoins with array optimization
M Carlo Pro -> PROFABIGHI_CAPITAL🌟 Overview
The M Carlo Pro is a sophisticated Monte Carlo simulation engine that generates probabilistic price projections and scenario analysis frameworks . It offers dual-mode operation combining forward-looking price path modeling with return-based scenario testing , featuring confidence interval calculations , histogram distribution analysis , and customizable random sampling from historical data or user-defined return distributions.
⚙️ Main Mode Selector
- Analysis Mode Choice : Select between Scenario Analysis or Price Projection
- Scenario Analysis : Return-based simulations displayed in separate indicator pane with distribution analysis
- Price Projection : Forward price paths rendered directly on main price chart
- Mode-Specific Visualization : Each mode optimizes display for its analytical purpose
📊 Common Simulation Settings
- Random Seed : Fixed seed value for reproducible simulation results across multiple runs
- Distribution Type Selection : Choose between Normal (Gaussian) distribution or Bootstrap resampling
- Number of Paths : Total simulation iterations to generate for statistical validity
- Projection Length : Forward-looking bars or steps for each simulation path
- Boundaries Only Toggle : Display only confidence bounds instead of full path ensemble
- Historical Lookback : Number of past bars to collect for return distribution calculation
- Path Style Selector : Visual line style (solid, dotted, or dashed) for rendered paths
📈 Scenario Analysis Settings
Simulation Source Options:
- Price Mode : Calculates returns from historical price data automatically
- Custom Returns Mode : Uses user-defined return values for scenario testing
Return Input Framework:
- Primary Returns : Main scenario return values entered as text (one per line)
- Secondary Returns : Additional scenario layer for multi-dimensional analysis
- Tertiary Returns : Third scenario dimension for complex modeling
- Quaternary Returns : Fourth scenario layer for maximum flexibility
- Multi-Layer Support : Combine multiple return sets for comprehensive scenario coverage
Confidence and Display:
- Confidence Level Percentage : Statistical confidence interval for boundary calculations
- Path Lines Only : Show simulation paths without additional visual elements
- Scatter Plot Mode : Render final outcomes as scatter points instead of connected paths
- Distribution View Only : Display exclusively the histogram distribution without paths
Histogram Configuration:
- Binning Method Selection : Choose between Sturges, Rice, Square Root, or custom bin calculation
- Automatic Bin Sizing : Statistical formulas determine optimal histogram granularity
- Custom Bin Option : Manual specification of histogram bar count when custom method selected
📈 Price Projection Settings
- Display Scale Toggle : Show or hide price axis and scale labels on projection chart
- Force Render Option : Override path limit for full rendering (may truncate long projections)
- Show Mean Path : Display the average projection path across all simulations for central tendency visualization
- Performance Table : Summary statistics showing number of paths generated and projection length
🔧 Distribution Methods
Normal Distribution (Gaussian):
- Calculates mean and standard deviation from historical returns
- Generates random values using Box-Muller transform
- Produces symmetric probability distribution around mean
- Two independent uniform random numbers transformed into normally distributed values
Bootstrap Resampling:
- Randomly samples from actual historical return observations
- Preserves empirical distribution characteristics without parametric assumptions
- Each simulation step selects one historical return with replacement
- Captures real market behavior including fat tails and skewness
Return Calculation Logic:
- Price Mode : Logarithmic returns calculated from consecutive price ratios
- Custom Mode : User-provided returns applied directly to simulation
- Exponential Application : Price mode uses exponential of return for price updates
- Additive Application : Custom return mode adds returns directly
📊 Scenario Analysis Execution
Simulation Loop Process:
- Initialize starting value (price or sum of returns)
- Generate random return using selected distribution method
- Apply return to current value using appropriate calculation method
- Store intermediate results in matrix structure
- Track final outcomes in endpoint array
- Repeat for specified number of paths
Confidence Interval Calculation:
- Bins final outcomes into histogram with chosen binning method
- Identifies bin with maximum frequency (mode)
- Expands range symmetrically around mode
- Calculates cumulative probability of range
- Highlights bins within specified confidence level
- Displays confidence percentage and visual fill
Visualization Components:
- Path Rendering : Colored lines showing individual simulation trajectories
- Scatter Plot Option : Final outcomes plotted as individual points with labels or boxes
- Boundary Lines : Orange and teal lines marking confidence envelope when boundaries-only enabled
- Current Sum Line : Yellow reference line showing starting return sum in custom mode
- Step Labels : Bar numbers or step counts along horizontal axis
- Scale Axes : Vertical scale with value labels and horizontal baseline
📈 Price Projection Execution
Path Generation Framework:
- Divides total paths into twenty batches for performance optimization
- Each batch processes assigned number of simulations
- Generates forward price points using distribution sampling
- Accumulates sum of all prices at each projection step for average calculation
- Stores endpoints for statistical analysis
- Renders paths as polylines with random color assignment
Mean Path Calculation:
- Sums all simulated prices at each forward bar
- Divides by total number of simulations for average
- Plots thicker aqua-colored line representing expected value path
- Provides central tendency reference across all scenarios
Performance Optimization:
- Batch Processing : Splits simulations into manageable chunks
- Point Aggregation : Collects points before polyline rendering
- Conditional Rendering : Force option overrides automatic path limits
- Dynamic Coloring : Random RGB generation for path differentiation
Scale and Annotation:
- Vertical Scale : Price axis with evenly spaced labels showing projection range
- Horizontal Scale : Bar count labels showing forward projection timeline
- Grid Lines : Teal-colored axes forming scale framework
- Performance Table : Bottom-right display of simulation parameters
🎨 Visualization Features
Scenario Analysis Display (Separate Pane):
- Simulation Paths : Multi-colored trajectories from starting point to projection horizon
- Baseline Plot : Aqua line showing starting value (price or return sum)
- Confidence Boundaries : Orange (lower) and teal (upper) envelope lines
- Histogram Distribution : Orange bars showing frequency of final outcomes
- Bin Labels : Outcome values and frequencies displayed on each histogram bar
- Confidence Highlight : Darker orange shading on bins within confidence interval
- Confidence Label : Percentage display showing statistical coverage
- Axis Scaling : Adaptive vertical scale based on outcome range
Price Projection Display (Main Chart):
- Price Candles : Teal (bullish) or orange (bearish) candles on underlying price chart
- Projection Paths : Rainbow-colored polylines extending forward from current bar
- Mean Path Line : Thick aqua line showing average projection across all simulations
- Scale Display : Optional price axis and bar count labels
- Performance Table : Summary box showing simulation statistics
Common Visual Elements:
- Random Coloring : Each path assigned unique RGB values for differentiation
- Line Style Options : Solid, dotted, or dashed rendering for all paths
- Transparent Colors : Semi-transparent fills and lines prevent visual clutter
- Dynamic Scaling : Automatic axis adjustment based on outcome distribution
🔍 Advanced Features
Matrix Data Management:
- Row-Column Structure : Simulation results stored in two-dimensional matrix
- Color Matrix : Parallel matrix storing path colors for rendering
- Min-Max Tracking : Boundary matrix records extremes at each projection step
- Endpoint Array : Final outcome values collected for histogram analysis
Histogram Construction:
- Automatic Binning : Statistical formulas calculate optimal bin count based on sample size
- Sturges Formula : Logarithmic approach for bin determination
- Rice Rule : Cube-root-based calculation for granularity
- Square Root Method : Simple square root of sample size
- Frequency Counting : Each outcome assigned to appropriate bin
- Value Tracking : Minimum value in each bin recorded for labeling
Scatter Plot Implementation:
- Label Creation : First 500 outcomes rendered as styled labels with circular markers
- Box Fallback : Additional outcomes beyond label limit rendered as boxes
- Random Positioning : X-coordinate randomization prevents perfect vertical alignment
- Color Preservation : Each point retains its assigned simulation color
Adaptive Visualization:
- Mode Detection : Different rendering logic for price versus return simulations
- Toggle Interactions : Boundary-only and histogram-only modes override default displays
- Dynamic Limits : Path rendering adjusts based on performance constraints
- Conditional Elements : Scale, mean, and table displays controlled by user toggles
🎯 Use Cases and Applications
Risk Assessment:
- Generate probability distribution of future outcomes
- Identify worst-case and best-case scenarios with confidence intervals
- Quantify likelihood of specific price targets
- Visualize range of plausible futures based on historical volatility
Scenario Planning:
- Test specific return sequences using custom input mode
- Model multiple market environments with layered return sets
- Compare outcomes across different volatility assumptions
- Evaluate strategy performance under various conditions
Portfolio Projections:
- Forecast future portfolio values with probabilistic bounds
- Estimate expected returns across multiple timeframes
- Assess probability of reaching financial goals
- Understand distribution of potential outcomes
Education and Research:
- Demonstrate Monte Carlo methodology visually
- Explore effects of different distribution assumptions
- Compare normal versus empirical (bootstrap) distributions
- Illustrate concepts of confidence intervals and central limit theorem
✅ Key Takeaways
- Dual-Mode Flexibility : Scenario Analysis for distribution study or Price Projection for forward visualization
- Statistical Rigor : Confidence interval calculation with automatic histogram binning methods
- Distribution Choices : Normal (Gaussian) assumption or Bootstrap for empirical distribution preservation
- Custom Scenario Testing : Four-layer return input system for complex multi-dimensional analysis
- Reproducible Results : Fixed random seed ensures consistent output across multiple runs
- Batch Processing Optimization : Twenty-batch execution for handling large simulation counts
- Visual Clarity : Separate pane for scenario analysis, main chart overlay for price projections
- Mean Path Reference : Average trajectory across all simulations provides expected value guidance
- Adaptive Scaling : Automatic axis adjustment and range detection for optimal display
- Performance Management : Conditional rendering limits and force options balance detail with execution speed
- Histogram Intelligence : Multiple binning algorithms with confidence highlighting for outcome distribution
- Comprehensive Visualization : Paths, boundaries, scatter plots, histograms, scales, and tables for complete analytical picture
🚀🚀 PROFABIGHI_CAPITAL Correlation Heatmap System 🚀🚀🌟 Overview
The PROFABIGHI_CAPITAL Correlation Heatmap System is an institutional-grade multi-asset correlation visualization tool engineered for cryptocurrency traders seeking to dissect inter-asset dependencies and portfolio risk clustering through dynamic, rolling correlation matrices or benchmark-focused comparisons. By computing Pearson correlation coefficients over adjustable lookback periods across up to 20 symbols, it generates color-coded heatmaps highlighting positive (green) or negative (red) relationships, while the single-asset mode benchmarks against a primary symbol (e.g., BTC) to reveal relative strength hierarchies [/b>, top/bottom extremes, and diversification insights—empowering users to optimize allocations, detect co-movement risks , or uncover decoupling opportunities in volatile markets with real-time table updates and symmetric visualizations.
This sophisticated system transcends basic scatter plots by offering dual-mode flexibility —comprehensive pairwise matrices for broad ecosystem scanning or targeted single-asset scans for focused relative analysis—complete with invalid symbol tolerance [/b>, dynamic table sizing [/b>, and performance-optimized fetching [/b>, ensuring seamless scalability from watchlists of 5 assets to full 20-symbol universes while maintaining computational efficiency and visual clarity for professional-grade decision-making.
🚀 Main Settings
- Display Mode : Core selector between 'X -> Y Matrix' for exhaustive pairwise correlation grids that reveal the full network of asset interdependencies, ideal for identifying clusters of high-beta alts or low-correlation hedges, and 'Single Asset R Comparison' for streamlined benchmarking against a chosen primary symbol, perfect for evaluating how individual tokens align or diverge from market leaders like BTC during regime shifts
- Correlation Length : Adjustable rolling window (default 30 bars) that defines the historical scope for coefficient calculations, where shorter periods emphasize recent volatility correlations for tactical adjustments and longer horizons capture structural relationships for strategic portfolio construction, balancing noise reduction with regime sensitivity
- Number of Assets in Matrix : Scalable limit (up to 20) controlling the heatmap dimensions, enabling focused 5x5 grids for core holdings or expansive 20x20 matrices for ecosystem-wide scanning, with automatic diagonal suppression (em-dashes) to avoid self-correlation artifacts and optimize visual density
📊 Single Asset R Comparison Settings
- The PROFABIGHI_CAPITAL Asset : Primary symbol designation (default BTCUSD) serving as the correlation anchor, allowing traders to assess how alts co-move with this reference during pumps, dumps, or sideways action, facilitating relative strength rankings and beta-like exposure profiling without full regressions
- Number of Assets in Main Table : Configurable count (up to 20) for the unsorted correlation list, providing a comprehensive yet manageable view of dependencies in original input order, useful for sequential portfolio reviews or quick scans of predefined watchlists
- Number of Top/Bottom Assets : Highlight limit (default 5) for dedicated tables showcasing strongest positive (top) and weakest/negative (bottom) correlations, spotlighting diversification candidates (low R) or momentum followers (high R) to guide rebalancing decisions amid market rotations
📈 Assets List (20x)
- Asset 1 through Asset 20 : Sequential symbol inputs for building the correlation universe, starting with majors like BTC, ETH, SOL for baseline stability and extending to alts like XRP, ADA for diversification insights, with tooltip guidance for format (e.g., CRYPTO:BTCUSD) and flexibility for custom tokens across exchanges
- Grouped Configuration : Organized list for streamlined portfolio assembly, allowing quick swaps of underperformers or additions of emerging narratives, ensuring the heatmap reflects current market themes from blue-chips to speculative plays
- Exchange Prefix Support : Native handling of prefixed symbols (e.g., CRYPTO:, BINANCE:), enabling cross-platform comparisons without manual adjustments, while the short name extractor cleans displays for readability in dense tables
📡 Data Fetching (20x)
- Parallel Security Requests : Simultaneous close price pulls for all 20 assets using timeframe-aligned fetches, ensuring synchronized data across symbols to maintain correlation accuracy even in asynchronous market hours
- System Asset Isolation : Dedicated retrieval for the primary benchmark symbol, preventing contamination in single-mode comparisons and allowing independent updates without affecting matrix computations
- Invalid Symbol Resilience : Built-in ignore_invalid_symbol parameter with na defaults, gracefully handling malformed inputs or delisted tokens to avoid script crashes and enable partial universe analysis
- Chart Timeframe Alignment : Automatic adaptation to the active chart resolution, supporting from 1-minute intraday correlations for scalping to daily for swing trading, with consistent bar indexing for reliable rolling windows
🔧 Helper Functions
- Short Name Extractor : Utility to strip exchange prefixes and suffixes (e.g., CRYPTO:BTCUSD → BTC), generating compact labels for table headers and cells, enhancing scannability in large matrices without losing symbol identity
- Correlation Column Generator : Core function computing Pearson coefficients between two series over the specified length, returning both the value and a binary color (green for positive >0, red for negative) to streamline heatmap cell population with visual intuition
- Cell Filler Routine : Standardized table.cell wrapper applying consistent black-transparent backgrounds, small text sizing, and dynamic text colors, ensuring uniform aesthetics across all visualization modes while supporting conditional formatting for emphasis
📊 Correlation Calculations
- Pairwise Rolling Coefficients : Exhaustive computation of ta.correlation for every unique asset pair (up to 190 in 20x20 mode), generating symmetric matrices that illuminate co-movement patterns, from tight BTC-ETH linkages to decoupled niche alts, with na-safe handling for data gaps
- Single-Asset Benchmark Series : Dedicated correlations against the primary symbol for all others, producing a vector of R values that quantify relative dependencies, enabling quick identification of 'BTC clones' (high positive) or inverse hedges (negative)
- Length-Parameterized Rolling : Each coefficient uses the user-defined lookback to filter transient noise, where 20-bar windows highlight short-term spillovers and 100-bar captures enduring regime correlations for long-term allocation
- Color Mapping Logic : Binary green/red assignment based on sign (positive/negative), providing immediate visual cues for diversification (seek reds) or momentum trading (cluster greens), with potential for gradient extensions in future iterations
- Diagonal Suppression : Automatic em-dash placement on self-correlations (always 1.0), avoiding redundant cells and centering focus on inter-asset insights in the heatmap grid
🎨 Visualization Logic
- Last-Bar Dynamic Refresh : Table recreation on barstate.islast with prior deletions to prevent accumulation, ensuring crisp updates without historical artifacts or memory bloat in extended sessions
- Branding Banner Table : Bottom-center single-cell overlay with bold, yellow-texted indicator title on black background, serving as persistent identifier and visual anchor amid multi-table layouts
- Matrix Heatmap Construction : Centered (num_assets+1)x(num_assets+1) table with gray borders, populating headers vertically/horizontally with short names, filling off-diagonals with formatted R values and sign-based colors for symmetric, at-a-glance dependency mapping
- Single-Mode Multi-Table Suite : Top-center primary asset highlight (yellow-bordered), middle-center unsorted main list for sequential review, left/right top/bottom sorted subsets for extreme correlation spotlights, all with gray headers and color-coded R cells
- Progressive Cell Population : Nested conditionals scaling fills to active asset count, ensuring partial matrices render cleanly while full 20x20 grids showcase exhaustive pairwise analysis without overflow
- Error Handling Label : Fallback red downward label when no valid correlations available, prompting data checks and preventing blank displays in edge cases like all-invalid symbols
✅ Key Takeaways
- Dual-Mode Versatility : Seamlessly toggles between exhaustive pairwise heatmaps for ecosystem mapping and single-asset benchmarks for relative strength profiling, adapting to tactical or strategic analysis needs
- Rolling Correlation Insights : Adjustable windows reveal dynamic dependencies, crucial for spotting co-crash risks (high positive R) or counter-trend hedges (negative R) in crypto's correlated environments
- Visual Heatmap Efficiency : Color gradients and symmetric layouts enable instant pattern recognition, from BTC-beta clusters to low-R diversification gems, accelerating portfolio optimization
- Scalable Asset Handling : Up to 20 symbols with invalid tolerance and dynamic sizing, supporting watchlist scans without performance hits or manual exclusions
- Top/Bottom Extremes : Dedicated tables flag strongest/weakest links, guiding quick rebalances toward uncorrelated assets for reduced drawdowns or amplified momentum plays
- Benchmark-Centric Flexibility : Custom primary symbol centers analysis on user priorities like ETH for DeFi focus, transforming raw R values into actionable relative performance hierarchies
Volume MatrixVolume Matrix (VM) is a comprehensive volume and position-sizing toolkit designed to help traders interpret market participation and manage trade risk efficiently.
