Drawdown Distribution Analysis (DDA)

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © EdgeTools

//@version=6
indicator("Drawdown Distribution Analysis (DDA) - Professional Risk Assessment", shorttitle="DDA Pro", overlay=false, max_lines_count=500, max_labels_count=500, max_boxes_count=500)

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
// DRAWDOWN DISTRIBUTION ANALYSIS - PROFESSIONAL RISK ASSESSMENT TOOL
// 
// This indicator provides institutional-grade risk analysis through comprehensive drawdown distribution statistics,
// combining advanced risk-adjusted performance metrics with sophisticated statistical modeling.
//
// ACADEMIC FOUNDATION:
// • Markowitz (1952) - Modern Portfolio Theory foundations
// • Sharpe (1966) - Risk-adjusted performance measurement  
// • Chekhlov, Uryasev & Zabarankin (2005) - Drawdown optimization theory
// • Sortino & Price (1994) - Downside risk framework
// • Jorion (2007) - Value at Risk methodology
//
// KEY FEATURES:
// • Statistical distribution analysis with percentile bands (5th-95th)
// • Professional risk-adjusted metrics (Sharpe, Sortino, Calmar ratios)
// • Value at Risk (VaR) and Conditional VaR calculations
// • Volatility-adjusted drawdowns for fair asset comparison
// • Dynamic risk-free rate integration (US10Y or custom)
// • 8 professional color themes optimized for institutional use
// • Real-time risk level classification and alerts
//
// PRACTICAL APPLICATIONS:
// • Portfolio risk assessment and asset allocation
// • Dynamic position sizing based on risk percentiles
// • Institutional portfolio monitoring and reporting
// • Market timing and risk management decisions
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                    CONSTANTS AND HELPERS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

BASE_TRANSPARENCY = 70
TABLE_TRANSPARENCY = 15
EXTREME_THRESHOLD = 2.5
SEVERE_THRESHOLD = 3.0

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                        INPUT GROUPS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Core Analysis Parameters
lookbackPeriod = input.int(500, title="Distribution Analysis Period", minval=100, maxval=2000, 
     tooltip="Statistical analysis period (recommended: 252-756 for daily data). Longer periods provide more robust statistics but slower adaptation to regime changes.", group="Core Settings")
smoothingPeriod = input.int(14, title="Drawdown Smoothing Period", minval=1, maxval=50, 
     tooltip="EMA smoothing period to reduce noise while preserving trend signals. Higher values = smoother but slower response.", group="Core Settings")
dataSource = input.source(close, title="Price Source", 
     tooltip="Price source for analysis (Close recommended for most applications, HL2 for reduced noise)", group="Core Settings")

// Distribution Bands Settings
showPercentileBands = input.bool(true, title="Show Percentile Bands", 
     tooltip="Display percentile-based distribution bands", group="Distribution Bands")
showStdDevBands = input.bool(true, title="Show Standard Deviation Bands", 
     tooltip="Display standard deviation bands (1σ, 2σ, 3σ)", group="Distribution Bands")
showFills = input.bool(true, title="Show Band Fills", 
     tooltip="Fill areas between distribution bands", group="Distribution Bands")

// Risk Assessment
riskThresholdModerate = input.float(50.0, title="Low Risk Threshold (%)", 
     minval=0.0, maxval=100.0, step=5.0, 
     tooltip="Drawdowns better than this % of history = Low Risk (default: top 50%)", group="Risk Assessment")
riskThresholdHigh = input.float(75.0, title="Moderate Risk Threshold (%)", 
     minval=0.0, maxval=100.0, step=5.0, 
     tooltip="Drawdowns better than this % of history = Moderate Risk (default: top 25%)", group="Risk Assessment")
riskThresholdExtreme = input.float(90.0, title="High Risk Threshold (%)", 
     minval=0.0, maxval=100.0, step=5.0, 
     tooltip="Drawdowns better than this % of history = High Risk (default: top 10%)", group="Risk Assessment")

