End-to-End Python implementation of STRAPSim: a novel portfolio similarity metric from Li et al. (2025). Combines Random Forest proximity learning with residual-aware bipartite matching to quantify economic substitutability between ETF baskets. Full replication pipeline included.

The credit API for AI agents

ML for endogenous OTC bond markets, where a dealer's policy reshapes future flow. Reframes learning as finding a fixed-point equilibrium stable under self-induced market adaptation.

Is AI displacement risk priced in corporate bonds? Firm-level exposure (industry automatability times labor intensity) on monthly Z-spreads for 344 issuers. A clean, well-identified null.

📊 Calculate portfolio similarity metrics to enhance ETF alignment and optimize trading strategies in quantitative finance.

End-to-end Python implementation of Dickerson, Mueller & Robotti (JFE 2023). Implements Dick-Nielsen TRACE cleaning, KRS misspecification-robust two-pass CSR, BKRS jackknife bias-corrected Sharpe ratios, and Fama-MacBeth regressions to rigorously identify priced risk factors in U.S. corporate bonds. Prevents false discoveries.