It combines volume analytics, risk-adjusted position sizing, and stock-specific financial data — all in a clear, visual, and automated format directly on TradingView charts.
The indicator integrates capital management, episodic volume spikes, and market capitalization data into a single, intuitive framework, giving traders an edge in both decision-making and discipline.
⚙️ Core Components & Features
🧩 1. Position Sizing & Risk Management
A dynamic risk table helps traders determine how much to trade and how much to risk per position, adapting automatically based on user inputs:
- Capital (CP): Total account size (₹ or $).
- Risk Mode (R): Choose between Percentage of capital or fixed Currency value.
- Lot Size Mode: Optional toggle to align quantities with F&O lot sizes (India-based).
- Standard Stop-Loss (SSL): Displays position quantities for three custom stop-loss levels (e.g., 0.75%, 1%, 1.25%).
- % Distance Metrics: D: Distance from day’s low/high (helps assess stop distance). DH: Distance from mid-body (useful for candle risk assessment). Auto-adjusts based on whether the trader is in Long, Short, or Both mode.
📈 Helps answer:
“How much quantity should I trade at my desired risk level?”
🔶 2. Volume Visualization
- Plots volume bars with default up/down coloring.
- Green for bullish bars.
- Red for bearish bars.
- Designed for quick visual differentiation of buying/selling pressure.
🚀 3. Episodic Pivot (EP) Detector
Identifies high-volume breakout or capitulation days, often marking significant turning points or trend initiations.
- Highlights bars where volume exceeds a custom threshold (in millions).
- Marks them visually with an orange triangle under the candle.
-Best used on daily charts to spot institutional footprints.
📊 Helps answer:
“Is today’s volume large enough to signal major institutional activity?”
🧾 4. Data Metrics Table
Displays fundamental and contextual data about the asset:
- Market Capitalization (MC): Auto-calculated using outstanding shares × price.
- Free Float (FF): Value of tradable shares in currency or Cr (INR).
- Industry × Sector × F&O Status: Shows the company’s industry and sector classification. Displays FC (Futures Contract) or NFC (Non-F&O stock).
- Customizable appearance: Choose between text/value display, text color, and background color. Flexible positioning and size control to suit any chart layout.
📚 Helps answer:
“What type of stock is this, how big is it, and does it trade in futures?”
🪄 5. User Interface Customization
- Modular UI grouped by functionality (Risk, Direction, Metrics, Volume, etc.).
- Flexible table position & size (Top/Bottom/Middle & Tiny–Huge).
- All elements are toggleable, giving full control over displayed data.
- Built to ensure visual clarity on any chart background.
| Trading Goal | How Volume Matrix Supports It |
| ------------------------------ | -------------------------------------------------------------- |
| **Risk Management** | Calculates optimal trade size and risk exposure automatically. |
| **Position Sizing Discipline** | Enforces consistent sizing across trades using SSL levels. |
| **Volume Confirmation** | Highlights institutional participation via Episodic Pivots. |
| **Stock Context Awareness** | Shows market cap, sector, and float value instantly. |
| **Efficiency** | Reduces manual work — no need for calculators or spreadsheets. |
💡 In Short
Volume Matrix simplifies trade planning, brings transparency to risk, and connects volume with context — all in one elegant visual tool.
Perfect for:
- Discretionary traders refining entries and sizing.
- Swing traders watching for volume-based pivots.
- Analysts who want price-volume fundamentals at a glance.
Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL is a specialized multi-chain memecoin intelligence dashboard that integrates relative strength positioning (RSP) via RSI on asset ratios with benchmark-relative metrics to score up to 36 memecoins across Ethereum, Solana, SUI, and BASE/VIRTUAL ecosystems. It computes weighted composites from outperformance binaries, category-leading RSP flags, and rank-based points, visualized in expansive tables for median benchmarking and top rankings to pinpoint viral momentum leaders amid speculative volatility.
🔧 General Settings
- Toggle for activating alpha to isolate excess returns beyond benchmark influence, highlighting unique memecoin drivers
- Toggle for enabling beta to quantify volatility correlation with the benchmark, aiding memecoin risk profiling
- Toggle for incorporating Sharpe ratio to gauge overall efficiency of returns relative to total risk exposure
- Toggle for including Sortino ratio to prioritize returns adjusted specifically for downside volatility impacts
- Toggle for utilizing omega ratio to weigh probability-adjusted gains against losses above a target threshold
- Toggle for adding rate of change (ROC) to capture raw momentum shifts over a specified horizon
- Adjustable lookback periods for alpha and beta regressions, tuning between stability and recency in relative analysis
- Customizable benchmark symbol , such as market indices, to establish the reference frame for comparative evaluations
- Configurable Sharpe rolling window and smoothing for responsive risk-reward snapshots
- Extended Sortino and omega periods with risk-free rates and target returns for robust downside and distributional insights
- ROC horizon setting to balance short-term reactivity with trend confirmation
- Scalable asset count up to 36 and top display limit for efficient screening from niche memecoin clusters to full ecosystems
📋 Table Settings
- Background transparency for semi-opaque overlays, ensuring readability while preserving pane context
- Border styling for clear delineation of data sections without visual clutter
- Text sizing options , from compact to prominent, to suit screen preferences and detail levels in dense memecoin grids
📈 RSP Settings
- RSI length for relative strength computations, defining the oscillator period on memecoin cross-ratios
- Primary smoothing type , selectable from standard averages to advanced hull or variable index for signal refinement
- Primary smoothing length , adjusting lag to match analysis timeframe from intraday to weekly
- Secondary smoothing type , allowing layered processing or dynamic comparisons for deeper confirmation
- Secondary smoothing length , providing extended baseline for stable relative momentum readings
- Toggle for second MA comparison , shifting scoring from absolute levels to relative crossovers
- VIDYA volatility lookback , dynamically scaling smoothing to market dispersion for adaptive RSP
🪙 Specific Coins
- ETH symbol input for RSP baseline, anchoring Ethereum memecoin relative strength calculations
- SOL symbol input for Solana ecosystem comparisons, evaluating chain-specific outperformance
- SUI symbol input for SUI memecoin benchmarking, highlighting ecosystem leaders
- VIRTUAL symbol input for BASE/VIRTUAL chain reference, facilitating cross-layer analysis
📊 Ethereum Memecoins
- Individual symbol inputs for up to 9 Ethereum-based memecoins, supporting high-liquidity viral tokens
- Grouped configuration for Ethereum ecosystem focus, enabling chain-specific RSP and metric screening
- Flexible ticker replacement for emerging or favorite memecoins within the Ethereum layer
📊 Solana Memecoins
- Individual symbol inputs for up to 9 Solana-based memecoins, targeting fast-chain speculative plays
- Grouped setup for Solana ecosystem isolation, optimizing relative strength across high-velocity tokens
- Customizable for new Solana launches, integrating with RSP for momentum hierarchy
📊 SUI Memecoins
- Individual symbol inputs for up to 9 SUI-based memecoins, focusing on layer-1 innovation tokens
- Dedicated grouping for SUI chain analysis, facilitating ecosystem-relative performance ranking
- Adaptable for SUI-specific narratives, blending with metrics for targeted selection
📊 BASE/VIRTUAL Memecoins
- Individual symbol inputs for up to 9 BASE/VIRTUAL memecoins, covering emerging layer-2 and virtual assets
- Consolidated group for BASE/VIRTUAL screening, emphasizing cross-layer memecoin dynamics
- Versatile for virtual economy tokens, supporting RSP comparisons within niche categories
📡 Data Fetching
- Benchmark retrieval on demand for alpha or beta needs, using daily resolution for consistent periodicity
- Parallel asset close pulls via security functions for 36 memecoins, ensuring uniform timeframe data
- Specific chain baselines fetched separately for ETH, SOL, SUI, VIRTUAL to enable targeted RSP
- Na defaults for inactive assets, preventing errors in partial memecoin scans
- Confirmed bar gating for price updates, aligning with real-time execution fidelity
🔢 Calculation Functions
- Exchange prefix remover for clean ticker displays, stripping identifiers for concise labeling
- Returns calculator standardizing daily percentage changes, zero-filling gaps for continuity
- Alpha isolator via regression intercept, extracting benchmark-independent performance
- Beta quantifier through covariance ratio, measuring systematic sensitivity with safeguards
- Sharpe efficiency engine , annualizing mean over volatility with exponential noise reduction
- Sortino downside protector , looping negative deviations for targeted risk adjustment and scaling
- Omega distribution analyzer , accumulating excesses and shortfalls for gain-loss probability ratios
- ROC momentum extractor , delivering unbounded percentage shifts with na neutrality
- Constant source checker , filtering static data to avoid misleading RSP computations
- Smoothed RSI calculator , applying multi-type averages including volatility-responsive VIDYA
- Score generator , binary outcomes from level thresholds or MA crossovers on relative prices
- RSP scores calculator , aggregating binaries across chain baselines for ecosystem leadership
📊 Returns Calculations
- Daily returns series for all 36 memecoins, foundational for regression and ratio inputs
- Benchmark returns computed conditionally, serving as relative analysis baseline
📈 Alpha Calculations
- Per-memecoin alpha toggled and derived, isolating benchmark excess for speculative edge detection
- Regression-based intercepts across assets, feeding into binary outperformance flags
📈 Beta Calculations
- Per-memecoin beta activated on demand, quantifying chain volatility against market
- Covariance ratios for systematic exposure, enhancing risk context in memecoin rankings
⚖️ Sharpe Calculations
- Rolling annualized Sharpe for each memecoin, assessing efficiency in high-volatility plays
- Smoothed volatility-adjusted returns , parallel computation for cross-chain comparability
🛡️ Sortino Calculations
- Downside-focused Sortino [/b> per memecoin, emphasizing loss aversion in speculative assets
- Loop-based deviation summing [/b>, scaled annually with risk-free adjustment for precision
🔄 Omega Calculations
- Distributional omega for each memecoin, capturing tail risks in viral surges
- Target-threshold accumulation [/b>, smoothed for gain-loss probability insights
📉 ROC Calculations
- Momentum ROC [/b> across memecoins, unbounded percentage changes for trend velocity
- Period-specific extraction , toggled for short-term hype detection
🏆 RSP Calculations
- Price array storage for 36 memecoins, enabling relative ratio computations
- Per-asset RSP matrices [/b>, filling with smoothed RSI binaries on cross-memecoin ratios
- Grand combined array [/b>, flattening matrices for holistic rank derivation
- Summed totals per asset , aggregating RSP strengths for competitive positioning
🪙 Specific RSP Scores
- Chain baseline prices for ETH, SOL, SUI, VIRTUAL, anchoring ecosystem-relative computations
- 4-coin RSP scoring , generating binaries on cross-chain ratios for leadership identification
- Max score indexing , pinpointing the dominant chain for category-wide RSP4 flags
📊 Median & Binary Scores
- Enabled metric arrays , collecting valid values for central tendency computation
- Median extraction per metric, providing neutral benchmarks for outperformance flags
- Binary conversion loops , flagging above-median as positive for normalized scoring
- Na exclusion , ensuring only reliable data influences relative classifications
- Per-asset binary arrays , storing flags for weighted contribution to final composites
- RSP4 category flags , binary boosts for memecoins in the leading chain group
🎯 Weighted Scores
- Metric binary summation , averaging enabled flags for risk-return consensus
- RSP points integration , blending rank rewards with metric outcomes for hybrid intelligence
- RSP4 category addition , elevating scores for ecosystem-dominant memecoins
- Balanced weighting , allocating portions to metrics and RSP for multifaceted evaluation
- Last-bar computation , finalizing scores for display without historical interference
📋 Main Data Table
- 16-column matrix centering memecoins with RSP scores, metrics, binaries, RSP4, and final scores
- Header labeling [/b> for clarity, spanning asset identifiers, RSP, performance columns, and flags
- Value rendering , formatted decimals or dashes for unavailable metrics
- Binary color-coding , green for above-median, red below, gray for invalids
- RSP score highlighting , green/red based on positive outperformance
- RSP4 flag column , green for chain leaders, red otherwise
- Score culmination , white text on transparent cells for final eligibility gauge
- Text sizing [/b> uniformity, ensuring legibility in expanded memecoin grids
📊 Median Table
- Compact right-side panel , listing medians for enabled metrics as reference anchors
- Two-column simplicity , metric names left, values right for quick benchmarking
- Dash placeholders [/b> for inactive metrics, maintaining structure without clutter
- White text consistency , neutral presentation for objective central tendencies
🏆 Top Assets Table
- Left-side summary , ranking memecoin leaders by weighted scores in descending order
- Two-column focus , tickers paired with scores for executive overview
- Dynamic sorting [/b> via indices, limiting to top count for prioritized insights
- Prefix-cleaned names , concise labels enhancing scan speed across chains
- Decimal score formatting , white text for clean highlight of elite memecoins
✅ Key Takeaways
- Chain-segmented RSP [/b> uncovers memecoin leaders within Ethereum, Solana, SUI, and BASE/VIRTUAL ecosystems
- Category RSP4 flags boost scores for dominant chain performers, emphasizing viral potential
- Expanded 36-asset capacity scales screening for comprehensive memecoin universes
- Tiered tables [/b>—detailed main with RSP4, neutral medians, elite tops—streamline from scan to speculation
- Modular toggles and smoothings adapt to memecoin volatility, from hype cycles to corrections
- Rank rewards incentivize competitive RSP, revealing cross-chain alpha in speculative niches
- Daily alignment ensures timely insights, quota-efficient for high-volume memecoin tracking
Complete Trading Dashboard + Stop Loss Calculator
## **What Does This Indicator Do?**
This is like having a **smart trading assistant** that helps you:
1. ✅ Calculate exactly how much money to risk on each trade
2. ✅ Know when it's a good time to enter a trade (LONG or SHORT)
3. ✅ See what the market is doing right now
4. ✅ Never lose more money than you planned
---
## 🎯 **MAIN FEATURES (Explained Simply)**
### **1️⃣ Entry Score Window (Traffic Light System)**
- **What it does:** Tells you if NOW is a good time to buy (LONG) or sell (SHORT)
- **How it works:** Like a traffic light! 🚦
- **Green 80%+ = GO!** ✅ Very good entry opportunity
- **Yellow 60-80% = CAREFUL** ⚠️ Moderate opportunity
- **Red below 60% = STOP** 🛑 Not a good time
- **Best part:** It checks 3 different timeframes automatically (like asking 3 experts instead of 1!)
**Example:** If you see "LONG 85% ⭐⭐" = Strong signal to BUY!
---
### **2️⃣ Stop Loss Calculator (Your Safety Net)**
- **What it does:** Calculates EXACTLY where to exit if the trade goes wrong
- **Why you need it:** So you never lose your entire account!
**Simple Example:**
- You have $10,000 in your account
- You want to risk only 1% = $100
- The indicator shows you:
- ✅ Entry price: $50,000 (where to enter)
- ✅ Stop Loss: $49,000 (where to exit if losing)
- ✅ Take Profit: $53,000 (where to exit if winning)
- ✅ Position size: Exactly how much to buy
**Works for BOTH:**
- **Crypto/Stocks** (Bitcoin, Tesla, etc.)
- **Forex** (EUR/USD, GBP/USD) - Calculates in LOTS automatically!
---
### **3️⃣ Market Condition Score**
- **What it shows:** Is the market GREEDY 🔥 or FEARFUL 😰?
- **Why it matters:**
- High score (70+) = Market is excited, prices moving fast
- Low score (30-) = Market is scared, prices dropping
**Think of it like:** Checking if it's sunny ☀️ or stormy ⛈️ before going outside
---
### **4️⃣ Pivot Points (Support & Resistance)**
- **What it shows:** Important price levels where price might bounce or stop
- **Simple explanation:**
- **Support** = Floor (price might bounce UP from here) 🟢
- **Resistance** = Ceiling (price might bounce DOWN from here) 🔴
**Shows you:** How close the current price is to these important levels
---
### **5️⃣ Timeframe Bias (The Big Picture)**
- **What it shows:** Which direction are bigger traders moving?