// Advanced Risk Metrics
enableRiskAdjustedMetrics = input.bool(true, title="Enable Risk-Adjusted Metrics", 
     tooltip="Calculate Sharpe, Sortino, Calmar ratios", group="Advanced Metrics")
riskFreeSymbol = input.string("US10Y", title="Risk-Free Rate Asset", 
     tooltip="Symbol for risk-free rate (default: US 10-Year Treasury)", group="Advanced Metrics")
useFixedRiskFreeRate = input.bool(false, title="Use Fixed Risk-Free Rate", 
     tooltip="Use fixed rate instead of live asset data", group="Advanced Metrics")
fixedRiskFreeRate = input.float(4.0, title="Fixed Risk-Free Rate (%)", 
     minval=0.0, maxval=20.0, step=0.25, 
     tooltip="Fixed annual risk-free rate (only if Use Fixed is enabled)", group="Advanced Metrics")
enableVaR = input.bool(true, title="Enable VaR Calculations", 
     tooltip="Calculate Value at Risk metrics", group="Advanced Metrics")
enableVolatilityAdjustment = input.bool(true, title="Volatility-Adjusted Analysis", 
     tooltip="Normalize drawdowns by volatility for asset comparison", group="Advanced Metrics")

// Display Options
showTable = input.bool(true, title="Show Statistics Table", 
     tooltip="Display essential risk metrics", group="Display Options")
showCurrentPosition = input.bool(true, title="Show Current Position Line", 
     tooltip="Highlight current drawdown level", group="Display Options")
showZeroLine = input.bool(false, title="Show Zero Reference Line", 
     tooltip="Display zero line for reference", group="Display Options")
showDistributionInfo = input.bool(true, title="Show Distribution Info", 
     tooltip="Display additional distribution metrics", group="Display Options")

// Appearance Settings
tablePosition = input.string("top_right", title="Table Position", 
     options=["top_right", "top_left", "bottom_right", "bottom_left"], 
     group="Appearance")
colorScheme = input.string("EdgeTools", "Color Theme", 
     options=["Gold", "EdgeTools", "Behavioral", "Quant", "Ocean", "Fire", "Matrix", "Arctic"], 
     group="Appearance")
useDarkMode = input.bool(true, title="Optimize for Dark Theme", 
     tooltip="Optimize colors for dark/light backgrounds", group="Appearance")
lineWidth = input.int(2, title="Main Line Width", minval=1, maxval=5, group="Appearance")
bandLineWidth = input.int(1, title="Band Line Width", minval=1, maxval=3, group="Appearance")

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                 PROFESSIONAL COLOR SCHEME
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Professional color definitions based on selected theme
var color primary_color = #2196F3
var color bullish_color = #4CAF50
var color bearish_color = #FF5252
var color neutral_color = #808080
var color text_color = color.white
var color bg_color = #000000
var color table_bg_color = #1E1E1E
var color header_bg_color = #2D2D2D

// Apply professional color scheme
switch colorScheme
    "Gold" =>
        primary_color := useDarkMode ? #FFD700 : #DAA520
        bullish_color := useDarkMode ? #FFA500 : #FF8C00
        bearish_color := useDarkMode ? #FF5252 : #D32F2F
        neutral_color := useDarkMode ? #C0C0C0 : #808080
        text_color := useDarkMode ? color.white : color.black
        bg_color := useDarkMode ? #000000 : #FFFFFF
        table_bg_color := useDarkMode ? #1A1A00 : #FFFEF0
        header_bg_color := useDarkMode ? #2D2600 : #F5F5DC
    
    "EdgeTools" =>
        primary_color := useDarkMode ? #3b82f6 : #2563eb  // edge-blue-500/600
        bullish_color := useDarkMode ? #22c55e : #16a34a  // edge-green-500/600
        bearish_color := useDarkMode ? #ef4444 : #dc2626  // Professional red
        neutral_color := useDarkMode ? #737373 : #525252  // edge-gray-500/600
        text_color := useDarkMode ? #fafafa : #0a0a0a     // edge-light/dark
        bg_color := useDarkMode ? #0a0a0a : #fafafa       // edge-dark/light
        table_bg_color := useDarkMode ? #171717 : #f9f9f9 // edge-gray-900/50
        header_bg_color := useDarkMode ? #262626 : #e5e5e5 // edge-gray-800/200
    
    "Behavioral" =>
        primary_color := #808080  // Gray 50%
        bullish_color := #00FF00  // Bright Green (Gier)
        bearish_color := #8B0000  // Deep Red (Panik)
        neutral_color := #FFBF00  // Amber (Unsicherheit)
        text_color := useDarkMode ? color.white : color.black
        bg_color := useDarkMode ? #000000 : #FFFFFF
        table_bg_color := useDarkMode ? #1A1A1A : #F8F8F8
        header_bg_color := useDarkMode ? #2D2D2D : #E8E8E8
    
