Research
01Multi-factor US large-cap equity strategy
A sector-neutral, beta-neutral tilt toward value, momentum and quality built from SEC filings and price data with point-in-time discipline. Then re-run on 35 years of survivorship-free CRSP/Compustat data: the same 0.38 information ratio, statistically significant over the full sample, earned in the 1990s and 2000s and flat since 2010. Factsheet, dashboard, full code.
Goldman Sachs QIS product review
Three client-style notes on the team's public funds. The Absolute Return Tracker, reverse-engineered: ten ETFs explain 89% of its returns and a passive clone earns back the fee. ActiveBeta U.S. Large Cap, rebuilt from its published rulebook: the rules recover 0.40 correlation of active returns, stable out of sample.
Cross-asset trend & carry program
Systematic macro across equities, bonds, currencies and commodities with volatility targeting and risk parity, benchmarked against Goldman Sachs' Managed Futures Strategy Fund. A gradient-boosted ML overlay, tested under purged walk-forward validation, lost to the simple rule and is reported as such.
Fund X-ray
An interactive tool. Type a fund and see what it holds judged only by its returns, its style tilts, how closely a passive clone tracks it, and whether the fee bought anything the clone could not. Every public Goldman Sachs QIS product is in it.
About
I spent last summer at Coolibar as an artificial intelligence engineer, leading a seven-person team that shipped the company's mobile app and deploying AI agents across its HR, marketing and sales workflows. Before that, a summer at Club Med negotiating supplier contracts in three languages.
The research here started from one question: what do quantitative investment products actually do for the people who own them, and can that be explained in a page? Every project answers with public data, published code and a section on what the evidence cannot show.