- **Checks:** 4-Hour and Daily charts to see the "big money" direction
- **Why it matters:** Like checking which way the river flows before jumping in!
**Example:**
- 4H Bias: Bullish ▲ = Big traders are buying
- Daily Bias: Bullish ▲ = Even bigger traders are buying
- **Result:** Safer to trade LONG!
---
### **6️⃣ Technical Indicators (Simple)**
**RSI (Overbought/Oversold):**
- Above 70 = Price too high, might drop soon
- Below 30 = Price too low, might rise soon
**MACD (Momentum):**
- Bullish = Price has energy going UP 📈
- Bearish = Price has energy going DOWN 📉
**ATR (Volatility):**
- High = Price moving A LOT (dangerous but profitable)
- Low = Price moving slowly (safer but less profit)
**VWAP (Average Price):**
- Above VWAP = Price is strong ▲
- Below VWAP = Price is weak ▼
---
## 🎨 **VISUAL FEATURES**
### **Price Lines on Chart:**
- **Blue/Orange Line** = Your Entry Price
- **Red Dashed Line** = Your Stop Loss (exit here if losing)
- **Green Dashed Line** = Your Take Profit (exit here if winning)
### **Signal Dots on Chart:**
- **Green Triangle UP** = Good time to BUY (LONG) 🟢
- **Red Triangle DOWN** = Good time to SELL (SHORT) 🔴
- Shows the score on each dot!
---
## 🔔 **ALERTS**
Set alerts at different levels:
- **75%+** = Decent signal
- **80%+** = Good signal
- **85%+** = Strong signal
- **90%+** = EXCELLENT signal ⭐
You'll get notified on your phone when opportunities appear!
---
## ⚙️ **HOW TO USE (Step by Step)**
### **For Beginners:**
1. Add indicator to your chart
2. Set your **Deposit** amount (how much money you have)
3. Set **Position Size %** (2% is recommended = safe)
4. Set **Max Loss %** (1% is recommended = very safe)
5. Choose **Market Type**: Crypto/Stocks OR Forex
6. Watch the **Entry Score** - Wait for 80%+ signals!
7. When you see a good signal, check the **Stop Loss Calculator** for exact prices
### **For Advanced Traders:**
- Adjust **Risk/Reward Ratio** (Default 1:3 = risk $100 to make $300)
- Change **Leverage** (Higher = more profit but more risk!)
- Enable **Auto Direction Based on VWAP** (automatic LONG/SHORT)
- Use **ATR for Stop Loss** (dynamic stops based on volatility)
- Customize which sections to show/hide
---
## 💡 **REAL EXAMPLE**
**Scenario:** Trading Bitcoin
1. **Entry Score shows:** LONG 87% ⭐⭐ (EXCELLENT!)
2. **Stop Loss Calculator shows:**
- Entry: $45,000
- Stop Loss: $44,100 (2% below)
- Take Profit: $47,700 (1:3 ratio)
- Position Size: $200 with 5x leverage = $1,000 position
- Max Risk: $20 (1% of $2,000 deposit)
3. **Market Analysis shows:**
- 4H Bias: Bullish ▲
- Market Condition: 75 (Optimistic)
- RSI: 45 (Neutral, good for entry)
- Price near S1 Support
4. **Decision:** ✅ This is a GREAT setup! All signals aligned!
---
## ⚠️ **IMPORTANT SAFETY TIPS**
1. **Never risk more than 1-2% per trade** (Keep your account safe!)
2. **Wait for 80%+ entry scores** (Don't trade every signal)
3. **Always use Stop Loss** (Protect yourself!)
4. **Check higher timeframe bias** (Trade with the big trend)
5. **Start with small position sizes** (Learn first, profit later)
---
## 🎯 **WHO IS THIS FOR?**
✅ **Beginners:** Simple traffic light system + automatic calculations
✅ **Intermediate:** Multiple timeframe analysis + risk management
✅ **Advanced:** Full technical analysis + customizable parameters
✅ **Day Traders:** Fast signals on lower timeframes
✅ **Swing Traders:** Higher timeframe bias confirmation
✅ **Forex Traders:** Automatic lot size calculations
✅ **Crypto Traders:** Leverage and position size optimization
---
## 📱 **BEST PRACTICES**
1. Use on **15-minute to 4-hour charts** for best signals
2. Set **alerts at 85%+** for high-quality opportunities only
3. Always check **all 3 sections** before entering:
- Entry Score (80%+)
- Market Condition (not extreme fear/greed)
- Timeframe Bias (aligned with your direction)
4. **Paper trade first!** (Practice without real money)
5. Keep a trading journal of your entry scores vs results
---
This indicator is **100% FREE** and includes:
- ✅ Multi-timeframe entry scoring
- ✅ Complete stop loss calculator
- ✅ Market analysis dashboard
- ✅ Price level lines
- ✅ Signal dots with alerts
- ✅ Forex AND Crypto support
**No hidden features. No upgrades needed. Everything included!**
---
## ❓ **SIMPLE Q&A**
**Q: What's the best entry score to trade?**
A: Wait for 80% or higher (85%+ is even better!)
**Q: Can I use this for day trading?**
A: Yes! Works on any timeframe (15m, 1h, 4h, Daily)
**Q: Do I need other indicators?**
A: No! Everything you need is included
**Q: How much should I risk per trade?**
A: Start with 1% of your account (very safe!)
**Q: Does it work on Forex?**
A: Yes! It automatically calculates lot sizes for Forex
**Q: What's the Risk:Reward ratio mean?**
A: 1:3 means risk $100 to potentially make $300
**Q: Can I customize the dashboard?**
A: Yes! Show/hide any section in settings
---
## 📊 **PERFORMANCE TIPS**
To get the best results:
1. ⭐ Only trade when Entry Score is 80%+
2. ⭐ Check that 4H and Daily bias match your direction
3. ⭐ Enter near Support (for LONG) or Resistance (for SHORT)
4. ⭐ Use 1:3 or higher Risk:Reward ratio
5. ⭐ Never skip the Stop Loss!
---
**Remember:** This tool helps you make BETTER decisions, but it's not magic! Always practice good risk management and never trade with money you can't afford to lose.
**Good luck and trade safe! 🚀📈**
---
AssetIQ -> PROFABIGHI_CAPITAL🌟 Overview
The AssetIQ -> PROFABIGHI_CAPITAL indicator is an advanced multi-asset intelligence tool for cryptocurrency analysis, blending traditional risk-adjusted metrics with relative strength positioning (RSP) via RSI on cross-asset price ratios to compute comprehensive eligibility scores. It evaluates up to 25 assets against a benchmark, generating weighted composites from binary outperformance flags and rank-based points, displayed in detailed tables for median comparisons and top rankings to guide portfolio selection in competitive markets.
📅 General Settings
- Toggle for activating alpha to isolate excess returns beyond benchmark influence, highlighting unique asset drivers
- Toggle for enabling beta to quantify volatility correlation with the benchmark, aiding diversification assessments
- Toggle for incorporating Sharpe ratio to gauge overall efficiency of returns relative to total risk exposure
- Toggle for including Sortino ratio to prioritize returns adjusted specifically for downside volatility impacts
- Toggle for utilizing omega ratio to weigh probability-adjusted gains against losses above a target threshold
- Toggle for adding rate of change (ROC) to capture raw momentum shifts over a specified horizon
- Adjustable lookback periods for alpha and beta regressions, tuning between stability and recency in relative analysis
- Customizable benchmark symbol , such as market indices, to establish the reference frame for comparative evaluations
- Configurable Sharpe rolling window and smoothing for responsive risk-reward snapshots
- Extended Sortino and omega periods with risk-free rates and target returns for robust downside and distributional insights
- ROC horizon setting to balance short-term reactivity with trend confirmation
- Scalable asset count and top display limit for efficient screening from watchlists to full universes
📋 Table Settings
- Background transparency for semi-opaque overlays, ensuring readability while preserving chart context
- Border styling for clear delineation of data sections without visual clutter
- Text sizing options , from compact to prominent, to suit screen preferences and detail levels
🏷️ Ticker Settings
- Dedicated inputs for up to 25 cryptocurrency symbols, supporting major pairs across exchanges for broad coverage
- Flexible symbol formatting with prefix handling, enabling seamless integration of diverse tickers
- Conditional loading based on asset count, optimizing data retrieval for selected instruments only
📈 RSP Settings
- RSI length for relative strength computations, defining the oscillator period on cross-asset ratios
- Primary smoothing type , selectable from standard averages to advanced hull or variable index for signal refinement
- Primary smoothing length , adjusting lag to match analysis timeframe from intraday to weekly
- Secondary smoothing type , allowing layered processing or dynamic comparisons for deeper confirmation
- Secondary smoothing length , providing extended baseline for stable relative momentum readings
- Toggle for second MA comparison , shifting scoring from absolute levels to relative crossovers
- VIDYA volatility lookback , dynamically scaling smoothing to market dispersion for adaptive RSP
📡 Data Fetching
- Benchmark retrieval on demand for alpha or beta needs, using daily resolution for consistent periodicity
- Parallel asset close pulls via security functions, ensuring uniform timeframe data across symbols
- Na defaults for inactive assets, preventing errors in partial portfolio scans
- Confirmed bar gating for price updates, aligning with real-time execution fidelity
🔧 Core Functions
- Exchange prefix remover for clean ticker displays, stripping identifiers for concise labeling
- Returns calculator standardizing daily percentage changes, zero-filling gaps for continuity
- Alpha isolator via regression intercept, extracting benchmark-independent performance
- Beta quantifier through covariance ratio, measuring systematic sensitivity with safeguards
- Sharpe efficiency engine , annualizing mean over volatility with exponential noise reduction
- Sortino downside protector , looping negative deviations for targeted risk adjustment and scaling
- Omega distribution analyzer , accumulating excesses and shortfalls for gain-loss probability ratios
- ROC momentum extractor , delivering unbounded percentage shifts with na neutrality
📈 RSP Functions
- Constant source checker , filtering static data to avoid misleading RSP computations
- Smoothed RSI calculator , applying multi-type averages including volatility-responsive VIDYA
- Score generator , binary outcomes from level thresholds or MA crossovers on relative prices
- Array population routine , filling per-asset matrices with RSP binaries for cross-comparisons
- Combined matrix builder , concatenating RSP arrays into a unified grid for rank derivation
- Rank-based points assigner , scaling rewards from top positions to encourage competitive outperformance
📊 Calculations
- Daily returns series for all assets, foundational for regression and ratio inputs
- Per-asset alpha and beta toggled and computed, feeding relative strength arrays
- Sharpe, Sortino, omega, and ROC parallels, with na handling for robust aggregation
- RSP price arrays , storing historical closes for ratio-based RSI evaluations
- Per-asset RSP matrices , computing smoothed oscillators on relative pricing
- Summed RSP totals , aggregating binary strengths for initial rank seeding
📦 RSP Calculations
- Asset price fetching on confirmed bars, populating arrays for relative computations
- Matrix filling loops , applying RSP scoring across all active asset pairs
- Grand combined array , merging matrices into a flat structure for efficient ranking
- Per-asset sum arrays , totaling RSP strengths to establish competitive hierarchies
- Rank derivation , comparing sums to assign positions from leader to laggard
- Points scaling , tiered rewards diminishing from top ranks to foster differentiation
📊 Median & Binary
- Enabled metric arrays , collecting valid values for central tendency computation
- Median extraction per metric, providing neutral benchmarks for outperformance flags
- Binary conversion loops , flagging above-median as positive for normalized scoring
- Na exclusion , ensuring only reliable data influences relative classifications
- Per-asset binary arrays , storing flags for weighted contribution to final composites
⚖️ Weighted Scores
- Metric binary summation , averaging enabled flags for risk-return consensus
- RSP points integration , blending rank rewards with metric outcomes for hybrid intelligence
- Balanced weighting , allocating portions to metrics and RSP for multifaceted evaluation
- Last-bar computation , finalizing scores for display without historical interference
📋 Main Table Display
- 16-column matrix centering assets with metric values, binaries, ranks, points, and scores
- Header labeling [/b> for clarity, spanning asset identifiers and performance columns
- Value rendering [/b>, formatted decimals or dashes for unavailable metrics
- Binary color-coding , green for above-median, red below, gray for invalids
- Rank and points [/b> in dedicated columns, highlighting competitive positioning
- Score culmination [/b>, white text on transparent cells for final eligibility gauge
- Text sizing [/b> uniformity, ensuring legibility in dense layouts
📊 Median Table
- Compact right-side panel [/b>, listing medians for enabled metrics as reference anchors
- Two-column simplicity , metric names left, values right for quick benchmarking
- Dash placeholders [/b> for inactive metrics, maintaining structure without clutter
- White text consistency [/b>, neutral presentation for objective central tendencies
🏆 Top Assets Table
- Left-side summary [/b>, ranking leaders by weighted scores in descending order
- Two-column focus [/b>, tickers paired with scores for executive overview
- Dynamic sorting [/b> via indices, limiting to top count for prioritized insights
- Prefix-cleaned names [/b>, concise labels enhancing scan speed
- Decimal score formatting [/b>, white text for clean highlight of elite performers
✅ Key Takeaways
- Hybrid RSP integration [/b> elevates traditional metrics with cross-asset relative strength for superior selection
- Binary medians [/b> normalize outperformance, creating fair comparisons across diverse assets
- Weighted composites fuse risk, momentum, and positioning into actionable intelligence
- Tiered tables [/b>—detailed main, neutral medians, elite tops—streamline from scan to strategy
- Modular toggles and smoothings adapt to regimes, from bull hunts to bear shields
- Rank rewards incentivize competitive RSP, uncovering hidden portfolio alphas
- Daily alignment [/b> ensures timely insights, scalable for watchlists or full scans
Livermore's Pyramiding Trading - 3Commas [SwissAlgo]
📊 J. LIVERMORE'S PYRAMIDING TRADING - 3Commas Integrated
A Trading Approach Inspired by Jesse Livermore's Position Building Principles
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DISCLAIMER
This indicator is an educational tool based on historical trading principles. Past performance is not indicative of future results. Trading involves substantial risk of loss. Only trade with capital you can afford to lose. You are responsible for all trading decisions.
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📚 WHO WAS JESSE LIVERMORE?
Jesse Livermore (1877-1940) was one of the greatest traders in history.
His core insight: "Most traders do everything backward."
♦ "They deploy all capital at once" → Livermore entered with a small fraction of his capital (he started with a 'test position' to validate his trade idea and waited for market confirmation to deploy more, building positions in steps = "pyramiding")
♦ "They average down" (DCA) → Livermore added to trades showing good results only, and never to losing trades, as the trend kept aligning with his trade idea
♦ "They use arbitrary % stops" → Livermore exited when structure appeared broken (he trailed his stop loss to try to protect unrealized profit - if any)
♦ "They take profits too early or set arbitrary TP%" → Livermore let trades showing positive results run until proven wrong (trial take profit)
💬 "I always made money when I was sure I was right before I began. What beat me was not having enough brains to stick to my own game."
— Jesse Livermore
This indicator tries to translate his principles into a SYSTEMATIC FRAMEWORK :
BO = Base Order (first order, base of the pyramid)
PO = Pyramid Orders (additional layers of capital deployed as long as the 'tape' does not invalidate the trade idea)
♦ Test First (BO - 20%) - Small entry to test your idea. If wrong, lose small. If right, can consider pyramiding into strength.
♦ Build Position Size (PO1-3 - 80%) - Add only as trend unfolds favorably (the indicator uses specific Fibonacci levels to track milestones - 0.618, 1.0, 1.272 - and looks for strong confluence among price, volume, trend, momentum, break of resistance/support levels to suggest and trigger actions: entries, exit)
♦ Attempt to Protect Capital - Dynamic stops: the indicator trails the stop loss, to try to protect potential gains from previous steps (if any)
♦ Discipline - Trades fire only when ALL conditions align
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🎯 INDICATOR FEATURES
You map 3 points on the chart → The indicator generates a systematic trading plan structure based on your wave analysis.
✓ Auto-detects trade direction: Uptrend wave (A➚B➘C) = Long signals | Downtrend wave (A➘B➚C) = Short signals
✓ Entry/exit prices: BO, PO1, PO2, PO3, and dynamic EXIT (trailing stop)
✓ Real-time condition monitoring: Live ✓/✗ checks for each order (price closes + volume + trend + pivot breaks + candle quality + sequence)
✓ Visual trade execution: Green labels mark entries (BO/PO1/PO2/PO3), red labels mark EXIT
✓ Optional 3Commas automation: JSON webhooks for hands-free execution via Signal Bots
⏰ Recommended Timeframes: 1H, 4H, Daily
(Lower timeframes like 15m/5m produce excessive noise and false signals)
💬 "Watch the market leaders, the stocks that have led the charge. That is where the action is and where the money is made."