    "Quant" =>
        primary_color := #808080  // Gray (neutral)
        bullish_color := #FFA500  // Orange (positive)
        bearish_color := #8B0000  // Dark Red (negative)
        neutral_color := #4682B4  // Steel Blue
        text_color := useDarkMode ? color.white : color.black
        bg_color := useDarkMode ? #000000 : #FFFFFF
        table_bg_color := useDarkMode ? #0D0D0D : #FAFAFA
        header_bg_color := useDarkMode ? #1A1A1A : #F0F0F0
    
    "Ocean" =>
        primary_color := useDarkMode ? #20B2AA : #008B8B  // Light Sea Green / Dark Cyan
        bullish_color := useDarkMode ? #00CED1 : #4682B4  // Dark Turquoise / Steel Blue
        bearish_color := useDarkMode ? #FF4500 : #B22222  // Orange Red / Fire Brick
        neutral_color := useDarkMode ? #87CEEB : #2F4F4F  // Sky Blue / Dark Slate Gray
        text_color := useDarkMode ? #F0F8FF : #191970     // Alice Blue / Midnight Blue
        bg_color := useDarkMode ? #001F3F : #F0F8FF       // Navy / Alice Blue
        table_bg_color := useDarkMode ? #001A2E : #E6F7FF
        header_bg_color := useDarkMode ? #002A47 : #CCF2FF
    
    "Fire" =>
        primary_color := useDarkMode ? #FF6347 : #DC143C  // Tomato / Crimson
        bullish_color := useDarkMode ? #FFD700 : #FF8C00  // Gold / Dark Orange
        bearish_color := useDarkMode ? #8B0000 : #800000  // Dark Red / Maroon
        neutral_color := useDarkMode ? #FFA500 : #CD853F  // Orange / Peru
        text_color := useDarkMode ? #FFFAF0 : #2F1B14     // Floral White / Dark Brown
        bg_color := useDarkMode ? #2F1B14 : #FFFAF0       // Dark Brown / Floral White
        table_bg_color := useDarkMode ? #261611 : #FFF8F0
        header_bg_color := useDarkMode ? #3D241A : #FFE4CC
    
    "Matrix" =>
        primary_color := useDarkMode ? #00FF41 : #006400  // Matrix Green / Dark Green
        bullish_color := useDarkMode ? #39FF14 : #228B22  // Neon Green / Forest Green
        bearish_color := useDarkMode ? #FF073A : #8B0000  // Neon Red / Dark Red
        neutral_color := useDarkMode ? #00FFFF : #008B8B  // Cyan / Dark Cyan
        text_color := useDarkMode ? #C0FF8C : #003300     // Light Green / Very Dark Green
        bg_color := useDarkMode ? #0D1B0D : #F0FFF0       // Very Dark Green / Honeydew
        table_bg_color := useDarkMode ? #0A1A0A : #E8FFF0
        header_bg_color := useDarkMode ? #112B11 : #CCFFCC
    
    "Arctic" =>
        primary_color := useDarkMode ? #87CEFA : #4169E1  // Light Sky Blue / Royal Blue
        bullish_color := useDarkMode ? #00BFFF : #0000CD  // Deep Sky Blue / Medium Blue
        bearish_color := useDarkMode ? #FF1493 : #8B008B  // Deep Pink / Dark Magenta
        neutral_color := useDarkMode ? #B0E0E6 : #483D8B  // Powder Blue / Dark Slate Blue
        text_color := useDarkMode ? #F8F8FF : #191970     // Ghost White / Midnight Blue
        bg_color := useDarkMode ? #191970 : #F8F8FF       // Midnight Blue / Ghost White
        table_bg_color := useDarkMode ? #141B47 : #F0F8FF
        header_bg_color := useDarkMode ? #1E2A5C : #E0F0FF

// Transparency settings
backgroundAlpha = useDarkMode ? 85 : 92
bandAlpha = useDarkMode ? 70 : 85
tableAlpha = useDarkMode ? 80 : 15

// Map to existing variable names for compatibility
neutralColor = primary_color
lowRiskColor = bullish_color
moderateRiskColor = neutral_color
highRiskColor = bearish_color
extremeRiskColor = bearish_color

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                   CORE CALCULATIONS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Enhanced Peak Tracking with Rolling Window
var float runningPeak = na
var float maxPeakInPeriod = na

// Initialize peak tracking
if na(runningPeak)
    runningPeak := dataSource
    maxPeakInPeriod := dataSource

// Update running peak (all-time high tracking)
runningPeak := math.max(runningPeak, dataSource)

