PORTFOLIO
Machine Learning Fund Ranking with the Fynup Ratio
A practitioner framework for classifying fund quality with modified Sharpe logic, exponential weighting, and sector blind validation.
Essays on quantitative finance, capital allocation, and decision systems. Deep dives into the frameworks behind the book.
A technical ranking architecture that predicts fund quality with historical return data only. Built on the Fynup framework and tested across 25 sectors.
Phase 1 catalog contains 42 practitioner articles from approved sources only. Open full catalog
A practitioner framework for classifying fund quality with modified Sharpe logic, exponential weighting, and sector blind validation.
Cost equity ratios, implied volatility calibration, and Monte Carlo profit probability bring legal grade evidence to trading misconduct analysis.
Why a theoretically sound futures hedge collapsed under margin pressure, and what optimal hedging functions imply for modern risk desks.
A valuation and suitability lens for swap structures sold to non specialist investors, with scenario logic grounded in case records.
A side by side hedge cost comparison that shows when contingent protection is superior to execution triggers in discontinuous markets.
A disciplined framework for put write and short option overlays when implied volatility persistently exceeds realized volatility.
New essays on quantitative finance and capital allocation. No spam, no fluff. Just research.