— Jesse Livermore
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⚙️ SETUP IN 3 STEPS
🟡 STEP 1: Map Your Wave (Points A → B → C)
Identify a completed wave pattern:
For LONGS:
♦ Point A = Swing low (wave start)
♦ Point B = Swing high (impulse end)
♦ Point C = Pullback low (retrace end - where next wave may begin)
For SHORTS:
♦ Point A = Swing high (wave start)
♦ Point B = Swing low (impulse end)
♦ Point C = Pullback high (retrace end - where next wave may begin)
How to set points:
Settings → Enter dates manually OR drag the vertical lines directly on the chart (easier - just click and drag the pre-mapped A/B/C lines)
Requirements (auto-validated by code):
✓ All dates must be in the past (Point C = completed retrace, not forming)
✓ Clear impulse A→B (minimum 5% move)
✓ Clear retrace B→C (minimum 3% pullback)
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🟡 STEP 2: Set Budget & Allocation
Settings → "TRADE PARAMETERS"
♦ Total Budget: $10,000 (example - capital for THIS trade only, not your entire account)
♦ Allocation (must total 100%):
BO = 20% ($2,000) - test position
PO1 = 25% ($2,500) @ Fib 0.618
PO2 = 30% ($3,000) @ Fib 1.0
PO3 = 25% ($2,500) @ Fib 1.272
💬 "It was never my thinking that made big money for me. It was always my sitting. Men who can both be right and sit tight are uncommon."
— Jesse Livermore
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🟡 STEP 3: Monitor Your Trade Plan Table
The table (top-right corner) has 4 sections that guide your execution:
BUDGET DEPLOYMENT
♦ Trigger prices for each order (BO auto-calculated at 0.5 Fib between B-C)
♦ Dollar amount per entry
♦ Fibonacci level assigned to each PO
ENTRY/EXIT CONDITIONS
Each column (BO, PO1, PO2, PO3) shows live status (✓ or ✗) for:
♦ Price: 2 consecutive closes (BO) | 3 consecutive closes (POs)
♦ Volume: OBV directional alignment OR volume spike above average
♦ Trend: Normal or Strong Bull/Bear (no entries in Uncertain trend)
♦ Pivot: Nearest resistance (longs) or support (shorts) broken
♦ Clean Candle: Momentum without reversal wicks <30% (POs only)
♦ Sequence: Prior order must have fired first (POs only - no skipping levels)
TRIGGERED?
Shows execution status for each order (✓ = fired, ✗ = waiting)
If using 3Commas: ✓ confirms JSON alert was sent to your bot for real execution
VALIDATIONS
✓ Green = All checks passed, setup is valid
⚠️ Yellow = Warning (e.g., budget doesn't equal 100%, deep retrace)
✗ Red = Error (e.g., dates in wrong order, invalid wave structure)
⚠️ Wait for ALL ✓✓✓✓✓ (or ✓✓✓✓✓✓) to align in a column before that order fires at bar close
💬 "The game of speculation is the most uniformly fascinating game in the world. But it is not a game for the stupid, the mentally lazy, the person of inferior emotional balance, or the get-rich-quick adventurer."
— Jesse Livermore
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📊 CHART VISUALS - READING THE INDICATOR
Fibonacci Extension Lines
After mapping A-B-C, horizontal lines extend to the right:
♦ Solid green/red lines = Active PO entry levels (0.618, 1.0, 1.272)
♦ Dotted gray lines = Reference Fib levels used for exit tracking (2.0, 2.618, 3.0, etc.)
♦ Labels on right = Show level and price: "Fib 0.618 / $67,324 "
Entry/Exit Price Lines
♦ Thick green line (longs) / red line (shorts) = BO entry price with direction label
♦ Dashed red line = Current EXIT price (your trailing stop loss - appears after BO fires and moves as price extends)
Trade Execution Labels
Visual confirmation when orders fire on the chart:
♦ Green labels (below/above candles) = BO, PO1, PO2, PO3 entries executed
♦ Red label = EXIT triggered (position closed)
Trend Strength Indicator (EMA Line)
The thick colored line shows real-time trend status:
♦ Bright lime = Strong bullish trend
♦ Light green = Normal bullish trend
♦ Bright red = Strong bearish trend
♦ Light red = Normal bearish trend
♦ Gray = Uncertain/weak trend (no entries fire in this state)
Entries require at least Normal trend strength aligned with your trade direction.
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
— Jesse Livermore
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🔧 ENTRY LOGIC - TECHNICAL DETAILS
💬 "The big money was never made in the buying or the selling. The big money was made in the waiting."
— Jesse Livermore
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🟢 BASE ORDER (BO) - TEST POSITION
BO Price Calculation
Auto-calculated at the 0.5 Fibonacci retracement between Point B and Point C
Formula: (Price B + Price C) / 2
Why this level?
♦ Midpoint between impulse end (B) and retrace end (C)
♦ Breakout above/below suggests retrace may be complete
♦ Designed to help position BO below all Fib extensions (to control sequence issues)
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BO Entry Conditions - ALL 5 Must Align:
1️⃣ PRICE: 2 Consecutive Closes Beyond BO
♦ Longs: close > BO AND close > BO
♦ Shorts: close < BO AND close < BO
♦ Why: Designed to confirm breakout commitment and filter fakeouts
2️⃣ TREND: Normal OR Strong Trend Aligned
♦ Detection: 18-period EMA + ADX/DMI + higher timeframe slope
♦ States: Strong Bull/Bear (ADX>30), Normal Bull/Bear (price vs EMA), Uncertain
♦ Confirmation: Requires 3 consecutive bars in the same state (to reduce flip-flop)
♦ BO accepts: Normal OR Strong (you're testing early, basic alignment sufficient)
3️⃣ PIVOT: Nearest Resistance/Support Broken
♦ Storage: 60 most recent pivot highs/lows (dynamic lookback per timeframe)
♦ Longs: Nearest pivot HIGH above BO → must break with 2 closes
♦ Shorts: Nearest pivot LOW below BO → must break with 2 closes
♦ Price Discovery: If no pivot exists beyond BO = auto-pass
♦ Why: Aims to confirm momentum has overcome previous rejection zones
4️⃣ VOLUME: OBV Aligned OR Spike
♦ Directional OBV: OBV > 20-EMA (longs) OR OBV < 20-EMA (shorts)
♦ OR Volume Spike: Current volume > 20-period SMA
♦ Why: Checks for institutional participation signals
5️⃣ VALIDATIONS: Setup Valid (✅)
♦ Dates valid (A < B < C, all in past)
♦ Wave structure valid (min 5% impulse, min 3% retrace)
♦ Budget allocation = 100%
♦ Prices detected at all points
⚠️ BO fires once per bar close. Flag set permanently until trade resets.
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🔺 PYRAMID ORDERS (PO1-3) - PYRAMIDING INTO STRENGTH
💬 "Never buy a stock because it has had a big decline from its previous high. The big money was never made in the stock market by buying on declines."
— Jesse Livermore
PO Price Calculation
Fixed Fibonacci extensions from Point C:
Formula: Price C ± (Impulse Range × Fib Level)
Where: Impulse Range = |Price B - Price A|
Default Levels:
♦ PO1 @ Fib 0.618 (Golden Ratio)
♦ PO2 @ Fib 1.000 (Full impulse repeat)
♦ PO3 @ Fib 1.272 (Fibonacci sequence extension)
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PO Entry Conditions - ALL 6 Must Align (STRICTER):
1️⃣ PRICE: 3 Consecutive Closes Beyond PO
♦ Longs: close > PO AND close > PO AND close > PO
♦ Shorts: close < PO AND close < PO AND close < PO
♦ Why: Higher conviction needed when adding capital (3 vs 2 closes for BO)
2️⃣ TREND: Same as BO
Normal OR Strong trend must remain aligned with trade direction
3️⃣ PIVOT: Per-Level Pivot Break
♦ Each PO checks its OWN nearest pivot (not shared with BO)
♦ Same 2-close break requirement
♦ PO3 Exception: Price discovery allowed (no pivot required if already profitable)
4️⃣ VOLUME: Same as BO
Sustained confirmation required (not weakening)
5️⃣ CLEAN CANDLE: <30% Reversal Wick (NEW)
♦ Filter: Uses ATR(14) - candles < ATR auto-pass (consolidation noise)
♦ Longs: Upper wick < 30% of candle range (no rejection at top)
♦ Shorts: Lower wick < 30% of candle range (no rejection at bottom)
♦ Why: Don't pyramid into weakness/rejection - only add on clean momentum
♦ Not checked for BO: Test position tolerates some wick risk
6️⃣ SEQUENCE: Prior Order Fired
♦ PO1 requires: BO fired
♦ PO2 requires: PO1 fired
♦ PO3 requires: PO2 fired
♦ Why: No skipping levels - disciplined building only
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⚙️ KEY DIFFERENCE:
BO (20% capital) = Lighter requirements, testing your idea early
POs (80% capital) = Stricter requirements, adding only to confirmed winners
♦ BO: 2 closes | POs: 3 closes
♦ BO: No candle check | POs: Clean candle required
♦ BO: Independent | POs: Sequential (must follow order)
♦ BO: No price discovery | PO3: Allows price discovery when profitable
💬 "Profits always take care of themselves, but losses never do. The speculator has to ensure himself against considerable losses by taking the first small loss."
— Jesse Livermore
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🚪 EXIT LOGIC - TECHNICAL DETAILS
🔴 EXIT PHILOSOPHY
The indicator uses TWO INDEPENDENT EXIT TRIGGERS (whichever fires first):
1) Structural Breakdown
Price breaks through the EXIT level with confirmation
2) Trend Reversal
Trend flips against your position AND price breaks EXIT level
Why two methods?
♦ Structure = price-based protection (hard stop)
♦ Trend = momentum-based exit (early warning when market character changes)
♦ Combined: Exit either when proven wrong (structure) or when conditions no longer favor your direction (trend)
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🔴 EXIT PRICE CALCULATION
The EXIT price (your stop loss) adjusts dynamically based on position size:
BEFORE PO3 Fires (Fixed Stops):
♦ BO only = Stop at Point C (small position, tight stop near entry)
♦ PO1 fired = Stop at Fib 0.5 (moved to breakeven zone)
♦ PO2 fired = Stop at Fib 0.786 (protecting partial profits)
AFTER PO3 Fires (Trailing Stops):
♦ Tracking: Monitors the highest Fib reached (longs) or the lowest Fib reached (shorts)
♦ Placement: EXIT moves 1-2 Fib levels below the highest (longs) or above the lowest (shorts)
♦ Example: Price reaches Fib 2.618 → EXIT trails up to Fib 2.0
♦ Purpose: Designed to protect accumulated profits while allowing room for normal pullbacks
💬 "It never was my thinking that made the big money for me. It was always my sitting. Men who can both be right and sit tight are uncommon."
— Jesse Livermore
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🔴 EXIT CONDITIONS
Exit Speed (Based on Risk Exposure):
♦ Full position (PO3 fired) = 1 close required (fast exit - more capital at risk)
♦ Partial position (BO/PO1/PO2 only) = 2 closes required (confirmation - less urgency)
METHOD 1: Structural Breakdown
Price violates the EXIT level with clean momentum:
For Longs:
♦ Price closes BELOW EXIT level (1 or 2 closes depending on position size)
♦ Clean candle required (lower wick < 50% of range - no false breakdown)
For Shorts:
♦ Price closes ABOVE EXIT level (1 or 2 closes depending on position size)
♦ Clean candle required (upper wick < 50% of range - no false breakout)
Why clean candle check?
Designed to reduce exits on wicks/fakeouts. If there's a large reversal wick (>50%), it suggests buyers/sellers are defending the level - not a true breakdown.
METHOD 2: Trend Reversal
Market character shifts against your position:
For Longs:
♦ Trend shifts from Bull → Normal Bear OR Strong Bear
♦ AND price breaks below EXIT level (same close requirements)
For Shorts:
♦ Trend shifts from Bear → Normal Bull OR Strong Bull
♦ AND price breaks above EXIT level (same close requirements)
Why this matters?
♦ Proactive exit before structural stop is hit
♦ If the trend that confirmed your entries reverses, the setup is invalidated
♦ Livermore principle: Exit when market proves you wrong, don't wait for max pain
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⚠️ EXIT BEHAVIOR
♦ Fires once per bar close (same as entries)
♦ Resets all tracking after exit (ready for fresh trade setup)
♦ Clears flags: boSignalFired, po1/po2/po3SignalFired, highestFib/lowestFib tracking
♦ If using 3Commas: Sends exit_long or exit_short JSON (market order closes 100% position)
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
— Jesse Livermore
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🤖 3COMMAS AUTOMATION (OPTIONAL)
💬 "There is the plain fool, who does the wrong thing at all times everywhere, but there is also the Wall Street fool, who thinks he must trade all the time."
— Jesse Livermore
Automation designed to help remove emotion and support disciplined execution.
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⚡ QUICK SETUP IN 5 STEPS
STEP 1: Create Your Signal Bots
You need 2 SEPARATE BOTS (one for Longs, one for Shorts):
Go to 3Commas → Bots → Create Bot → Select "Signal Bot"
Basic Settings:
♦ Bot Name: "Livermore Long - " (example: "Livermore Long - BTCUSDT")
♦ Exchange: Your connected exchange
♦ Trading Pair: Must match TradingView chart exactly
♦ Strategy: Custom Signal
♦ Direction: LONG (for first bot) or SHORT (for second bot)
♦ Max Active Deals: 1
⚠️ CRITICAL SETTINGS:
Entry Orders:
♦ Toggle ON: "Entry Orders"
♦ Volume per Order: "Send in webhook, quote"
♦ Why: This lets the indicator control exact $ amounts per order (BO=$2K, PO1=$2.5K, etc.)
♦ If you skip this: Orders will use wrong sizes and break your allocation plan
Exit Orders:
♦ Toggle ON: "Exit Orders"
♦ Volume per Order: "100 Position %"
♦ Why: Closes your entire position when EXIT signal fires
♦ Toggle OFF: "Take Profit" (managed by indicator)
♦ Toggle OFF: "Stop Loss" (managed by indicator)
Click "Start Bot" for both Long and Short bots.
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STEP 2: Get Your Bot Credentials
For EACH BOT (Long and Short):
♦ Open the bot → Click "Orders" tab
♦ Scroll down to "Webhook Messages" section
♦ Copy these 3 values:
bot_uuid (long string like: a362cbcf-7e68-4379-a83d-ae6e47dba656)
secret (very long token starting with: eyJhbGciOiJ...)
webhook URL (refer to 3commas to get exact webhook - signal bots)
Note: The secret is usually the same for both bots, but the bot_uuid is different.
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STEP 3: Enter Credentials in Indicator
Back in TradingView:
♦ Open indicator Settings
♦ Find section: "1️⃣ INTEGRATE 3COMMAS"
♦ Paste:
Long = Your Long bot UUID
Short = Your Short bot UUID
Secret = Your secret token (same for both)
♦ Click "OK"
The indicator now has everything needed to build JSON payloads.
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STEP 4: Create TradingView Alert
This alert bridges TradingView → 3Commas. ONE ALERT HANDLES ALL SIGNALS (BO, PO1, PO2, PO3, EXIT).
How to create:
♦ Right-click chart → "Add Alert" (or click clock icon)
♦ Condition: Select this indicator from dropdown
♦ Trigger: "Any alert() function call"
♦ Alert Name: "Livermore Pyramiding - "
♦ Message: Leave default (indicator sends its own JSON)
♦ Webhook URL: Paste your 3Commas webhook URL from Step 2
♦ ⚠️ Alert Frequency: "Once Per Bar Close" (CRITICAL - controls duplicate orders)
♦ Expiration: Open-ended (or set specific date)
♦ Click "Create"
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STEP 5: Test Before Going Live
🧪 NEVER TEST WITH REAL CAPITAL FIRST. Use one of these methods:
Test 1: Check Bot Status
♦ 3Commas → Bots → Both bots show "Active" (green)
♦ Click into each bot → Orders tab → Should say "Waiting for signal"
Test 2: Verify Alert Active
♦ TradingView → Alerts panel (bell icon)
♦ Your alert should show "Active" status
Test 3: Paper Trade / Tiny Position
♦ Use 3Commas paper mode if available, OR
♦ Set Total Budget to $10-50 for first real test
♦ Map a wave that's about to trigger
♦ Watch if orders actually appear on 3Commas
Test 4: Check JSON Format
♦ When alert fires → TradingView Alerts → Click your alert
♦ Look at "History" or "Log"
♦ Verify JSON has: bot_uuid, secret, action, price, amount
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🛠️ COMMON ISSUES & SOLUTIONS
✗ Problem: Orders not appearing on 3Commas
Possible causes:
♦ Wrong webhook URL → Must be exact 3Commas URL (check for typos)
♦ Bot paused → Check bot status must be "Active" (green)
♦ Wrong bot UUID → Verify you copied Long UUID for longs, Short UUID for shorts
♦ Secret mismatch → Double-check secret is correct
♦ Exchange API issues → Verify exchange connection in 3Commas settings
How to debug:
♦ 3Commas → Your Signal Bot → Orders tab
♦ Look for "Rejected Signals" section
♦ Should show error messages if webhook failed
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✗ Problem: Orders executing at wrong prices
Possible causes:
♦ Limit order not filled → Price gapped through your level before order filled
♦ Slippage on exits → Exits use market orders (intentional - speed over exact price)
♦ Exchange minimums → Some exchanges have minimum order sizes
Solution:
♦ Entries use limit orders (wait for exact price - may not fill if price gaps)
♦ Exits use market orders (prioritize fast execution when structure breaks)
♦ This is INTENTIONAL DESIGN following Livermore's principle: exit when proven wrong
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✗ Problem: PO orders firing out of sequence or skipping
Possible causes:
♦ Alert not set to "Once Per Bar Close" → Change alert frequency setting
♦ Multiple alerts running → Delete old/duplicate alerts for this indicator
♦ Conditions changed mid-bar → Indicator only fires at bar close (protective feature)
Solution:
♦ Keep only 1 active alert per indicator instance
♦ Always use "Once Per Bar Close" frequency
♦ Wait for full bar to close before signals can fire
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✗ Problem: Bot not closing position on EXIT
Possible causes:
♦ Exit order setting wrong → Check bot settings
♦ Wrong JSON action → Should be "exit_long" or "exit_short"
♦ No position open → Can't close what doesn't exist
Solution:
♦ Verify: Bot Settings → Exit Orders → Volume per Order = "100 Position %"
♦ Check alert history for correct JSON payload
♦ If stuck: Manually close position in 3Commas, then fix settings
♦ Delete and recreate alert if JSON format is wrong
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🔒 SECURITY BEST PRACTICES
♦ Never share bot UUID or Secret - Treat them like passwords
♦ Use restricted API keys - Limit to specific pairs, disable withdrawals
♦ Start small - Test with $10-50 first, scale up only after success
♦ Monitor first trades - Don't set-and-forget immediately
♦ Delete old alerts - If you change A/B/C points, delete old alert and create new one
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📊 PREFER MANUAL TRADING?