// Update peak within analysis period  
maxPeakInPeriodCalc = ta.highest(dataSource, lookbackPeriod)
if bar_index < lookbackPeriod
    maxPeakInPeriod := math.max(nz(maxPeakInPeriod, dataSource), dataSource)
else
    maxPeakInPeriod := maxPeakInPeriodCalc

// Calculate raw drawdown from peak
rawDrawdown = runningPeak > 0 ? ((dataSource - runningPeak) / runningPeak) * 100 : 0.0

// Smoothed drawdown for analysis
smoothedDrawdown = ta.ema(rawDrawdown, smoothingPeriod)

// Ensure sufficient data for distribution analysis
validBars = bar_index >= lookbackPeriod

// Risk-Free Rate Calculation
riskFreeRateValue = useFixedRiskFreeRate ? fixedRiskFreeRate : 
                   request.security(riskFreeSymbol, "D", close, lookahead=barmerge.lookahead_off)
// Fallback to fixed rate if symbol data unavailable
riskFreeRate = na(riskFreeRateValue) ? fixedRiskFreeRate : riskFreeRateValue

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                              DISTRIBUTION STATISTICAL ANALYSIS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Core Distribution Metrics - Extract ta.stdev calls first
drawdownMeanCalc = ta.sma(smoothedDrawdown, lookbackPeriod)
drawdownStdDevCalc = ta.stdev(smoothedDrawdown, lookbackPeriod)

// Apply conditions
drawdownMean = validBars ? drawdownMeanCalc : na
drawdownStdDev = validBars ? drawdownStdDevCalc : na
drawdownVariance = validBars and not na(drawdownStdDev) ? math.pow(drawdownStdDev, 2) : na

// Percentile Analysis (Key Distribution Points) - Extract function calls first
p5_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 5)
p10_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 10)
p25_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 25)
p50_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 50)
p75_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 75)
p90_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 90)
p95_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 95)

// Apply conditions
p5_drawdown = validBars ? p5_calc : na
p10_drawdown = validBars ? p10_calc : na
p25_drawdown = validBars ? p25_calc : na
p50_drawdown = validBars ? p50_calc : na
p75_drawdown = validBars ? p75_calc : na
p90_drawdown = validBars ? p90_calc : na
p95_drawdown = validBars ? p95_calc : na

// Current Position in Distribution - Extract ta.percentrank call first
currentPercentileRankCalc = ta.percentrank(smoothedDrawdown, lookbackPeriod)
currentPercentileRank = validBars ? currentPercentileRankCalc : na

// Standard Deviation Bands
std1_upper = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean + drawdownStdDev : na
std1_lower = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean - drawdownStdDev : na
std2_upper = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean + 2 * drawdownStdDev : na
std2_lower = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean - 2 * drawdownStdDev : na
std3_upper = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean + 3 * drawdownStdDev : na
std3_lower = validBars and not na(drawdownMean) and not na(drawdownStdDev) ? drawdownMean - 3 * drawdownStdDev : na

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                    RISK ASSESSMENT
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Risk Level Determination
riskLevel = validBars and not na(currentPercentileRank) ?
     currentPercentileRank >= (100 - riskThresholdModerate) ? "Low" :
     currentPercentileRank >= (100 - riskThresholdHigh) ? "Moderate" :
     currentPercentileRank >= (100 - riskThresholdExtreme) ? "High" : "Extreme" : "Insufficient Data"

// Risk Color Mapping
riskColor = riskLevel == "Low" ? lowRiskColor :
           riskLevel == "Moderate" ? moderateRiskColor :
           riskLevel == "High" ? highRiskColor :
           riskLevel == "Extreme" ? extremeRiskColor : neutralColor

// Z-Score for statistical significance
zScore = validBars and not na(drawdownMean) and not na(drawdownStdDev) and drawdownStdDev > 0 ? 
         (smoothedDrawdown - drawdownMean) / drawdownStdDev : na

// Statistical Significance Levels
significantDrawdown = validBars and not na(zScore) ? math.abs(zScore) > EXTREME_THRESHOLD : false
severeDrawdown = validBars and not na(zScore) ? math.abs(zScore) > SEVERE_THRESHOLD : false

// Maximum Drawdown in Analysis Period
maxDrawdownCalc = ta.lowest(smoothedDrawdown, lookbackPeriod)
maxDrawdownInPeriod = validBars ? maxDrawdownCalc : na

// Recovery Analysis
dataSourceLowest = ta.lowest(dataSource, lookbackPeriod)
drawdownRecovery = runningPeak > 0 ? ((dataSource - dataSourceLowest) / dataSourceLowest) * 100 : 0.0

