PR Quant Formula | 369 Parameters | Golden Falcon Algorithms by Piyush Ratnu

$PR Q^{369} (t) = Ω [α M^{t} + β C^{t} + γ T^{t} + δ O^{t} + θ V^{t} + λ L^{t} + ϕ E^{t} + ψ Q^{t}]$ $Mt=∑i=145wiM(XiM(t)−μiMσiM)M_t=\sum_{i=1}^{45} w_i^M \left( \frac{X_i^M(t)-\mu_i^M}{\sigma_i^M} \right)$

$Ct=∑i=4690wiC[ρi,XAU,DXY(t)+ρi,XAU,US10Y(t)+ρi,XAU,USDJPY(t)]C_t=\sum_{i=46}^{90} w_i^C \left[ \rho_{i,XAU,DXY}(t)+\rho_{i,XAU,US10Y}(t)+\rho_{i,XAU,USDJPY}(t) \right]$ $Tt=∑i=91135wiT[EMA10−EMA21+SMA50−SMA200+BOS+CHOCH]T_t=\sum_{i=91}^{135} w_i^T \left[ EMA_{10}-EMA_{21}+SMA_{50}-SMA_{200}+BOS+CHOCH \right]$

$Ot=∑i=136180wiO[RSIi+MACDi+Stochi+ROCi+VolumeImpulsei]O_t=\sum_{i=136}^{180} w_i^O \left[ RSI_i+MACD_i+Stoch_i+ROC_i+VolumeImpulse_i \right]$

$Vt=∑i=181225wiV[ATRi+HVi+IVi+VolExpansioni+TailRiski]V_t=\sum_{i=181}^{225} w_i^V \left[ ATR_i+HV_i+IV_i+VolExpansion_i+TailRisk_i \right]$

$Lt=∑i=226270wiL[LiquiditySweepi+OrderBlocki+FVGi+DOMi+InstitutionalFlowi]L_t=\sum_{i=226}^{270} w_i^L \left[ LiquiditySweep_i+OrderBlock_i+FVG_i+DOM_i+InstitutionalFlow_i \right]$

$Et=∑i=271315wiE[FOMCi+CPIi+NFPi+GeoRiski+OilShocki+PolicyRiski]E_t=\sum_{i=271}^{315} w_i^E \left[ FOMC_i+CPI_i+NFP_i+GeoRisk_i+OilShock_i+PolicyRisk_i \right]$

$Qt=∑i=316369wiQ[MonteCarloi+Regressioni+Scenarioi+StressTesti+RiskRewardi+Expectancyi]Q_t=\sum_{i=316}^{369} w_i^Q \left[ MonteCarlo_i+Regression_i+Scenario_i+StressTest_i+RiskReward_i+Expectancy_i \right]$

Final probability engine:

$PBUY(t)=11+e−PRQ369(t)\boxed{ P_{BUY}(t)= \frac{1} {1+e^{-PRQ_{369}(t)}} }$ $P_{SELL}(t)=1-P_{BUY}(t)$

Execution equation:

$Vt>ExpansionWAIT,0.40<PBUY<0.60\boxed{ Signal_t= \begin{cases} BUY, & P_{BUY}\geq0.70,\ L_t>0,\ T_t>0,\ V_t<Extreme \\ SELL, & P_{SELL}\geq0.70,\ L_t<0,\ T_t<0,\ V_t>Expansion \\ WAIT, & 0.40<P_{BUY}<0.60 \end{cases} }$

Risk-adjusted trade size:

$Lott=AccountEquity×Risk%SLpoints×PointValueLot_t= \frac{ AccountEquity \times Risk\% }{ SL_{points}\times PointValue }$

Complete PR Quant Gold Equation:

$PRGold(t)=[∑i=1369wiZi(t)]×LiquidityConfirmation×VolatilityFilter×EventRiskAdjustment→Probability→Zone→Execution\boxed{ PR_{Gold}(t)= \left[ \sum_{i=1}^{369}w_iZ_i(t) \right] \times LiquidityConfirmation \times VolatilityFilter \times EventRiskAdjustment \rightarrow Probability \rightarrow Zone \rightarrow Execution }$

FOR PYTHON USERS:

PR Quant Algorithm — Mathematical Equation

$PRQ (t) = i = 1 \sum 369 w_{i} \cdot Z_{i} (t)$

Where:

$Z_{i} (t) = σ ^{i} X ^{i} ( t ) - μ ^{i}$

Final probability score:

$P_{PR} (t) = 1 + e ^{- PRQ (t)} 1$

Trading decision model:

$S i g na l = ⎩ ⎨ ⎧ B U Y, SE LL, W A I T, P^{PR} (t) \geq 0.70 and liquidity zone confirms P^{PR} (t) \leq 0.30 and resistance/order-flow confirms 0.30 < P^{PR} (t) < 0.70$

Expanded PR framework:

$PRQ = α M + βC + γ T + δ O + θ V + λ L + ϕE + ψ Q$

Where:

M = Macroeconomic pressure
C = Correlation engine
T = Trend structure
O = Oscillator momentum
V = Volatility regime
L = Liquidity & institutional flow
E = Event-driven risk
Q = Quantitative probability model

Core formula line:

$PR Q^{369} = f (M, C, T, O, V, L, E, Q) \to P ro babi l i t y \to Z o n e \to E x ec u t i o n$

To be encoded+added: PRSRSDBS D1 W1 MN Framework

$PR Q^{369} (t) = Ω [α M^{t} + β C^{t} + γ T^{t} + δ O^{t} + θ V^{t} + λ L^{t} + ϕ E^{t} + ψ Q^{t}]$ $M_{t} = i = 1 \sum 45 w_{i M} (σ ^{i M} X ^{i M} ( t ) - μ ^{i M})$ $C_{t} = i = 46 \sum 90 w_{i C} [ρ_{i, X A U, D X Y} (t) + ρ_{i, X A U, U S 10 Y} (t) + ρ_{i, X A U, U S D J P Y} (t)]$ $T_{t} = i = 91 \sum 135 w_{i T} [EM A_{10} - EM A_{21} + SM A_{50} - SM A_{200} + BOS + C H OC H]$ $O_{t} = i = 136 \sum 180 w_{i O} [RS I_{i} + M A C D_{i} + St oc h_{i} + RO C_{i} + V o l u m e I m p u l s e_{i}]$ $V_{t} = i = 181 \sum 225 w_{i V} [A T R_{i} + H V_{i} + I V_{i} + V o lE x p an s i o n_{i} + T ai lR i s k_{i}]$ $L_{t} = i = 226 \sum 270 w_{i L} [L i q u i d i t y Sw ee p_{i} + O r d er Bl oc k_{i} + F V G_{i} + D O M_{i} + I n s t i t u t i o na lFl o w_{i}]$ $E_{t} = i = 271 \sum 315 w_{i E} [FOM C_{i} + CP I_{i} + NF P_{i} + G eo R i s k_{i} + O i lS h oc k_{i} + P o l i cy R i s k_{i}]$ $Q_{t} = i = 316 \sum 369 w_{i Q} [M o n t e C a r l o_{i} + R e g ress i o n_{i} + S ce na r i o_{i} + St ress T es t_{i} + R i s k R e w a r d_{i} + E x p ec t an c y_{i}]$

Final probability engine:

$P^{B U Y} (t) = 1 + e ^{- PR Q 369 (t)} 1$ $P_{SE LL} (t) = 1 - P_{B U Y} (t)$

Execution equation:

$S i g na l^{t} = ⎩ ⎨ ⎧ B U Y, SE LL, W A I T, P^{B U Y} \geq 0.70, L^{t} > 0, T^{t} > 0, V^{t} < E x t re m e P^{SE LL} \geq 0.70, L^{t} < 0, T^{t} < 0, V^{t} > E x p an s i o n 0.40 < P^{B U Y} < 0.60$

Risk-adjusted trade size:

$L o t_{t} = S L ^{p o in t s} \times P o in t Va l u e A cco u n tEq u i t y \times R i s k %$

Complete PR Quant Gold Equation:

$P R^{G o l d} (t) = [i = 1 \sum 369 w^{i} Z^{i} (t)] \times L i q u i d i t y C o n f i r ma t i o n \times V o l a t i l i t y F i lt er \times E v e n tR i s k A d j u s t m e n t \to P ro babi l i t y \to Z o n e \to E x ec u t i o n$

To be encoded+added: PRSRSDBS D1 W1 MN Framework

FOR PYTHON USERS:

PRQ369 = (((((DXY*RealYield)+(CPI-PPI)+(NFP-Unemployment)+FedBias+OilShock)/GlobalLiquidity) + ((1/Corr_XAU_DXY)+(1/Corr_XAU_US10Y)+(1/Corr_XAU_USDJPY)+Corr_XAU_OIL) + (((EMA10-EMA21)/ATR14)+((SMA50-SMA200)/VolatilityIndex)+BOS+CHOCH+FibonacciCluster) + (((RSI14*MACD_Hist)+(Stochastic*ROC)+VolumeImpulse)/(MarketExhaustion+1)) + ((ATR14*HistoricalVolatility*ImpliedVolatility)+BlackSwanRisk+GeoPoliticalPremium) + (((OrderBlocks+FVG+LiquidityPools)*DOM_Imbalance*InstitutionalFlow)/(Spread+Slippage+LatencyRisk)) + (((FOMC*w1)+(CPI*w2)+(NFP*w3)+(OPEC*w4)+(WarRisk*w5))*ReactionVelocity) + ((MonteCarlo10000+RegressionScore+StressTestScore+ScenarioProbability+ExpectancyRatio)/DrawdownRisk)) / ((MacroVariance+CorrelationVariance+TrendVariance+MomentumVariance+VolatilityVariance+LiquidityVariance+EventVariance+QuantVariance)**0.5)) * ((LiquidityScore*VolatilityScore*ProbabilityScore)/(RiskScore+0.0001)) * math.exp(-TailRisk)

PRQ-369(t) = Ω { 
[Σ(i=1→45) αi · Zi(Macro_t)]
+ [Σ(i=46→90) βi · ρ(XAU_t , Xi_t)]
+ [Σ(i=91→135) γi · ΔTrend_i(t)]
+ [Σ(i=136→180) δi · Momentum_i(t)]
+ [Σ(i=181→225) θi · Volatility_i(t)]
+ [Σ(i=226→270) λi · Liquidity_i(t)]
+ [Σ(i=271→315) φi · EventRisk_i(t)]
+ [Σ(i=316→369) ψi · QuantProb_i(t)]
}

Where:

Zi(t) = [Xi(t) − μi] / σi

Ω = Liquidity Confirmation × Volatility Filter × Event Risk Adjustment × Execution Discipline

Expanded PR Quant Gold Algorithm:

PRQ-369(t) =
{
Σ αi[(DXY Momentum + Real Yield Pressure + CPI Shock + NFP Surprise + Fed Policy Bias + Fiscal Liquidity + Recession Risk + Energy Risk) / σM]
+
Σ βi[(Corr_XAU,DXY + Corr_XAU_US10Y + Corr_XAU_USDJPY + Corr_XAU_OIL + Corr_XAU_SPX + Corr_XAU_VIX + Corr_XAU_SILVER)]
+
Σ γi[(EMA10−EMA21) + (SMA50−SMA200) + BOS + CHOCH + Fibonacci Confluence + Channel Break + Trendline Reaction]
+
Σ δi[(RSI Divergence + MACD Histogram + Stochastic Pressure + ROC Acceleration + Volume Impulse + Market Breadth + Sentiment Exhaustion)]
+
Σ θi[(ATR Expansion + Historical Volatility + Implied Volatility + Tail Risk + Black Swan Premium + Volatility Clustering + Session Range Expansion)]
+
Σ λi[(Liquidity Sweep + Stop Hunt + Order Block + Fair Value Gap + DOM Imbalance + Footprint Delta + Institutional Flow + Market Depth)]
+
Σ φi[(FOMC Shock + CPI Impact + NFP Impact + Central Bank Event + Geopolitical Risk + Oil Shock + Policy Headline Risk)]
+
Σ ψi[(Monte Carlo Score + Regression Score + Scenario Weight + Stress Test Score + Risk Reward + Expectancy + Confidence Score)]
}

Probability Engine:

P(BUY)t = 1 / [1 + e^(−PRQ-369(t))]

P(SELL)t = 1 − P(BUY)t

Trade Decision Matrix:

IF P(BUY)t ≥ 0.72 
AND Liquidity Confirmation > 0 
AND Trend Score > 0 
AND Volatility Risk < Extreme 
THEN BUY ZONE CONFIRMED

IF P(SELL)t ≥ 0.72 
AND Liquidity Confirmation < 0 
AND Trend Score < 0 
AND Volatility Expansion > Threshold 
THEN SELL ZONE CONFIRMED

IF 0.40 < P(BUY)t < 0.60 
THEN WAIT / NO TRADE

Risk Engine:

Position Size =
(Account Equity × Risk %) / (Stop Loss Points × Point Value)

Expected Value:

EV = [P(win) × Average Win] − [P(loss) × Average Loss]

Final PR Quant Output:

PR GOLD SIGNAL =
PRQ-369(t)
× Liquidity Confirmation
× Volatility Regime
× Event Probability
× Correlation Alignment
× Risk Discipline

= High Probability Zone → Entry → Stop Loss → Target → Execution

To be encoded+added: PRSRSDBS D1 W1 MN Framework

Piyush Ratnu

Quant Gold Strategist

PR Quant Formula | 369 Parameters | Golden Falcon Algorithm by Piyush Ratnu