Skip 3Commas entirely and use the indicator for planning only:
♦ Watch Trade Plan table for ✓✓✓✓✓ alignment
♦ Manually place limit orders at displayed prices
♦ Manually move stop loss as EXIT price updates
♦ Manually close when EXIT signal fires
Benefits: Full control, no API concerns, can override based on context
Drawbacks: Must watch chart constantly, emotions can interfere, may miss signals
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✅ FINAL CHECKLIST BEFORE LIVE TRADING
✓ Both Signal Bots created (Long + Short)
✓ Entry Orders: Volume = "Send in webhook, quote"
✓ Exit Orders: Volume = "100 Position %"
✓ Take Profit and Stop Loss disabled in bots
✓ Bot UUIDs and Secret entered in indicator
✓ TradingView alert created with correct webhook
✓ Alert frequency = "Once Per Bar Close"
✓ Alert status shows "Active"
✓ Tested with small amounts successfully
✓ Trade Plan table shows ✅ (no validation errors)
✓ Understand your risk per trade
Once all checked: You're ready for automated pyramiding execution.
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💡 KEY REMINDERS - BEFORE YOU TRADE
💬 "The speculator's chief enemies are always boring from within. It is inseparable from human nature to hope and to fear."
— Jesse Livermore
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⚠️ COMMON MISTAKES (AVOID THESE)
Mapping Incomplete Waves
♦ Point C must be in the PAST (completed retrace, not currently forming)
♦ Don't map a wave that's still developing - wait for confirmation
♦ Minimum requirements: 5% impulse (A→B), 3% retrace (B→C)
Ignoring Validation Warnings
♦ Never create alerts when status shows ✗ (red) or ⚠️ (yellow)
♦ Fix all errors first: dates in order, budget = 100%, valid wave structure
♦ Common issues: dates in future, Point C above B (longs) or below B (shorts)
Premature Manual Entries
♦ Don't enter just because price touched the level
♦ Wait for ALL ✓✓✓✓✓ (or ✓✓✓✓✓✓) to align in Trade Plan table
♦ Patience pays - partial confluence = partial edge = higher risk of losing trades
Wrong Timeframe Selection
♦ Avoid: 15m, 5m, 1m (too much noise, false signals)
♦ Use: 1H, 4H, Daily (cleaner structure, better confluence)
♦ Lower timeframes require faster decisions and produce more whipsaws
Over-Risking Capital
♦ Trade budget ≠ Account size
♦ Never risk capital you can't afford to lose
♦ One bad trade should NOT destroy your account
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✅ LIVERMORE PRINCIPLES IN ACTION
Confirmation > Prediction
♦ Don't predict where price will go
♦ Wait for price to INDICATE direction via pivots + volume + trend
♦ Test first (BO 20%), build only when confirmed (POs 80%)
💬 "A man must believe in himself and his judgment if he expects to make a living at this game."
Pyramid on Strength, Never Weakness
♦ Add only when: 3 closes + clean candles + volume + pivot breaks
♦ Never average down (DCA into losers)
♦ If BO wrong, take small loss fast - don't hope and add more
💬 "Never buy a stock because it has had a big decline from its previous high."
Respect Market Structure
♦ Pivots = where smart money previously acted (support/resistance)
♦ Breaking them = momentum overcoming barriers
♦ Entering before pivot break = entering into known rejection zones
Trend is Your Friend
♦ Never pyramid against the trend
♦ If trend shifts to Uncertain or reverses → no new entries
♦ Exit when trend proves you wrong (don't fight it)
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
Discipline > Emotion
♦ Can't "almost" have all conditions met
♦ Either 100% aligned (all ✓) or you wait
♦ No exceptions, no "this time is different"
♦ Automation designed to help remove emotion - consider using 3Commas
💬 "It never was my thinking that made the big money for me. It always was my sitting."
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🎯 FINAL THOUGHT
This indicator is a SYSTEMATIC FRAMEWORK, not a magic solution. It translates Livermore's century-old principles into actionable rules:
♦ Test small, build big
♦ Add to winners, cut losers fast
♦ Let structure guide exits
♦ Stay disciplined when emotions scream
The market will test your patience, discipline, and conviction. The indicator aims to reduce guesswork - but YOU still need to:
♦ Find valid wave structures
♦ Choose appropriate market conditions
♦ Size positions properly
♦ Accept losses as part of the game
💬 "The game of speculation is the most uniformly fascinating game in the world. But it is not a game for the stupid, the mentally lazy, the person of inferior emotional balance, or the get-rich-quick adventurer."
— Jesse Livermore
The Eligible Asset Power Table -> PROFABIGHI_CAPITAL🌟 Overview
The Eligible Asset Power Table is a multi-asset screening dashboard that assesses cryptocurrency portfolios across multiple momentum, risk, and relative metrics to generate eligibility scores. It combines RSI variants, rate of change layers, Sharpe ratios, momentum RSI, price delta analysis, and beta exposure to rank assets, helping traders identify high-conviction opportunities through dual-mode scoring and visual tables.
⚙️ General Settings
- Evaluation mode toggle between aggressive averaging for nuanced scoring or conservative consensus requiring all conditions met for full eligibility
- Number of assets to screen, adjustable up to the platform's data fetch limits for focused or comprehensive portfolio reviews
- Count of top-ranked assets for a dedicated summary table, customizable to highlight leading candidates without overwhelming the display
📊 Indicator Parameters - RSI#1
- Source price selection for RSI input, allowing adaptation to closes, highs, or other series for tailored momentum sensitivity
- Period length for the shorter RSI variant, tuning detection of near-term overbought or oversold zones
- Primary smoothing moving average type, from basic to advanced options like hull or variable index for refined signal clarity
- Length for the first smoothing layer, balancing lag and responsiveness in volatile conditions
- Secondary smoothing moving average type, enabling dual-layer processing or crossover comparisons for added confirmation
- Length for the second smoothing layer, providing deeper trend stability
- Toggle for second MA comparison mode, shifting from fixed thresholds to dynamic relative movements
- Volatility lookback for adaptive smoothing when using variable index methods, responding to market dispersion
📊 Indicator Parameters - RSI#2
- Period length for the medium-term RSI variant, capturing sustained momentum beyond immediate fluctuations
- Primary smoothing moving average type applied to the longer RSI, consistent with RSI#1 for uniform processing
- Length for the first RSI#2 smoothing, optimizing for intermediate trend persistence
- Secondary smoothing moving average type, supporting layered refinement or bullish/bearish crossovers
- Length for the second RSI#2 smoothing, enhancing equilibrium zone reliability
- Toggle for second MA comparison, favoring motion-based conditions over static levels
- Volatility lookback specific to RSI#2's adaptive smoothing, scaling to regime changes
📈 Indicator Parameters - ROC#1
- Period length for the shortest rate of change, emphasizing immediate price acceleration for quick trend shifts
📈 Indicator Parameters - ROC#2
- Period length for the medium rate of change, evaluating ongoing momentum to validate directional strength
📈 Indicator Parameters - ROC#3
- Period length for the longest rate of change, assessing extended trends to confirm multi-period alignment
⚡ Indicator Parameters - Sharpe Ratio
- Lookback period for return averaging and volatility measurement, defining the window for efficiency snapshots
- Smoothing period on raw ratios, applying exponential decay to highlight persistent risk-reward patterns
- Buy threshold for positive conditions, establishing the minimum efficiency level for asset qualification
- Sell threshold for negative flags in averaging mode, pinpointing low-efficiency underperformers
🎯 Momentum RSI Parameters
- Momentum input period, deriving price changes to feed into RSI for velocity-driven insights
- RSI period on the momentum series, normalizing changes into overbought/oversold signals
- Primary smoothing moving average type on momentum RSI, selectable for signal purification
- Length for the first momentum RSI smoothing, aligning lag with trading horizons
- Secondary smoothing moving average type, facilitating comparative layers for crossover setups
- Length for the second momentum RSI smoothing, adding baseline robustness
- Toggle for second MA comparison, prioritizing relative dynamics over absolute readings
- Volatility lookback for momentum RSI's adaptive smoothing, attuning to velocity dispersion
📊 Indicator Parameters - Price Delta RSI
- Condition type between raw delta or RSI-transformed, choosing direct flow analysis or oscillator normalization
- Period for price delta calculation, quantifying net changes to reveal underlying pressure
- RSI period applied to delta, smoothing flow into bounded momentum readings
- Primary smoothing type for delta RSI, from averages to hull for delta refinement
- Length for the first delta RSI smoothing, tuning to flow trends in ranging or trending phases
- Secondary smoothing type, enabling dual-MA for enhanced crossover precision
- Length for the second delta RSI smoothing, bolstering signal stability
- Toggle for second MA comparison on delta RSI, emphasizing motion over static hurdles
- Volatility lookback for delta RSI's adaptive smoothing, adapting to flow-specific variability
📉 Beta Parameters
- Benchmark symbol choice, such as market indices, to gauge asset sensitivity against broader movements
- Lookback period for beta estimation, ensuring sufficient data for covariance while staying current
💼 Assets Configuration
- Sequential symbol inputs for up to 39 assets, supporting diverse crypto pairs across exchanges
- Conditional data loading by count, activating fetches only for selected instruments to conserve resources
- Prefix handling for clean display, stripping exchange details for ticker focus
- Broad compatibility for majors, mid-caps, or niche tokens, enabling sector or theme-based scans
🔧 Helper Functions
- Versatile moving average applicator, supporting multiple types including exponential variants and volatility-adjusted for flexible smoothing
- Sharpe ratio engine, annualizing mean returns over volatility with optional decay for trend focus
- Beta regressor, pulling benchmark data to compute relative risk via return covariances
- Layered ROC calculators, delivering percentage changes across horizons for momentum stacking
📊 Indicator Calculations
- Dual RSI systems with multi-MA options, scoring on optimal ranges or crossover confirmations for balanced strength
- Triple ROC cascade from acute to chronic, binary scoring on positivity to align short, medium, and long trends
- Sharpe derivation prioritizing excess efficiency, with thresholds gating high-reward low-risk assets
- Momentum RSI fusing velocity into RSI, smoothed for level or motion-based bullish filters
- Price delta probing net flow, raw or RSI-normalized, with adaptive layers for directional purity
- Beta isolating systematic exposure, supplementing scores with market-context relativity
🎯 Asset Metrics Calculation
- Parallel per-asset pipeline fetching and computing metrics, unpacking into arrays for centralized handling
- Binary condition evaluation per indicator: thresholds, crossovers, or signs, feeding into mode-specific aggregation
- Eight-metric blend: RSIs, ROCs, Sharpe, momentum RSI, delta, averaged aggressively or unanimous conservatively
- Beta as orthogonal factor, weighting top ranks without score dilution
- Neutral na defaults, preserving evaluations amid data gaps
📦 Data Storage Arrays
- Fixed-size arrays for names, metrics, conditions, and flags, indexed by asset order for efficient access
- Segregated storage for raw values, binaries, and composites, supporting sorting and retrieval
- Scalable to max assets, minimizing overhead in partial loads
📊 Data Retrieval for All Assets
- Conditional security pulls aligned to chart timeframe, ensuring consistent multi-symbol data
- Metrics function per instrument, distributing results to arrays for unified processing
- Benchmark-embedded beta calls, avoiding extra fetches
- Last-bar gating for snapshot accuracy, sidestepping repaints
📊 Main Table for All Assets
- Centered wide-format table listing assets leftward with metric columns spanning conditions and beta
- Headers labeling RSI layers, ROC trio, Sharpe, momentum, delta, beta, and final score for metric traceability
- Green/red cell text for met/failed conditions, white neutrals, with score highlighting above midpoint
- Ticker truncation for compactness, transparent overlay for pane integration
🏆 Top Assets Table
- Left-aligned rankings by score-beta composite, descending to prioritize leaders
- Compact four-column view: ticker, score, beta, Sharpe with threshold colors for efficiency triage
- Temporary key sorting, row clearing for updates, limited to user count
- Visual cues mirroring main table, flagging high-Sharpe standouts
✅ Key Takeaways
- Fuses diverse metrics into probabilistic or strict eligibility for alpha hunting across assets
- Dual modes adapt screening from flexible averages to rigorous confluences
- Custom periods and smoothings tune to timeframes, from scalps to positions
- Dual tables balance detail with digestible summaries for rapid insights
- Beta adds relativity, elevating resilient picks in correlated markets
- Efficient array handling scales screening without lag, quota-aware
PROFABIGHI_CAPITAL Ratio🌟 Overview
The PROFABIGHI_CAPITAL Ratio Tracker is a comprehensive multi-asset performance dashboard designed for cryptocurrency portfolio analysis , evaluating up to 33 altcoins against a customizable benchmark using six key quantitative metrics: alpha for excess returns, beta for relative volatility, Sharpe ratio for overall risk-adjusted performance, Sortino ratio for downside risk focus, omega ratio for probability-weighted gain-loss assessment, and rate of change (ROC) for momentum tracking. It aggregates these metrics into unified composite scores for each asset, enabling traders to rank and compare opportunities through intuitive table-based visualizations , median benchmarking , and top-performer highlights , all while supporting selective metric activation, adjustable parameters, and real-time alerts for systematic decision-making in volatile markets.