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                 ADVANCED RISK-ADJUSTED METRICS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Returns Calculation for Risk-Adjusted Metrics - Extract ta.stdev calls first
returns = validBars ? math.log(dataSource / dataSource[1]) : na
annualizedReturnsCalc = ta.sma(returns, lookbackPeriod) * 252 * 100
volatilityCalc = ta.stdev(returns, lookbackPeriod) * math.sqrt(252) * 100

// Apply conditions
annualizedReturns = validBars ? annualizedReturnsCalc : na  // Annualized %
volatility = validBars ? volatilityCalc : na  // Annualized volatility %

// Sharpe Ratio Calculation
excessReturn = validBars and not na(annualizedReturns) ? annualizedReturns - riskFreeRate : na
sharpeRatio = validBars and not na(excessReturn) and not na(volatility) and volatility > 0 ? excessReturn / volatility : na

// Downside Deviation for Sortino Ratio - Extract ta.stdev call first
downsideReturns = validBars and not na(returns) ? (returns < 0 ? returns : 0) : na
downsideDeviationCalc = ta.stdev(downsideReturns, lookbackPeriod) * math.sqrt(252) * 100

// Apply conditions
downsideDeviation = validBars ? downsideDeviationCalc : na
sortinoRatio = validBars and not na(excessReturn) and not na(downsideDeviation) and downsideDeviation > 0 ? excessReturn / downsideDeviation : na

// Calmar Ratio (Return / Max Drawdown)
calmarRatio = validBars and not na(annualizedReturns) and not na(maxDrawdownInPeriod) and maxDrawdownInPeriod < -0.01 ? 
              annualizedReturns / math.abs(maxDrawdownInPeriod) : na

// Volatility-Adjusted Drawdown for Asset Comparison
volatilityAdjustedDrawdown = enableVolatilityAdjustment and validBars and not na(smoothedDrawdown) and not na(volatility) and volatility > 0 ? 
                             smoothedDrawdown / (volatility / 20) : smoothedDrawdown  // Normalized to 20% vol baseline

// Value at Risk Calculations (VaR) - Reuse existing percentile calculations
// 95% VaR = 5th percentile (already calculated as p5_calc)
// 99% VaR = 1st percentile  
var99_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 1)

// Apply conditions
var95 = validBars ? p5_calc : na  // Reuse p5_calc for efficiency
var99 = validBars ? var99_calc : na

// Conditional VaR components (calculate remaining percentiles)
p2_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 2)
p3_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 3)
p4_calc = ta.percentile_nearest_rank(smoothedDrawdown, lookbackPeriod, 4)
// p1_calc = var99_calc (1st percentile)
// p5_calc already calculated above

// Conditional VaR (Expected Shortfall) - approximation using worst 5% cases
cvar95 = validBars and not na(var95) ? (var99_calc + p2_calc + p3_calc + p4_calc + p5_calc) / 5 : na

// Risk Efficiency Score (0-100, higher = better risk-adjusted performance)
riskEfficiencyScore = validBars and not na(sharpeRatio) and not na(currentPercentileRank) ? 
                     math.max(0, math.min(100, (sharpeRatio * 10 + currentPercentileRank) / 2)) : na

// Maximum Drawdown Duration (approximation)
var int drawdownDuration = 0
var bool inDrawdown = false

if validBars and smoothedDrawdown < -1.0  // In drawdown
    if not inDrawdown
        drawdownDuration := 1
        inDrawdown := true
    else
        drawdownDuration := drawdownDuration + 1
else
    inDrawdown := false

maxDrawdownDurationCalc = ta.highest(drawdownDuration, lookbackPeriod)
maxDrawdownDuration = validBars ? maxDrawdownDurationCalc : na

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                         PLOTTING
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Zero reference line
plot(showZeroLine ? 0 : na, title="Zero Line", color=color.new(color.gray, 0), linewidth=1, style=plot.style_line, display=display.all)

// Main drawdown line with dynamic coloring
mainLineColor = color.new(riskColor, 0)
plot(smoothedDrawdown, title="Smoothed Drawdown (%)", color=mainLineColor, linewidth=lineWidth)

// Volatility-Adjusted Drawdown (optional overlay)
plot(enableVolatilityAdjustment ? volatilityAdjustedDrawdown : na, 
     title="Vol-Adjusted Drawdown (%)", color=color.new(primary_color, 30), linewidth=lineWidth-1, style=plot.style_line, display=display.none)

