QUANT SUITE // STOCHASTIC ENGINE v2.0
[ ⚪ FUTURES: CLOSED // WEEKEND SHUTDOWN ]Advanced stochastic modeling, fat-tail risk analysis, and behavioral state transition engines for prop firm fleets.
f* = (p·b − q) / b
Calculates optimal leverage and position sizing adapted specifically for prop firm trailing drawdown buffers (Half-Kelly & Quarter-Kelly models).
CVaR_α = E[X | X ≤ VaR_α]
Evaluates tail-risk during black swan volatility events (NFP, flash crashes). Calculates expected dollar loss across your fleet in the worst 5% of trading days.
P(Xₙ₊₁ = j | Xₙ = i)
Models behavioral state transitions (Winning → Frustration → Revenge). Calculates the exact probability of hitting an absorbing state ($0 balance) after consecutive losses.
E[R(n)/S(n)] = C · nᴴ
Classifies asset time-series into Trending (H > 0.5), Mean-Reverting (H < 0.5), or Random Walk (H = 0.5) to align your R:R model with current market structure.
rₖ = Σ(Yₜ − Ȳ)(Yₜ₋ₖ − Ȳ) / Σ(Yₜ − Ȳ)²
Analyzes CSV trade history to detect psychological dependency—testing whether trade N outcome negatively influences trade N+1 position size.
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