⚙️ Metrics Selection
- Toggle for enabling alpha calculations to quantify an asset's unique performance beyond benchmark movements , ideal for identifying true outperformance in diversified portfolios
- Toggle for activating beta measurements to evaluate how closely an asset mirrors benchmark volatility , helping assess diversification benefits or leverage exposure
- Toggle for incorporating Sharpe ratio to measure returns per unit of total risk , providing a standardized benchmark for comparing asset efficiency across varying volatility profiles
- Toggle for including Sortino ratio to emphasize returns adjusted for harmful downside moves only, particularly useful in asymmetric markets like crypto where upside swings are desirable
- Toggle for utilizing omega ratio to analyze the full return distribution by weighting probable gains against losses relative to a target threshold , capturing tail risks and skewness effects
- Toggle for adding rate of change to capture short-term momentum trends , complementing longer-term risk metrics with directional conviction signals
- Modular activation allows traders to tailor the analysis to specific philosophies, such as risk-averse setups focusing on Sortino and omega or momentum-driven approaches emphasizing ROC alongside Sharpe
- Computational efficiency through conditional enabling, ensuring only selected metrics consume resources while maintaining flexibility for evolving market conditions or strategy refinements
🎯 Alpha and Beta Parameters
- Adjustable lookback period for alpha and beta computations, balancing statistical robustness with responsiveness —longer horizons smooth noise for stable estimates, shorter ones highlight recent regime shifts
- Customizable benchmark symbol selection, such as broad market cap indices or sector-specific aggregates , to define the reference for relative performance evaluation and ensure meaningful comparisons
- Alpha derivation as the intercept in a regression of asset returns against benchmark returns , revealing skill-based outperformance after accounting for systematic market exposure
- Beta estimation via covariance divided by benchmark variance , quantifying sensitivity to market moves —values above 1 signal amplified volatility for growth-oriented allocations , below 1 indicate defensive traits
- Shared lookback application across both metrics for consistency, with higher values promoting trend-following reliability and lower values enabling tactical adjustments to intraday or weekly dynamics
- Conditional benchmark data fetching only when alpha or beta is active, optimizing script performance by avoiding unnecessary external data requests in lightweight configurations
- Tooltip-guided parameter explanations emphasizing trade-offs between smoothness and reactivity, aiding users in aligning settings with their timeframe and risk tolerance
- Integration with daily return series for precise regression inputs, ensuring calculations reflect realistic percentage-based movements rather than absolute price changes
⚡ Sharpe Ratio Parameters
- Rolling period for mean return and volatility estimation , where shorter windows capture recent performance spikes for agile monitoring, and longer ones provide trend-stable assessments
- Exponential moving average smoothing length to filter daily fluctuations in raw ratios, reducing visual noise while preserving signals of genuine risk-return shifts
- Daily return computation via price changes divided by prior close , standardizing inputs for cross-asset comparability regardless of nominal price levels
- Mean return via simple moving average over the period, representing average daily excess as the reward component in the risk-adjusted formula
- Standard deviation of returns as the risk denominator , capturing total volatility including both upside and downside deviations for holistic efficiency gauging
- Raw ratio as mean divided by standard deviation , with zero-volatility safeguards to prevent errors during flat periods , defaulting to neutral performance
- Annualization through multiplication by the square root of 365 , converting daily metrics to yearly equivalents for intuitive benchmarking against industry standards
- Smoothed and annualized output for each asset, enabling direct ranking of risk efficiency —higher values highlight superior return generation per volatility unit
🎯 Sortino Ratio Parameters
- Extended lookback for downside deviation accumulation , favoring longer periods for reliable negative return sampling in sporadic drawdown environments
- Annual risk-free rate input as the downside threshold , adjustable to reflect opportunity costs like bond yields or inflation , with zero default treating all losses as harmful
- Smoothing period via EMA to stabilize the ratio against window shifts , mirroring Sharpe approach but tailored to the selective nature of downside focus
- Periodic returns calculated as close-to-prior ratios minus one, ensuring percentage consistency for multi-asset analysis
- Effective period adaptation to available bars, allowing early calculations with shorter windows that expand over time for progressive accuracy
- Downside squared deviations summed only for underperformance instances , divided by period count , then square-rooted for standard deviation equivalent
- Raw ratio as excess mean return over downside deviation , scaled annually via square root scaling , emphasizing protection against capital erosion
- Smoothed final values per asset, rewarding strategies that minimize harmful volatility while ignoring beneficial upside dispersion common in crypto rallies
🔄 Omega Ratio Parameters
- Calculation period for return distribution sampling , longer horizons capturing fuller gain-loss spectra for robust probability weighting
- Target return threshold per period, defining success boundaries —zero treats positives as gains , positives add hurdles for conservative analysis
- EMA smoothing to dampen ratio swings from individual extreme returns entering or exiting the window, maintaining trend clarity
- Periodic returns derived similarly to other ratios, with decimal conversion of target for precise excess/shortfall computations
- Cumulative above-target excesses summed for gains , below-target shortfalls for losses , via explicit loop over historical series
- Raw ratio as gains divided by losses , with zero-loss default to neutral rather than infinity, avoiding misleading perfect-period artifacts
- Smoothed output revealing distributional health —ratios above 1 favor gains , higher values signal skewed positives ideal for tail-risk hedging
- Asset-specific computations highlighting asymmetry , where fat positive tails in crypto assets can elevate omegas despite high total volatility
📈 Rate of Change Parameters
- Period length for percentage momentum measurement , shorter for reactive trend detection , longer for sustained direction confirmation
- Built-in ROC function application to source prices , yielding unbounded percentage shifts —positive for uptrends , negative for downtrends
- Zero default for missing data , treating data gaps as neutral momentum to avoid biasing composite scores
- Complementary role to risk metrics , capturing raw directional strength without normalization, spotlighting acceleration phases
- Direct integration into averages, where high ROC boosts scores in momentum-favoring selections , balanced by volatility adjustments elsewhere
- Simplicity in computation enabling lightweight inclusion , with na handling ensuring seamless array pushes in scoring logic
💼 Assets Configuration
- Number of altcoins to monitor and display, scalable from focused portfolios to broad market scans for comprehensive opportunity hunting
- Top combined assets count for dedicated ranking table , adjustable to highlight elite performers without overwhelming the view
- Individual symbol inputs grouped left and right for organizational clarity , accepting crypto pairs , indices , or custom tickers
- Conditional activation based on total count , loading only selected assets to optimize data requests and calculations
- Default focus on major and mid-cap altcoins , but fully customizable for sector-specific or emerging token universes
- Prefix stripping in displays for clean ticker presentation , enhancing readability in table formats
- Array-based storage of names and scores post-calculation, facilitating sorting , medians , and iterative population
- Integration with security requests for daily closes , ensuring uniform timeframe data across diverse exchanges
🎨 Table Style
- Background color with transparency for semi-opaque overlays , blending professional aesthetics with chart visibility
- Border color for frame delineation , providing subtle separation without distracting from metric focus
- Consistent application across main , median , and top tables , maintaining visual coherence in multi-panel layouts
- Frame width and color for structural emphasis , using dark tones to evoke institutional-grade presentation
- Color functions for score backgrounds — green for above-median outperformance , red for underperformance , gray for invalids
- Emoji integration for intuitive cues — rockets for strong assets , down arrows for laggards , enhancing at-a-glance scanning
📡 Data Fetching and Returns Calculation
- Benchmark close retrieval conditional on alpha or beta needs, using daily timeframe for consistent periodicity
- Parallel asset close fetches via security calls , defaulting to na for inactive symbols to prevent errors
- Returns function standardizing one-period ROC for daily percentage changes , zero-filling na for continuity
- Benchmark returns computed similarly, serving as regression baseline for relative metrics
- Na propagation to individual asset returns , ensuring downstream calculations skip invalid data gracefully
- Daily resolution enforcement across all fetches, aligning with annualization assumptions in ratios
- Efficient conditional logic minimizing API calls , scalable to full 33-asset loads without performance degradation
📈 Alpha Calculation
- Function guarding against na inputs , returning na for insufficient data to flag unreliable estimates
- Mean asset and benchmark returns via SMA over lookback , establishing central tendencies
- Covariance as product mean minus means product , capturing joint variability
- Benchmark variance similarly, ensuring positive denominator for beta
- Beta as cov/var ratio , zero-default for flat benchmarks to avoid divisions
- Alpha as asset mean minus beta times benchmark mean , isolating idiosyncratic performance
- Zero fallback for na alphas , treating computation failures as neutral in composites
- Per-asset execution only when enabled, feeding into scoring arrays for holistic aggregation
📉 Beta Calculation
- Identical input guards and mean computations as alpha , leveraging shared regression framework
- Covariance and variance derivations mirroring alpha prep , focusing solely on slope coefficient
- Beta output as sensitivity measure , with zero handling for degenerate cases
- Na-to-zero conversion for seamless array integration , avoiding score distortions
- Toggle-based activation per asset, allowing isolated volatility analysis without excess return overhead
- Conceptual role in diversification —low betas signal hedges , high ones amplify market bets
- Lookback sensitivity trade-off : short for tactical betas , long for structural exposures
⚡ Sharpe Ratio Calculation
- Source na guard returning na , preserving data integrity
- Daily returns via change over prior source , avoiding log approximations for arithmetic consistency
- Period SMA for mean reward , stdev for total risk dispersion
- Raw daily ratio with zero-stdev neutral default , preventing infinities
- Nz-EMA smoothing to dampen variability , weighting recent ratios heavily
- Sqrt(365) annualization for yearly comparability , assuming i.i.d. returns
- Zero na fallback , distinguishing errors from flat performance
- Asset-parallel computations , ranking efficiency where high Sharpes indicate optimal risk pricing
🎯 Sortino Ratio Calculation
- Na source guard , with annualization factor predefined for scaling
- Periodic returns and per-period risk-free derivation for threshold alignment
- Effective period min with bar count , enabling progressive buildup
- Loop-summed downside squares only for positive deviations ( underperformance ), averaged and sqrt-ed
- Excess mean over downside dev , scaled annually , zero-dev neutral
- Nz-EMA smoothing for stability , focusing on loss aversion
- Zero na output , emphasizing downside protection in crypto's crash-prone nature
- Longer periods favored for sparse downside events , enhancing estimate reliability
🔄 Omega Ratio Calculation
- Na guard with periodic returns and decimal target setup
- Loop over period accumulating above-target excesses vs. below shortfalls
- Raw ratio as gains/losses , zero-loss neutral to conservatism
- Nz-EMA smoothing , defaulting raw na to zero for continuity
- Distributional insight : >1 favors assets with skewed positives , <1 warns of loss dominance
- Target flexibility —zero for absolute , positive for relative hurdles
- Per-asset loops ensuring full history scan , capturing crypto's lottery-like tails
📈 Rate of Change Calculation
- Simple ta.roc application over period , percentage momentum direct from prices
- Na-to-zero for gaps , neutral in momentum absence
- Unbounded output allowing extreme trend magnitudes , unlike bounded oscillators
- Toggle integration boosting composites in trending selections
- Short-period reactivity for entry timing , complementing ratio stability
🎯 Combined Score Calculation
- Selected metrics count via incremental ifs , normalizing averages
- Last-bar loop over assets , building per-asset score arrays
- Switch-retrieved metric values , na-filtered pushes with valid count tracking
- Average only over valid scores , handling partial data gracefully
- Var assignment to per-asset combined vars , persisting for table use
- Equal-weighting assumption , treating metrics as complementary signals
- Na results when no valids , flagging data-deficient assets
- Holistic aggregation simplifying multi-metric overload into rankable scores
📊 Table Display Functions
- Background color getter : green above median , red below, gray invalid
- Emoji selector : rocket for outperformers , down for underperformers , blank invalid
- Row/column math for three-column layout , maximizing space efficiency
- Prefix-stripped asset names for compact display
- Rounded three-decimal scores or N/A , centered alignment
- Header branding centered, dark background for prominence
- Median table compact right-side , gray neutral for reference
- Top table left-side descending sort via indices array , limited rows
📋 Table Preparation
- Var arrays for names and scores , last-bar conditional pushes
- Conditional per-asset adds based on num_assets , avoiding over-allocation
- Median via array.median , central tendency for relative gauging
- Sort indices descending for top ranking , min with size for bounds
- String concatenation for alerts , newline-separated asset-score pairs
- Once-per-bar alert freq , compiling only non-na for actionable output
- Barstate.islast gating all prep/display , preventing historical repaints
✅ Key Takeaways
- Modular metrics enable tailored risk-return portfolios , from alpha hunts to downside shields
- Composite scores distill complexity into actionable rankings , median-anchored for relativity
- Benchmark-relative analysis uncovers crypto alphas amid market noise
- Table triad — main matrix , median ref , top highlights —delivers scannable insights
- Alerts and custom assets support automated monitoring in dynamic altcoin spaces
- Smoothing and lookbacks balance reactivity with stability for versatile timeframes
- Equal-metric averaging assumes balance , customizable via toggles for bias
ROC Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The ROC Tracker → PROFABIGHI_CAPITAL indicator measures momentum strength by calculating the Rate of Change (ROC) for up to 33 customizable altcoins over a user-specified period, revealing acceleration or deceleration in price movements. It dynamically generates color-gradient tables displaying individual ROC values, median benchmarks, and ranked top momentum performers with emoji indicators, allowing traders to spot surging assets for timely entries or fading ones for exits in volatile markets.
⚙️ General Settings
– ROC Period : Defines the lookback bars for percentage change computation, where shorter periods (e.g., 5-10) highlight immediate momentum bursts while longer spans (e.g., 20-50) capture sustained trends—key for aligning with trading horizons like scalping or swing setups.
💎 Asset Selection Settings
– Number of Altcoins to Display : Scales the primary table from a streamlined 5-asset view for rapid momentum checks to a full 33-symbol scan for broad-market acceleration profiling—balances detail with computational efficiency.
– Number of Top ROC Assets : Configures the momentum leaderboard to emphasize leading changers, adjustable from 1 for focused highlights to the total count for unbridled ranking—accelerates identification of breakout candidates.
– Asset 1-17 (Left Group) : Curates the main table's left column with essential altcoins, enabling personalization from anchors like ETHUSD to varied inclusions such as XRPUSD—each retrieves daily closes for standalone ROC derivation, with tooltips confirming symbol standards.
– Asset 18-33 (Right Group) : Populates the right column for diversified momentum tracking, incorporating further tokens from LTCUSD to specialized selections like MNTUSD—fosters balanced tri-column flow for lateral dataset review.
– Dynamic Input Rendering : Activates fields proportional to asset tally, veiling extras to sidestep errors and simplify navigation—facilitates effortless escalation from narrow lists to panoramic surveillance.
🎨 Table Style Settings
– Low ROC Color : Sets the gradient's deceleration base (e.g., deep red for negative changes), promptly signaling momentum fades that may prompt profit-taking or avoidance.
– High ROC Color : Anchors the acceleration peak (e.g., vivid green for positive changes), illuminating surging movers ripe for momentum continuation plays.
– Neutral ROC Value : Centers the color pivot at zero change (typically 0.0), modulating from loss to gain hues—adjustment biases toward conservative or aggressive momentum reads.
– ROC Color Range : Governs the transitional breadth around neutral, embracing wide fades for nuanced momentum gradients or narrow contrasts for binary surge/lag demarcation.
– Table Background : Deploys a muted dark semi-transparent canvas for thematic unity and cross-theme visibility, crafting an elegant momentum dashboard.
– Table Border : Enframes with neutral gray for subtle containment, encapsulating data without stylistic diversion.
📡 Data Fetching
– Asset Data Retrieval : Conducts concurrent daily close queries for nominated symbols, interposing NA for gaps to fortify table resilience.
– Return Series Computation : Applies 1-period percentage variances to asset paths, yielding the momentum quanta for period-based change metrics.
– Missing Data Resilience : Implants sentinels (-9999) for voids, rendering as grays to indicate incompleteness without structural breach.
🧮 Calculations
– Periodic Return Generation : Computes rate of change over the specified bars as current divided by prior minus unity, distilling momentum as percentage acceleration.
– Raw ROC Derivation : Directly yields the percentage shift over the lookback, quantifying speed without further averaging for pure velocity insight.
– NA Propagation Handling : Forwards missing values to preserve computational chain integrity, displaying as neutrals in outputs.
📋 Table Display
– Dynamic Layout Optimization : Erects columns (up to 9 for tri-set harmony) and rows attuned to asset volume plus header, assuring pithy utility for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded momenta (3 decimals), and velocity emojis in parsimonious trios for row-thrifty perusal.
– ROC Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate momentum profiling.
– Emoji Velocity Markers : Dispatches rocket for above-median changes (accelerators) and downward arrow for below (decelerators), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal momentum with gradient tint, mooring relative appraisals as a parity linchpin.
– Top ROC Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for surge-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded momenta on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– ROC quantification unveils momentum velocity, spotlighting acceleration for timely pursuits.
– Rolling period with direct computation yields crisp, unaltered speed metrics.
– Profuse symbol pliancy forges bespoke crypto velocity observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten surge/lag discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Omega Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Omega Ratio Tracker → PROFABIGHI_CAPITAL indicator quantifies the probability-weighted gain-to-loss efficiency by computing the Omega ratio for up to 33 customizable altcoins over a rolling lookback period, contrasting cumulative returns above a user-defined target against those below to assess favorable outcomes. It dynamically constructs color-gradient tables featuring individual Omegas, median benchmarks, and ranked top performers with emoji indicators, allowing traders to evaluate assets' upside potential relative to downside risks for informed, asymmetric opportunity selection.
⚙️ General Settings
– Calculation Period (Bars) : Establishes the historical scope for return accumulation and threshold comparisons, where shorter windows spotlight immediate efficiencies amid market swings while extended periods gauge long-term gain/loss asymmetries—pivotal for matching trading cadences like intraday (e.g., 20-50 bars) or swing (e.g., 100+ bars).
– Target Return per Period (%) : Specifies the aspirational return threshold per bar/day, serving as the pivot separating "gains" from "losses" in the ratio—elevated targets demand superior performance for positive Omegas, ideal for high-conviction filters, while modest ones broaden inclusion for diverse scans.
– Smoothing Period (EMA) : Implements exponential moving average on raw ratios to mitigate transients, with low values (e.g., 1-2) retaining volatility for granular views and higher settings (e.g., 4-7) fostering trend persistence for strategic planning.
💎 Asset Selection Settings
– Number of Altcoins to Display : Dictates the primary table's expanse from a targeted 5-asset spotlight for swift evaluations to a maximal 33-symbol expanse for holistic risk-reward profiling—impacts processing demands and dashboard density.
– Number of Top Omega Assets : Tailors the elite leaderboard to showcase premier ratios, variable from 1 for ultra-focused highlights to the aggregate count for unfiltered excellence—expedites prioritization of high-gain/low-loss candidates.
– Asset 1-17 (Left Group) : Loads the main table's left column with bedrock altcoins, facilitating bespoke curation from stalwarts like ETHUSD to varied mid-tiers such as XRPUSD—each solicits daily closes for autonomous Omega computation, with tooltips validating symbol protocols.
– Asset 18-33 (Right Group) : Charges the right column for augmented diversification, embracing further tokens from LTCUSD to esoteric picks like MNTUSD—cultivates equilibrated tri-column ergonomics for lateral dataset traversal.
– Dynamic Input Activation : Manifests fields per asset tally, obfuscating redundants to forestall faults and declutter—empowers fluid augmentation from succinct rosters to panoramic oversight sans reconfiguration.
🎨 Table Style Settings
– Low Omega Color : Grounds the gradient's unfavorable terminus (e.g., stark red for ratios below 1.0), instantaneously tagging assets with skewed losses over gains that might erode portfolio viability.