// Plot invisible lines for alert access
plot(sharpeRatio, title="Sharpe Ratio", display=display.none)
plot(riskEfficiencyScore, title="Risk Efficiency Score", display=display.none)
plot(riskFreeRate, title="Risk-Free Rate (%)", display=display.none)

// Current position line (secondary overlay of the main drawdown)
plot(showCurrentPosition and validBars ? smoothedDrawdown : na, 
     title="Current Position Line", color=color.new(riskColor, 40), linewidth=1, 
     style=plot.style_line)

// Mean line  
plot(drawdownMean, title="Mean Drawdown", color=color.new(primary_color, 40), linewidth=bandLineWidth)

// Percentile Bands
p95_plot = plot(showPercentileBands ? p95_drawdown : na, title="95th Percentile", 
                 color=color.new(bearish_color, bandAlpha), linewidth=bandLineWidth)
p90_plot = plot(showPercentileBands ? p90_drawdown : na, title="90th Percentile", 
                 color=color.new(bearish_color, bandAlpha + 10), linewidth=bandLineWidth)
p75_plot = plot(showPercentileBands ? p75_drawdown : na, title="75th Percentile", 
                 color=color.new(neutral_color, bandAlpha), linewidth=bandLineWidth)
p50_plot = plot(showPercentileBands ? p50_drawdown : na, title="50th Percentile (Median)", 
                 color=color.new(primary_color, bandAlpha), linewidth=bandLineWidth)
p25_plot = plot(showPercentileBands ? p25_drawdown : na, title="25th Percentile", 
                 color=color.new(bullish_color, bandAlpha), linewidth=bandLineWidth)
p10_plot = plot(showPercentileBands ? p10_drawdown : na, title="10th Percentile", 
                 color=color.new(bullish_color, bandAlpha + 10), linewidth=bandLineWidth)
p5_plot = plot(showPercentileBands ? p5_drawdown : na, title="5th Percentile", 
                 color=color.new(bullish_color, bandAlpha + 20), linewidth=bandLineWidth)

// VaR Lines
var95_plot = plot(enableVaR ? var95 : na, title="95% VaR", 
                  color=color.new(bearish_color, bandAlpha - 20), linewidth=bandLineWidth + 1, style=plot.style_linebr)
var99_plot = plot(enableVaR ? var99 : na, title="99% VaR", 
                  color=color.new(bearish_color, bandAlpha - 30), linewidth=bandLineWidth + 1, style=plot.style_linebr)

// Standard Deviation Bands
std1_upper_plot = plot(showStdDevBands ? std1_upper : na, title="1σ Upper", 
                       color=color.new(primary_color, bandAlpha), linewidth=bandLineWidth)
std1_lower_plot = plot(showStdDevBands ? std1_lower : na, title="1σ Lower", 
                       color=color.new(primary_color, bandAlpha), linewidth=bandLineWidth)
std2_upper_plot = plot(showStdDevBands ? std2_upper : na, title="2σ Upper", 
                       color=color.new(neutral_color, bandAlpha), linewidth=bandLineWidth)
std2_lower_plot = plot(showStdDevBands ? std2_lower : na, title="2σ Lower", 
                       color=color.new(neutral_color, bandAlpha), linewidth=bandLineWidth)
std3_upper_plot = plot(showStdDevBands ? std3_upper : na, title="3σ Upper", 
                       color=color.new(bearish_color, bandAlpha), linewidth=bandLineWidth)
std3_lower_plot = plot(showStdDevBands ? std3_lower : na, title="3σ Lower", 
                       color=color.new(bearish_color, bandAlpha), linewidth=bandLineWidth)

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                         FILLS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Percentile band fills
fill(p95_plot, p90_plot, color=showPercentileBands and showFills ? color.new(bearish_color, backgroundAlpha) : na, title="95th-90th Percentile")
fill(p90_plot, p75_plot, color=showPercentileBands and showFills ? color.new(bearish_color, backgroundAlpha + 5) : na, title="90th-75th Percentile")
fill(p75_plot, p50_plot, color=showPercentileBands and showFills ? color.new(neutral_color, backgroundAlpha) : na, title="75th-50th Percentile")
fill(p50_plot, p25_plot, color=showPercentileBands and showFills ? color.new(primary_color, backgroundAlpha) : na, title="50th-25th Percentile")
fill(p25_plot, p10_plot, color=showPercentileBands and showFills ? color.new(bullish_color, backgroundAlpha) : na, title="25th-10th Percentile")
fill(p10_plot, p5_plot, color=showPercentileBands and showFills ? color.new(bullish_color, backgroundAlpha + 10) : na, title="10th-5th Percentile")

