Option Risk Explain is a Python toolkit for equity-option P&L attribution, valuation reconciliation, and risk exception monitoring, with interactive scenario analysis.
Swap book valuation and daily P&L attribution (carry, roll-down, key-rate curve moves) on a Treasury-bootstrapped curve, plus historical CVA with wrong-way risk
Cross-asset risk & P&L dashboard (rates, credit, FX, equity derivatives): FastAPI + React, sensitivity-explained P&L, data-quality controls. Live demo on Render.
Daily P&L attribution for an options book into greeks, new trades and unexplained, flagging days with big residuals.
Automated monthly fund P&L attribution report: Breaks down portfolio performance by security, sector and geography vs budget and prior month
Synthetic limit order book simulator and market-making research lab with imbalance signals, inventory-aware quoting, adverse selection, PnL attribution, and ETF premium/NAV experiments.
PnL attribution and alpha decay framework for FinBERT sentiment signals — Information Coefficient decay curves, Spearman rank correlation, statistical significance bands, rolling signal quality monitoring.
Derivatives pricing and risk system: 40Y SOFR OIS bootstrap, SABR surface calibration, Greek P&L attribution with FRTB PLA testing, and VaR/ES stress framework documented to SR 11-7.
A Python simulator for studying passive quoting, inventory control, adverse selection, markouts, and risk limits in market making.
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