– High Omega Color : Secures the advantageous apex (e.g., radiant green for ratios above 1.0), illuminating prospects with dominant upsides relative to downsides for asymmetric edge hunting.
– Neutral Omega Value : Locates the color fulcrum at equilibrium efficiency (typically 1.0 for balanced outcomes), where ratios modulate from penalty to premium—refinement inclines toward prudent or venturesome outlooks.
– Omega Color Range : Regulates the transitional amplitude encircling neutral, favoring expansive fades for refined gradations or constricted shifts for unequivocal high/low bifurcation.
– Table Background : Imposes a discreet dark semi-opaque substrate for thematic cohesion and theme-agnostic legibility, evoking a refined analytics interface.
– Table Border : Encases perimeters with subdued gray for tacit delineation, encapsulating intelligence without stylistic encumbrance.
📡 Data Fetching
– Asset Data Retrieval : Undertakes simultaneous daily close interrogations for nominated symbols, interposing NA for lacunae to buttress table solidity.
– Return Series Computation : Extracts 1-period percentage variances from asset trajectories, proffering the elemental grist for gain/loss partitioning.
– Void Data Fortification : Implants sentinels (-9999) for lacunae, materializing as grays in renderings to signify incompleteness sans architectural compromise.
🧮 Calculations
– Periodic Return Generation : Forges bar/daily percentage alterations as source divided by antecedent minus unity, underpinning the discrete quanta for target-relative dissection.
– Target Threshold Decimalization : Transmutes percentage input to fractional form, delineating the demarcation betwixt accretive and detractive outcomes.
– Cumulative Gain Accrual : Aggregates excesses above target over the period, encapsulating favorable deviations' aggregate potency.
– Cumulative Loss Accrual : Tallies shortfalls below target, quantifying adverse deviations' collective burden.
– Raw Omega Formulation : Divides gains by losses, yielding the probability-adjusted efficiency quotient—defaults to NA on nil losses for interpretive clarity.
– EMA Transient Suppression : Exponentially averages raw quotients to quell ephemera, engendering interpretable contours over jagged dailies.
– Annualization Omission : Presents periodic ratios without scaling, prioritizing raw bar-level insights for intraday or short-term applicability.
📋 Table Display
– Dynamic Layout Optimization : Assembles columns (apex 9 for tri-set orchestration) and rows calibrated to asset quantum plus header, vouchsafing succinct potency for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded quotients (3 decimals), and efficiency emojis in parsimonious trios for row-thrifty perusal.
– Omega Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate gain/loss equilibrium profiling.
– Emoji Efficiency Markers : Dispatches rocket for above-median quotients (asymmetric victors) and downward arrow for below (lopsided laggards), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal quotient with gradient tint, mooring relative appraisals as a parity linchpin.
– Top Omega Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for gain-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded quotients on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– Gain/loss partitioning via target thresholds unveils asymmetric efficiency beyond traditional metrics.
– Rolling computations with smoothing furnish trend-stable, noise-attenuated efficiency vistas.
– Profuse symbol pliancy forges bespoke crypto observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten low-loss/high-gain discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Sortino Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sortino Ratio Tracker → PROFABIGHI_CAPITAL indicator assesses downside risk-adjusted performance by computing the Sortino ratio for up to 33 customizable altcoins over a rolling lookback period, focusing solely on negative volatility to penalize harmful deviations while smoothing and annualizing for actionable insights. It dynamically generates color-gradient tables displaying individual Sortinos, median benchmarks, and ranked top performers with emoji indicators, empowering traders to prioritize assets with superior returns relative to their drawdown risks for more resilient portfolio construction.
⚙️ General Settings
– Calculation Period (Days/Bars) : Specifies the historical window for return averaging and downside deviation estimation, where shorter periods emphasize recent efficiency amid volatility spikes while longer horizons evaluate enduring downside protection—vital for aligning with strategies like short-term trading (e.g., 30-60 bars) versus long-term holding (e.g., 90+ bars).
– Annual Risk-Free Rate (%) : Sets the threshold below which returns are considered "downside," typically a conservative benchmark like treasury yields—higher rates raise the bar for positive Sortinos, favoring only truly superior risk-adjusted outcomes.
– Smoothing Period (EMA) : Applies exponential moving average to raw ratios for noise reduction, where minimal smoothing (e.g., 1-3) preserves granularity for active monitoring while higher values (e.g., 5+) yield trend-stable views for strategic overviews.
– Number of Altcoins to Display : Determines the primary table's breadth from a streamlined 5-asset focus for rapid scans to a thorough 33-symbol panorama for exhaustive downside risk profiling—directly affects data processing and visual footprint.
– Number of Top Sortino Assets : Configures the leaderboard to spotlight leading ratios, scalable from 1 for laser-focused highlights to the full asset set for complete efficiency hierarchy—facilitates prioritization of low-downside winners.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Fills the main table's left column with cornerstone altcoins, enabling tailored selection from majors like ETHUSD to diversified options such as XRPUSD—each pulls daily closes for standalone Sortino computation, with tooltips verifying symbol conventions.
– Asset 18-33 (Right Group) : Loads the right column for extended diversification, incorporating further tokens from LTCUSD to specialized choices like MNTUSD—promotes balanced tri-column ergonomics for fluid cross-dataset comparison.
– Dynamic Input Activation : Renders fields conditionally on total assets, hiding extras to avert errors and declutter the interface—supports frictionless growth from compact portfolios to all-encompassing surveillance.
🎨 Table Style Settings
– Low Sortino Color : Establishes the gradient's downside anchor (e.g., intense red for negative ratios), immediately flagging assets with excessive harmful volatility that could undermine portfolio stability.
– High Sortino Color : Pins the excellence terminus (e.g., luminous green for positive ratios), illuminating low-risk/high-return standouts perfect for conservative growth strategies.
– Neutral Sortino Value : Positions the color inflection at breakeven efficiency (typically 0.0), pivoting hues from penalty to premium—tweaking recalibrates toward defensive or opportunistic lenses.
– Sortino Color Range : Modulates the spectrum's transitional span around neutral, opting for broad fades in subtle differentiation or tight contrasts for stark performer/laggard splits.
– Table Background : Instills a understated dark semi-transparent foundation for unified readability across themes, evoking a sleek, professional analytics dashboard.
– Table Border : Circumscribes frames with unobtrusive gray for gentle containment, directing focus to the gradient-infused data without stylistic interference.
📡 Data Fetching
– Asset Data Retrieval : Performs concurrent daily close queries for specified symbols, substituting NA for voids to sustain table robustness.
– Return Series Computation : Extracts 1-period percentage changes from asset series, supplying the granular inputs for mean and downside deviation metrics.
– Missing Data Resilience : Employs sentinels (-9999) for gaps, manifesting as grays in tables to denote incompleteness without layout disruption.
🧮 Calculations
– Periodic Return Generation : Derives daily/bar percentage changes as source over prior close minus one, capturing discrete movements for efficiency evaluation.
– Mean Return Estimation : Averages returns over the rolling period with simple moving average, forging a baseline excess performance metric.
– Downside Deviation Quantification : Sums squared deviations below the risk-free threshold, averaging to measure only harmful volatility—ignores upside for focused risk penalization.
– Raw Sortino Formulation : Divides mean excess return by downside deviation, defaulting to zero on nil volatility for computational safety.
– EMA Noise Attenuation : Exponentially smooths raw ratios to filter transients, yielding interpretable trends over erratic daily swings.
– Annualization Adjustment : Scales smoothed ratios by the square root of 365 (crypto calendar), transforming periodic efficiency into yearly benchmarks for cross-asset comparability.
📋 Table Display
– Dynamic Layout Scaling : Erects columns (maximum 9 for tri-set grouping) and rows attuned to asset quantity plus header, guaranteeing compact utility for 1-33 symbols.
– Main Table Architecture : Branded header traverses the summit row, pursued by asset symbols, rounded ratios (3 decimals), and efficiency emojis in efficient trios for streamlined row navigation.
– Sortino Color Continuum : Maps values from low (red) via neutral (midpoint) to high (green), with grays for voids—enables instantaneous downside efficiency profiling.
– Emoji Efficiency Markers : Deploys rocket for above-median ratios (superior performers) and downward arrow for below (inferior), infusing swift visual assessment.
– Median Table Encapsulation : Succinct single-column portrayal of central ratio with gradient hue, anchoring relative evaluations as a risk-neutral pivot.
– Top Sortino Table Hierarchy : Descending classification in 3-column matrix (symbol, value, emoji) with header branding, concentrating on elite assets for downside-focused decisions.
– Index-Fueled Ranking : Exploits array indices for descending extraction, reconstructing sorted arrays while preserving originals for exact median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Constructs newline-separated assemblages of symbols and rounded ratios on the terminal bar, excising prefixes for terse formatting.
– Once-Per-Bar Dispatch : Initiates alerts at close with the complete dataset, accommodating external integrations like notifications or automated systems.
– Output Refinement : Curates parseable content by excluding NAs, zeroing in on executable data for streamlined workflow incorporation.
✅ Key Takeaways
– Downside-focused Sortino ratios spotlight assets excelling in returns per harmful volatility unit.
– Rolling computations with smoothing and annualization yield comparable, trend-stable efficiency metrics.
– Vast symbol adaptability crafts bespoke crypto dashboards from majors to alts.
– Gradient tables with medians and tops accelerate low-risk winner identification via visuals.
– Automated alerts consolidate scans into digestible packets, expediting from evaluation to execution.
Sharpe Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sharpe Ratio Tracker → PROFABIGHI_CAPITAL indicator evaluates risk-adjusted performance by computing the Sharpe ratio for up to 33 customizable altcoins over a rolling lookback period, smoothing values for stability and annualizing for comparability. It dynamically renders color-gradient tables showcasing individual Sharpe ratios, median benchmarks, and ranked top performers with emoji indicators, enabling traders to identify assets delivering superior returns per unit of volatility for optimized portfolio selection.
⚙️ General Settings
– Sharpe Rolling Period : Adjustable lookback window for return and volatility averaging, where shorter horizons capture recent efficiency while longer spans assess sustained performance stability.
– Smoothing Period : EMA length applied to raw ratios to dampen noise, promoting smoother trends for clearer visual and analytical insights.
– Number of Altcoins to Display : Scales the primary table's capacity from a focused 5-asset scan for quick reviews to a full 33-symbol matrix for comprehensive risk-adjusted screening.
– Number of Top Sharpe Assets : Curates the leaderboard to emphasize leading ratios, tunable from 1 for pinpoint focus to the total count for exhaustive ranking of efficiency standouts.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Populates the main table's left column with foundational altcoins, supporting customization from blue-chips like ETHUSD to diversified selections such as XRPUSD—each input retrieves daily closes for isolated Sharpe derivation, with tooltips ensuring accurate symbol formatting.
– Asset 18-33 (Right Group) : Fills the right column for broader exposure, accommodating additional tokens from LTCUSD to niche assets like MNTUSD—facilitates ergonomic tri-column layout for horizontal scanning across the expanded dataset.
– Dynamic Input Rendering : Conditionally activates fields based on total assets, concealing unused slots to eliminate errors and streamline the interface—allows effortless scaling from compact watchlists to exhaustive monitoring without reconfiguration.
🎨 Table Style Settings
– Low Sharpe Color : Anchors the gradient's underperformance base (e.g., deep red for negative ratios), visually flagging assets with poor efficiency that may drag portfolio returns.
– High Sharpe Color : Establishes the excellence endpoint (e.g., vivid green for positive ratios), spotlighting high-efficiency performers ideal for risk-conscious allocations.
– Neutral Sharpe Value : Centers the color pivot at breakeven efficiency (typically 0.0), where ratios shift from subdued to vibrant hues—calibration tilts toward conservative or aggressive interpretations.
– Sharpe Color Range : Broadens or narrows the transition zone around neutral, yielding gradual blends for nuanced rankings or sharp delineations for clear high/low separation.
– Table Background : Deploys a subtle dark semi-transparent canvas for all views, fostering glare-free readability across themes while delivering a cohesive dashboard appearance.
– Table Border : Frames outlines with neutral gray for understated structure, containing content without diverting from the gradient-centric data narrative.
📡 Data Fetching
– Asset Data Retrieval : Executes parallel daily close requests for designated symbols, gracefully managing empty inputs by inserting NA placeholders to uphold table cohesion.
– Return Series Computation : Derives 1-period percentage changes for each asset, furnishing the discrete inputs for mean and standard deviation estimations.
– Invalid Data Mitigation : Substitutes missing values with sentinels (-9999) for rendering as grays, preserving layout amid incomplete datasets.
🧮 Calculations
– Daily Return Generation : Applies rate of change over one day to each asset's series, yielding percentage shifts as the core for efficiency metrics.
– Mean Return Smoothing : Averages returns over the rolling period via simple moving average, establishing historical performance baselines.
– Standard Deviation Volatility : Computes rolling dispersion of returns, quantifying risk as the denominator for ratio normalization.
– Raw Sharpe Derivation : Divides mean return by standard deviation, handling zero-volatility cases with zero fallback for stability.
– EMA Smoothing Application : Applies exponential moving average to raw ratios, attenuating fluctuations for trend-revealing outputs.
– Annualization Scaling : Multiplies smoothed ratios by the square root of 365, converting daily efficiency to yearly comparability.
📋 Table Display
– Dynamic Layout Optimization : Constructs columns (up to 9 for tri-set configuration) and rows scaled to asset count plus header, ensuring compact efficiency for 1-33 symbols.
– Main Table Framework : Branded header bridges the top row, trailed by asset symbols, rounded ratios (3 decimals), and efficiency emojis in streamlined trios for row-efficient navigation.
– Sharpe Color Continuum : Interpolates from low (red) through neutral (midpoint) to high (green), with grays for invalids—facilitates at-a-glance risk-adjusted profiling.
– Emoji Efficiency Markers : Renders rocket for above-median ratios (strong performers) and downward arrow for below (weak), injecting rapid visual sentiment.
– Median Table Encapsulation : Compact single-column showcase of central ratio with gradient coloring, anchoring relative evaluations as an efficiency fulcrum.
– Top Sharpe Table Hierarchy : Descending rank in 3-column array (symbol, value, emoji) with header branding, zeroing in on superior assets for allocation prioritization.
– Index-Fueled Ranking : Harnesses array indices for descending extraction, rebuilding sorted arrays while safeguarding originals for precise median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Assembles newline-separated compilations of symbols and rounded ratios on the final bar, purging prefixes for succinct formatting.
– Once-Per-Bar Dispatch : Activates alerts at close with the full dataset, accommodating external integrations like notifications or bots.
– Output Refinement : Curates parseable content by excluding NAs, concentrating on executable data for seamless workflow embedding.
✅ Key Takeaways
– Transforms risk-adjusted efficiency into gradient-scored tables for effortless asset ranking.
– Rolling Sharpe with smoothing and annualization delivers comparable, noise-reduced insights.
– Extensive symbol flexibility supports tailored crypto portfolios from majors to alts.
– Top medians and emojis accelerate outperformance detection with visual punch.
– Automated alerts package complete scans, streamlining from analysis to action.
Beta Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Beta Tracker → PROFABIGHI_CAPITAL indicator quantifies market sensitivity by calculating the beta coefficient for up to 33 customizable altcoins relative to a selected benchmark over a user-defined lookback, revealing how assets amplify or dampen systemic movements. It dynamically renders color-gradient tables with individual betas, median values, and sorted top sensitivities alongside emoji indicators, enabling traders to assess volatility alignment and construct diversified portfolios based on risk exposure profiles.
⚙️ General Settings
– Beta Measurement Length : Establishes the historical horizon for return covariance and variance computations, where shorter spans highlight recent sensitivities while longer periods reveal enduring market correlations—essential for tailoring to trading styles like short-term scalping or long-term holding.
– Benchmark Symbol : Designates the reference index for beta normalization, such as total market cap to evaluate broad exposure or Bitcoin for coin-specific amplification—forms the foundational volatility baseline for all asset comparisons.
– Number of Altcoins to Display : Scales the primary table's capacity from a concise 5-asset focus for quick scans to a robust 33-symbol overview for exhaustive screening, directly influencing data volume and computational efficiency.
– Number of Top Beta Assets : Curates the leaderboard to showcase the most sensitive performers, adjustable from 1 for pinpoint focus to the full asset count for comprehensive ranking—streamlines identification of high-volatility opportunities.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Populates the main table's left column with core altcoins, supporting sequential customization from established leaders like ETHUSD to diversified mid-caps such as XRPUSD—each fetches daily closes for independent beta derivation, with tooltips ensuring proper symbol entry.
– Asset 18-33 (Right Group) : Fills the right column for expanded coverage, accommodating additional tokens from LTCUSD to niche selections like MNTUSD—facilitates balanced tri-column layout for ergonomic horizontal scanning across the dataset.
– Dynamic Input Adaptation : Conditionally renders inputs based on total assets, suppressing unused fields to prevent errors and streamline the interface—allows seamless scaling from minimal watchlists to full-spectrum monitoring without reconfiguration.
🎨 Table Style Settings
– Low Beta Color : Anchors the gradient's defensive endpoint (e.g., muted red for betas below 1.0), visually denoting lower market sensitivity and potential stability in portfolios.