// Standard deviation fills
fill(std2_upper_plot, std1_upper_plot, color=showStdDevBands and showFills ? color.new(primary_color, backgroundAlpha + 5) : na, title="1σ-2σ Upper")
fill(std1_lower_plot, std2_lower_plot, color=showStdDevBands and showFills ? color.new(primary_color, backgroundAlpha + 5) : na, title="1σ-2σ Lower")
fill(std3_upper_plot, std2_upper_plot, color=showStdDevBands and showFills ? color.new(neutral_color, backgroundAlpha + 5) : na, title="2σ-3σ Upper")
fill(std2_lower_plot, std3_lower_plot, color=showStdDevBands and showFills ? color.new(neutral_color, backgroundAlpha + 5) : na, title="2σ-3σ Lower")

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                 BACKGROUND HIGHLIGHTING
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Risk-based background coloring
bgcolor(riskLevel == "Extreme" ? color.new(bearish_color, backgroundAlpha + 10) : na, title="Extreme Risk Zone")
bgcolor(riskLevel == "High" ? color.new(bearish_color, backgroundAlpha + 15) : na, title="High Risk Zone")
bgcolor(significantDrawdown and not severeDrawdown ? color.new(neutral_color, backgroundAlpha + 15) : na, title="Significant Drawdown")
bgcolor(severeDrawdown ? color.new(bearish_color, backgroundAlpha + 5) : na, title="Severe Drawdown")

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                    STATISTICS TABLE
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Professional table styling (shared by both tables)
tableBgColor = color.new(table_bg_color, tableAlpha)
headerTextColor = text_color
labelTextColor = text_color
valueTextColor = text_color
headerBgColor = color.new(header_bg_color, 20)

if showTable and barstate.islast and validBars
    
    // Position mapping
    pos = switch tablePosition
        "top_right" => position.top_right
        "top_left" => position.top_left
        "bottom_right" => position.bottom_right
        "bottom_left" => position.bottom_left
        => position.top_right
    
    // Create compact main table
    var table statsTable = table.new(pos, 2, 9, 
         border_width=1, 
         bgcolor=tableBgColor,
         border_color=color.new(neutral_color, 50))
    
    if barstate.islast
        table.clear(statsTable, 0, 0, 1, 8)
        
        // Professional Headers
        table.cell(statsTable, 0, 0, "Risk Analysis", 
             text_color=headerTextColor, bgcolor=headerBgColor, text_size=size.small)
        table.cell(statsTable, 1, 0, "Value", 
             text_color=headerTextColor, bgcolor=headerBgColor, text_size=size.small)
        
        // Core Risk Metrics
        table.cell(statsTable, 0, 1, "Current Drawdown", text_color=labelTextColor, text_size=size.small)
        table.cell(statsTable, 1, 1, str.tostring(smoothedDrawdown, "#.##") + "%", 
             text_color=riskColor, text_size=size.small)
        
        table.cell(statsTable, 0, 2, "Risk Level", text_color=labelTextColor, text_size=size.small)
        table.cell(statsTable, 1, 2, riskLevel, 
             text_color=riskColor, text_size=size.small)
        
        table.cell(statsTable, 0, 3, "Percentile Rank", text_color=labelTextColor, text_size=size.small)
        table.cell(statsTable, 1, 3, str.tostring(currentPercentileRank, "#.#") + "%", 
             text_color=riskColor, text_size=size.small)
        
        // Risk-Adjusted Performance
        table.cell(statsTable, 0, 4, "Sharpe Ratio", text_color=labelTextColor, text_size=size.small)
        sharpeColor = not na(sharpeRatio) ? (sharpeRatio > 1.0 ? bullish_color : (sharpeRatio > 0 ? primary_color : bearish_color)) : neutral_color
        table.cell(statsTable, 1, 4, str.tostring(sharpeRatio, "#.##"), 
             text_color=sharpeColor, text_size=size.small)
        
        table.cell(statsTable, 0, 5, "Risk Efficiency Score", text_color=labelTextColor, text_size=size.small)
        efficiencyColor = not na(riskEfficiencyScore) ? (riskEfficiencyScore > 70 ? bullish_color : (riskEfficiencyScore > 40 ? primary_color : bearish_color)) : neutral_color
        table.cell(statsTable, 1, 5, str.tostring(riskEfficiencyScore, "#.#") + "/100", 
             text_color=efficiencyColor, text_size=size.small)
        
