Tag
Quant
Quantitative research, to me, means building models that are mathematically honest about their assumptions and empirically validated before deployment. The Polybius project applies this discipline to prediction market trading: cross-validated calibration, out-of-sample backtesting, and a live deployment with hard risk limits before any capital is at stake.
Blog
March 29, 2026
Accounting in Quantitative Finance and Algorithmic Trading
A graduate-level bridge from double-entry bookkeeping to P&L attribution, the Greeks, risk measures, and tax lot accounting for algorithmic trading.
March 27, 2026
Performance Measurement Under Uncertainty
A measure-theoretic construction of risk-adjusted return: Sharpe, Sortino, Calmar, Omega, and Rachev as functionals on the space of return distributions, with four novel theorems and empirical verification on live backtest data.
March 17, 2026
Price as Geometry: Resolution, Coarse-Graining, and the Structure of Market Noise
A rigorous tour through stationary and non-stationary models of price evolution, with geometric analysis at the forefront. From the random walk null and Black-Scholes as flat geometry, through mean reversion as curved Riemannian diffusion, wavelets, geometric harmonics, and information geometry, anchored throughout by empirical evidence from BTC/ETH millisecond data.
March 9, 2026
BTC/ETH Lead-Lag: Resolution-Dependent Direction Reversal on Binance Spot
Resolution-dependent direction reversal in BTC/ETH lead-lag on Binance spot: ETH leads at 1ms, BTC leads at 100ms, crossover at 15–20ms. January and full year 2025.