– High Beta Color : Defines the aggressive anchor (e.g., vibrant green for betas above 1.0), spotlighting amplified movers ideal for volatility-seeking strategies.
– Neutral Beta Value : Centers the color transition at market-equivalent sensitivity (typically 1.0), where betas pivot from subdued to heightened hues—calibration shifts emphasis toward conservative or offensive interpretations.
– Beta Color Range : Expands or contracts the spectrum bandwidth around neutral, fostering gradual blends for nuanced rankings or abrupt shifts for clear high/low demarcation.
– Table Background : Applies a subtle dark semi-transparent canvas across all views, promoting eye comfort on varied themes while unifying the professional dashboard aesthetic.
– Table Border : Outlines frames with neutral gray for subtle definition, framing content without distracting from the gradient-driven data insights.
📡 Data Fetching
– Benchmark Data Retrieval : Utilizes security requests for daily closing prices from the designated symbol, compiling a consistent series for variance and covariance baselines.
– Asset Data Retrieval : Conducts parallel daily close pulls for chosen symbols, substituting NA for invalid inputs to safeguard computational flow.
– Rate of Change Derivation : Generates 1-period percentage returns for assets and benchmark, providing the discrete inputs for mean estimation and co-movement analysis.
– Invalid Data Safeguarding : Flags missing values with sentinels (-9999) for table rendering as grays, maintaining structural integrity amid data gaps.
🧮 Calculations
– Return Series Generation : Applies rate of change over one day to each asset and benchmark, yielding daily percentage shifts as the raw material for sensitivity metrics.
– Mean Return Smoothing : Averages returns via simple moving over the lookback, establishing historical performance norms for both series.
– Covariance Quantification : Computes the averaged product of asset and benchmark returns minus their means' product, encapsulating directional co-variance.
– Benchmark Variance Measurement : Averages squared deviations of benchmark returns from its mean, capturing the reference's inherent volatility.
– Beta Coefficient Computation : Divides covariance by variance to derive systemic sensitivity, where values above 1.0 indicate amplification and below suggest dampening.
– NA Handling in Metrics : Defaults beta to NA for zero-variance benchmarks, preventing division errors while displaying as neutrals.
📋 Table Display
– Dynamic Layout Scaling : Constructs columns (up to 9 for tri-set grouping) and rows based on asset volume plus header, optimizing density for seamless 1-33 symbol integration.
– Main Table Structuring : Branded header spans the top row, succeeded by asset symbols, rounded betas (3 decimals), and sensitivity emojis in compact trios for efficient row-wise scanning.
– Beta Color Spectrum : Applies gradient mapping from low (red) via neutral (midpoint) to high (green), with grays for invalids—facilitates instantaneous volatility profile assessment.
– Emoji Sensitivity Cues : Deploys rocket for above-median betas (high sensitivity) and downward arrow for below (low sensitivity), infusing quick visual narrative.
– Median Table Compact View : Single-column encapsulation of central beta with gradient hue, anchoring relative evaluations as a market-neutral fulcrum.
– Top Beta Table Ranking : Descending sort in 3-column format (symbol, value, emoji) with header branding, concentrating on amplified assets for volatility-focused decisions.
– Index-Driven Sorting : Leverages array indices for efficient descending extraction, reconstructing views while retaining originals for accurate median computation.
🔔 Alerts
– Dynamic Alert Assembly : Constructs newline-formatted lists of symbols and rounded betas on the final bar, excising prefixes for concise messaging.
– Bar-Close Triggering : Fires alerts once per close with the entire dataset, supporting seamless external tooling or notifications.
– Formatted Output Optimization : Ensures clean, parseable content by omitting NAs, focusing on viable data for integration.
✅ Key Takeaways
– Illuminates asset-market sensitivity through beta coefficients, guiding volatility-aligned portfolio construction.
– Gradient tables with medians and tops transform raw metrics into actionable, scannable intelligence.
– Extensive symbol customization supports bespoke crypto monitoring from majors to alts.
– Emojis and colors add intuitive flair, accelerating relative strength identification.
– Automated alerts distill full scans into digestible updates, bridging analysis to execution.
Alpha Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Alpha Tracker → PROFABIGHI_CAPITAL is a sophisticated performance analytics tool that computes and visualizes the risk-adjusted excess returns (alpha) of up to 33 customizable altcoins against a user-defined benchmark over a flexible lookback horizon. By leveraging daily return covariance and beta adjustments, it dynamically generates color-gradient tables showcasing individual alphas, median benchmarks, and ranked top performers with intuitive emoji indicators, empowering traders to swiftly pinpoint relative outperformance and inform portfolio rotations or allocation decisions.
⚙️ General Settings
– Alpha Measurement Length : Defines the historical window for return averaging and covariance calculations, where shorter periods emphasize recent momentum while longer horizons capture sustained trends—crucial for aligning with trading horizons like short-term scalping (e.g., 10-20 days) versus long-term positioning (e.g., 50+ days).
– Benchmark Symbol : Serves as the market reference for alpha isolation, typically a broad index like total crypto cap to gauge systemic risk-adjusted gains; selecting alternatives like Bitcoin enables coin-specific outperformance analysis.
– Number of Altcoins to Display : Controls the scale of the main table, from a focused watchlist of 5-10 high-conviction assets to a comprehensive 33-symbol scan for broad-market screening—impacts computational load and visual density.
– Number of Top Alpha Assets : Limits the dedicated leaderboard to the highest alphas, streamlining focus on actionable leaders (e.g., 3-7 for quick scans) while maintaining full data in the primary view for deeper dives.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Curates the primary column of the main table with foundational altcoins, allowing sequential customization from blue-chip like ETHUSD to mid-caps like XRPUSD—each input fetches daily closes for independent alpha computation, with tooltips guiding symbol formatting.
– Asset 18-33 (Right Group) : Expands to secondary symbols in the right column, supporting diverse exposure from established tokens like LTCUSD to emerging ones like ONDOUSD—seamless integration ensures balanced left-right distribution for ergonomic table reading.
– Dynamic Input Scaling : Automatically accommodates the total asset count by disabling unused inputs, preventing errors and optimizing data fetches—enables modular expansion from a minimal 5-asset portfolio to full 33 for exhaustive coverage.
🎨 Table Style Settings
– Low Alpha Color : Establishes the gradient's underperformance endpoint (e.g., deep red for negative alphas), visually signaling laggards that may warrant reduction or avoidance in allocations.
– High Alpha Color : Sets the outperformer anchor (e.g., bright green for positive alphas), highlighting assets generating excess returns beyond benchmark expectations.
– Neutral Alpha Value : Anchors the color spectrum's midpoint, where zero or breakeven alphas transition from red to green—fine-tuning shifts the bias toward aggressive or conservative interpretations.
– Alpha Color Range : Widens or narrows the transition bandwidth around neutral, creating smoother blends for subtle rankings or sharper contrasts for binary hot/cold asset identification.
– Table Background : Applies a semi-opaque dark base across all tables, ensuring low-glare readability on both light and dark themes while maintaining professional aesthetics.
– Table Border : Defines frame outlines for structural definition, with gray subtlety preventing visual clutter while framing content effectively.
📡 Data Fetching
– Benchmark Data Retrieval : Employs security requests for daily closes from the chosen symbol, ensuring a stable time series for covariance baseline without intraday noise.
– Asset Data Retrieval : Parallel daily close fetches for selected symbols, gracefully handling invalid inputs by substituting NA values to preserve table stability.
– Rate of Change Computation : Derives 1-period percentage returns for assets and benchmark, forming the raw input for mean and covariance matrices.
– Error Handling for NA Values : Replaces missing data with sentinel placeholders (-9999) in tables, displaying as gray neutrals to flag data gaps without disrupting layout.
🧮 Calculations
– Return Series Generation : Applies rate of change over one day for each asset and benchmark, capturing discrete daily movements essential for alpha's excess return focus.
– Mean Return Averaging : Computes simple moving averages of returns over the lookback, providing smoothed historical performance baselines for both series.
– Covariance Estimation : Averages the product of asset and benchmark returns minus their means' product, quantifying linear co-dependence critical for beta adjustment.
– Benchmark Variance : Averages squared benchmark deviations from its mean, measuring systemic volatility to normalize asset sensitivity.
– Beta Coefficient : Divides covariance by variance to derive market beta, isolating systematic risk before alpha extraction.
– Alpha Derivation : Subtracts beta-adjusted benchmark mean from asset mean, yielding the intercept as true excess return attributable to security-specific factors.
📋 Table Display
– Dynamic Table Dimensions : Auto-scales columns (up to 9 for tri-column layout) and rows based on asset count plus header, optimizing space for 1-33 symbols without overflow.
– Main Table Population : Features a branded header spanning the top, followed by asset symbols, rounded alphas (3 decimals), and performance emojis in balanced trios for scannable rows.
– Alpha Color Gradient : Maps values from low (red) through neutral (midpoint) to high (green), with gray for invalids—enables instant visual ranking across the dataset.
– Emoji Performance Icons : Renders rocket for above-median alphas (outperformers) and downward arrow for below (laggards), adding emotional quick-scan appeal.
– Median Table Summary : Compact single-column view of the central alpha with gradient coloring, serving as a neutral benchmark for relative assessments.
– Top Assets Table : Ranks the highest alphas descending in a 3-column format (symbol, value, emoji), with header branding for focused opportunity highlighting.
– Array-Based Sorting : Generates descending indices from alpha array, reconstructing sorted lists for leaderboard extraction while preserving originals for display.
🔔 Alerts
– Dynamic Alert Construction : Compiles a newline-separated list of symbols and rounded alphas on the last bar, stripping prefixes for clean formatting.
– Once-Per-Bar Frequency : Triggers alerts at close with the complete dataset, facilitating external integrations like notifications or automation.
– Content Customization : Formats messages for readability, excluding NA values to focus on actionable data points.
✅ Key Takeaways
– Streamlines alpha computation across portfolios, transforming complex risk-adjusted metrics into intuitive, gradient-scored tables for rapid insights.
– Benchmark-relative ranking with medians and tops enables proactive asset rotation based on true outperformance.
– Customizable symbols and lookbacks adapt to diverse crypto watches, from majors to niche alts.
– Visual emojis and colors provide at-a-glance sentiment, complementing numerical precision.
– Automated alerts deliver full-dataset updates, bridging analysis to actionable trading decisions.
AlphaRank - Relative Strength Portfolio StrategyWHAT IS ALPHARANK?
AlphaRank is a multi-asset relative strength portfolio system that identifies the strongest performing assets within a customizable universe of 10 instruments through pairwise comparison analysis. Unlike traditional relative strength indicators that simply compare price ratios, AlphaRank employs a tournament-style evaluation system using 7 distinct technical indicators to determine true relative strength.
METHODOLOGY - HOW IT WORKS
Core Concept: Pairwise Tournament Analysis
AlphaRank compares every asset against every other asset in your universe (45 unique pairs for 10 assets). For each pair, the system evaluates relative strength using 7 independent indicators:
- RSI (35-period) - Momentum comparison
- Rate of Change (31-period) - Price velocity analysis
- Z-Score (44-period) - Statistical deviation from mean
- Omega Ratio (30-period, smoothed) - Risk-adjusted returns using imported ratio library
- Linear Regression ROC (30-period linreg, 14-period ROC) - Trend strength and acceleration
- Kijun Sen Base (44-period SMA) - Ichimoku-style baseline comparison
- RSI ROC (45-period RSI, 15-period ROC) - Momentum acceleration
Scoring System:
For each pairwise comparison (e.g., ETH vs SOL), the system calculates all 7 indicators on the price ratio (ETH/SOL). Each indicator returns a binary signal (1 or 0). These are summed to create a pair score from 0-7.
If pair score > 3: The numerator asset (ETH) is considered relatively stronger
If pair score ≤ 3: The denominator asset (SOL) is considered relatively stronger
This creates a decisive winner for each pair (no neutral outcomes due to the odd number of indicators).
Final Ranking:
Each asset accumulates points for every pairwise comparison it wins. With 10 assets, each asset faces 9 competitors. Final scores range from 0 (lost all comparisons) to 9 (won all comparisons).
ORIGINALITY - WHY THIS IS DIFFERENT
Traditional Relative Strength:
- Compares assets to a benchmark (like SPY)
- Uses single indicator (usually RSI or price ratio)
- Binary strong/weak classification
AlphaRank Approach:
- Round-robin tournament: every asset vs every other asset
- Multi-indicator consensus (7 indicators, not 1)
- Granular ranking from 0-9 showing exact relative positioning
- Real-time tournament matrix visualization showing all head-to-head results
- Integrated backtesting with position sizing
Key Innovation: By using 7 uncorrelated indicators in a consensus model, AlphaRank reduces false signals from any single indicator's weaknesses. An asset must demonstrate strength across multiple analytical dimensions (momentum, trend, volatility, acceleration) to rank highly.
VISUAL COMPONENTS
Tournament Matrix (Top Right):
Shows every head-to-head matchup
Green dots = asset won that comparison
Red dots = asset lost that comparison
Instantly see which assets dominate across the board
RSPS Score Table (Right side of matrix):
Final relative strength scores (0-9)
Color-coded gradient showing strength hierarchy
Top Assets Table (Bottom Center):
Displays your top N ranked assets
Updates dynamically as rankings change
Equity Curve (Main Chart):
Shows backtested portfolio performance
Compares system returns vs buy-and-hold
Performance Metrics (Bottom):
Sharpe ratio, Sortino ratio, Omega ratio
Maximum drawdown
Individual asset and portfolio metrics
HOW TO USE
Setup:
Choose your 10 assets in the settings (crypto, stocks, indices, etc.)
Set your desired number of top assets to hold (default: 2)
Configure backtest start date and leverage
Interpretation:
Score 7-9: Extremely strong relative to peers - high confidence holdings
Score 4-6: Moderate relative strength - proceed with caution
Score 0-3: Weak relative to peers - avoid or consider shorting
Trading Strategy:
The system automatically allocates capital equally among the top-ranked assets and rebalances when rankings change. This creates a rotation strategy that systematically favors the strongest performers.
TECHNICAL SPECIFICATIONS
Timeframe: Works on all timeframes (1H, 4H, 1D recommended for crypto)
Assets: Fully customizable 10-asset universe
Rebalancing: Automatic when rankings change
SETTINGS EXPLAINED
Leverage Amount: Apply leverage to position sizing (1.0 = no leverage)
Startdate: When to begin backtesting calculations
Highlight Top Assets: How many top-ranked assets to hold (2-5 recommended)
Show Combined Matrix: Toggle the tournament visualization
Show Detailed Metrics: Individual asset performance statistics
Show Small Metrics Table: Simplified performance summary
BACKTESTING METHODOLOGY
The indicator includes full backtesting capabilities. It calculates:
Individual Asset Performance: Each asset's returns if held in isolation
Portfolio Performance: Combined returns of top-ranked assets
Buy & Hold Benchmark: Equal-weight portfolio of all 10 assets
Risk Metrics: Sharpe, Sortino, Omega ratios for all strategies
This allows you to validate the relative strength rotation strategy against simple buy-and-hold.
IMPORTANT NOTES
This is a rotation strategy - it does not predict absolute direction, only relative strength
Works best with correlated assets (e.g., all crypto, all tech stocks)
Requires sufficient history for indicator calculations (minimum 60 bars)
Backtesting uses historical data; future performance may differ
Not financial advice - use for educational purposes
SPY200SMA (+4%/-3%) TQQQ/QQQ STRATEGYSummary of the Improved Strategy: When the price of AMEX:SPY is +4% above the 200SMA BUY NASDAQ:TQQQ and when the price of SPY drops to -3% under the SPY 200SMA SELL everything and slowly DCA into NASDAQ:QQQ over the next 6-12 months or until price returns to +4% above the SPY 200SMA at which point you will go back into 100% TQQQ.
Note: (if the price of QQQ goes 30% above the 200SMA of QQQ deleverage to QQQ or Sell to protect yourself from dot com level event)
More info and stats -https://www.reddit.com/r/LETFs/comments/1nhye66/spy_200sma_43_tqqqqqq_long_term_investment/
Ekoparaloji Cyrpto StrategyEkoparaloji Crypto Strategy - User Information Document
📊 Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
🎯 Key Features
✅ Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
📈 Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
💰 Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
📱 Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
⚠️ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
⚠️ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
🎓 How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Happy trading! 📊
Days Without -x% Move (Within x Days)Days Without X% Move
This indicator tracks consecutive days without a significant price drop, helping traders monitor market stability and potential risk buildup.
How It Works:
- Monitors a rolling window (default: 3 days) for the maximum drawdown
- Resets the counter when price drops by the specified percentage (default: 15%)
- Counts consecutive days where the threshold hasn't been breached
- Higher values indicate extended periods without significant corrections
Key Features:
- Configurable Drop Threshold: Set the percentage drop that resets the counter
- Adjustable Window: Define the lookback period for measuring drawdowns
- Wick Analysis: Option to include or exclude wicks in calculations
- Visual Display: Red area plot shows the current streak length
Use Cases:
- Risk management: Identify when markets are "overdue" for a correction
- Market regime analysis: Compare calm vs volatile periods
- Position sizing: Adjust exposure based on streak length
- Entry timing: Higher streak values may indicate increased correction risk