        // Key Risk Levels
        table.cell(statsTable, 0, 6, "Max Drawdown", text_color=labelTextColor, text_size=size.small)
        table.cell(statsTable, 1, 6, str.tostring(maxDrawdownInPeriod, "#.##") + "%", 
             text_color=bearish_color, text_size=size.small)
        
        table.cell(statsTable, 0, 7, "95% VaR", text_color=labelTextColor, text_size=size.small)
        table.cell(statsTable, 1, 7, str.tostring(var95, "#.##") + "%", 
             text_color=bearish_color, text_size=size.small)
        
        table.cell(statsTable, 0, 8, "Annualized Return", text_color=labelTextColor, text_size=size.small)
        returnColor = not na(annualizedReturns) and annualizedReturns > 0 ? bullish_color : bearish_color
        table.cell(statsTable, 1, 8, str.tostring(annualizedReturns, "#.##") + "%", 
             text_color=returnColor, text_size=size.small)



// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//                                                        ALERTS
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════

// Risk level change alerts
extremeRiskAlert = riskLevel == "Extreme" and riskLevel[1] != "Extreme"
highRiskAlert = riskLevel == "High" and riskLevel[1] != "High" and riskLevel[1] != "Extreme"
significantDrawdownAlert = significantDrawdown and not significantDrawdown[1]
severeDrawdownAlert = severeDrawdown and not severeDrawdown[1]

// Statistical significance alerts
newMaxDrawdownAlert = validBars and smoothedDrawdown <= maxDrawdownInPeriod and smoothedDrawdown[1] > maxDrawdownInPeriod

// Risk-Adjusted Metric Alerts
sharpeDeclineAlert = enableRiskAdjustedMetrics and validBars and not na(sharpeRatio) and not na(sharpeRatio[1]) and 
                     sharpeRatio < 0 and sharpeRatio[1] >= 0
riskEfficiencyAlert = enableRiskAdjustedMetrics and validBars and not na(riskEfficiencyScore) and not na(riskEfficiencyScore[1]) and 
                     riskEfficiencyScore < 30 and riskEfficiencyScore[1] >= 30

alertcondition(extremeRiskAlert, 
     title="Extreme Risk Level Alert", 
     message="Drawdown has entered extreme risk territory ({{plot(\"Smoothed Drawdown (%)\")}}}%)")

alertcondition(highRiskAlert, 
     title="High Risk Level Alert", 
     message="Drawdown has reached high risk level ({{plot(\"Smoothed Drawdown (%)\")}}}%)")

alertcondition(significantDrawdownAlert, 
     title="Statistically Significant Drawdown", 
     message="Drawdown is statistically significant (Z-Score: {{plot(\"Z-Score\")}})")

alertcondition(severeDrawdownAlert, 
     title="Severe Drawdown Alert", 
     message="Drawdown has reached severe levels (Z-Score: {{plot(\"Z-Score\")}})")

alertcondition(newMaxDrawdownAlert, 
     title="New Maximum Drawdown", 
     message="New maximum drawdown reached: {{plot(\"Smoothed Drawdown (%)\")}}%")

alertcondition(sharpeDeclineAlert, 
     title="Sharpe Ratio Negative", 
     message="Sharpe ratio has turned negative: {{plot(\"Sharpe Ratio\")}}")

alertcondition(riskEfficiencyAlert, 
     title="Poor Risk Efficiency", 
     message="Risk efficiency score below 30: {{plot(\"Risk Efficiency Score\")}}/100")

// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
// PROFESSIONAL QUALITY ASSURANCE & ACADEMIC COMPLIANCE
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
//
// This indicator meets institutional standards for:
// • Regulatory compliance (educational/research purposes)
// • Risk management integration capabilities  
// • Audit trail and methodology transparency
// • Performance monitoring and validation
// • Scalability for portfolio management applications
//
// ACADEMIC DISCLAIMER:
// This indicator implements peer-reviewed methodologies and maintains transparency in its statistical approach.
// Past performance does not guarantee future results. The academic research cited provides theoretical
// foundation but does not constitute investment advice.
//
// TECHNICAL IMPLEMENTATION:
// • Pine Script™ v6 compliance with optimized performance
// • Function call consistency for reliable execution
// • Memory-efficient calculations and data handling
// • Professional error handling and edge case management
//
// For detailed methodology, citations, and application examples, refer to the comprehensive
// academic documentation provided with this indicator.
//
// © EdgeTools - Professional Trading Analytics
// License: Mozilla Public License 2.0
// ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════