Deleveraging Detection Score

// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © realanthonyc https://www.tradingview.com/u/realanthonyc

//@version=6
// ----------------------------------------------------------------------
//  Deleveraging Detection Score (DDS)
//  On GitHub: https://github.com/realanthonyc/Deleveraging-Detection-Score
//  v1.1.2
// ----------------------------------------------------------------------
indicator("Deleveraging Detection Score", shorttitle="DDS", overlay=false, precision=2)

// ==========================================
// 1. LOGIC INPUTS & GUIDANCE
// ==========================================
i_proxy_sym = input.symbol("NASDAQ:QQQ", "Liquidation Proxy", tooltip="Choose a liquidity proxy to monitor its correlation. Examples:\n- Metals: NQ1! / QQQ / SPY\n- Crypto: DXY (preferred) / QQQ\n- NQ1! / QQQ: DXY (preferred) / US10Y")
sigmaThr    = input.float(3.00, "Crash Sigma Threshold", step=0.25, tooltip="Extreme drop threshold.\n- Gold: 3.0\n- Silver: 3.5 - 4.0\n- Copper: 3.5\n- Crypto: 4.0+")
atrZThr     = input.float(2.00, "ATR Z-Score Threshold", step=0.25, tooltip="Volatility spikes.\n2 = 2 standard deviations above mean")
lb          = input.int(10, "Stress Lookback (Bars)", minval=3, tooltip="Memory of the market (for Stress Cascade Count).")
corrLen     = input.int(20, "Sync Corr Length", minval=10, maxval=60, tooltip="Higher = more stable sync signal. Metals often look cleaner at 20-40.")

// ==========================================
// 2. CORE PHYSICS (Liquidation Engine)
// ==========================================
f_sec(sym, expr) => request.security(sym, timeframe.period, expr, gaps=barmerge.gaps_off, lookahead=barmerge.lookahead_off)

// A. Price Velocity (Standardized Log Returns)
logRet      = math.log(close / close[1])
retSD       = ta.stdev(logRet, 60)
// Explicit zero-dispersion check
retSig      = (retSD == 0 or na(retSD)) ? 0.0 : logRet / retSD

// B. Volatility Intensity (ATR Z-Score)
atr_v       = ta.atr(14)
atrSMA      = ta.sma(atr_v, 100)
atrSD       = ta.stdev(atr_v, 100)
// Ensure Z-score calculation is stable
atrZ        = (atrSD == 0 or na(atrSD)) ? 0.0 : (atr_v - atrSMA) / atrSD

// C. Global Synchronicity (Correlation with Liquidity Proxy)
proxy_logRet = f_sec(i_proxy_sym, math.log(close / close[1]))
market_corr  = nz(ta.correlation(logRet, proxy_logRet, corrLen), 0.0)

// D. Stress Identifiers
is_crash    = retSig < -sigmaThr
is_vol      = atrZ > atrZThr and logRet < 0
stressBar   = is_crash or (retSig < -2.0 and atrZ > 1.0)

// E. Cascade Logic (Dynamic Thresholding)
stressCount = 0
for i = 0 to lb - 1
    if stressBar[i] == true
        stressCount += 1

// Dynamic threshold logic
casMin      = math.max(2, math.floor(lb / 4))
is_cascade  = stressCount >= casMin

// ==========================================
// 3. SCORING & COLOR SYSTEM
// ==========================================
baseScore   = is_crash ? 75 : is_vol ? 45 : is_cascade ? 25 : 0

// Support both positive and inverse correlation
sync_positive = (market_corr > 0.5) and (logRet < 0) and (proxy_logRet < 0)
sync_inverse  = (market_corr < -0.5) and (logRet < 0) and (proxy_logRet > 0)
syncBonus     = sync_positive or sync_inverse

score       = math.min(100, baseScore + (syncBonus ? 10 : 0))

c_stable    = color.new(color.green, 0)
c_recovery  = color.new(color.orange, 0)
c_stress    = color.new(color.red, 0)
c_liq       = color.new(color.purple, 0)

regime_col  = score >= 70 ? c_liq : score >= 40 ? c_stress : score >= 20 ? c_recovery : c_stable

// ==========================================
// 4. VISUALS
// ==========================================
plot(score, "Risk Level %", color=regime_col, linewidth=2)
bgcolor(score >= 20 ? color.new(regime_col, 92) : na)

// ==========================================
// 5. TACTICAL DASHBOARD
// ==========================================
var table panel = table.new(position.top_right, 2, 5, border_width=1, border_color=color.white)

f_row(r, l, v, bg) =>
    table.cell(panel, 0, r, l, bgcolor=color.new(color.black, 0), text_color=color.white, text_size=size.small)
    table.cell(panel, 1, r, v, bgcolor=bg, text_color=color.white, text_size=size.small)

if barstate.islast
    state_txt = score >= 70 ? "FORCED LIQUIDATION" : score >= 40 ? "HIGH STRESS" : score >= 20 ? "RECOVERY" : "NORMAL"
    strat_txt = score >= 40 ? "DEFEND / EXIT" : score >= 20 ? "WATCH" : "ATTACK"

    f_row(0, "Market Status", state_txt, regime_col)
    f_row(1, "Risk Level", str.tostring(score) + "%", regime_col)

    // Palette-consistent sync coloring (support strong negative correlation)
    corr_col = math.abs(market_corr) > 0.5 ? c_stress : math.abs(market_corr) > 0.3 ? c_recovery : c_stable
    f_row(2, "Liquidity Proxy Sync", str.tostring(market_corr, "#.##"), corr_col)

    cas_col = stressCount >= casMin ? (score >= 40 ? c_stress : c_recovery) : c_stable
    f_row(3, "Stress Cascade Count", str.tostring(stressCount) + " / " + str.tostring(casMin), cas_col)

    f_row(4, "Strategic Action", strat_txt, regime_col)