The Cost of a Free Lunch: Evidence from U.S. Derivatives Markets

Battle Count: 75

The paper directly addresses the economics of parity enforcement in U.S. equity-index options, a core activity for market makers and arbitrage desks. The carry gap quantifies the hidden implementation cost of a strategy that appears risk-free in price space, with direct implications for position sizing, margin planning, funding cost allocation, and alpha decay in options-based arbitrage. The GBM path-risk term provides a practical reduced-form proxy for survival-capital requirements that can inform real-time risk management and capital allocation decisions in derivatives trading.

The core pipeline involves: (1) minute-level NBBO option data processing and call-put pair matching; (2) cross-sectional regression per date-maturity to extract implied discount factors (Azzone-Baviera method); (3) OIS curve bootstrapping; (4) carry-gap construction; (5) GBM path-risk term computation using VIX/RVX and OIS rates; (6) OLS with HAC inference; (7) LOYO validation and Engle-Granger tests. The data preprocessing and OIS bootstrap are non-trivial, and the full pipeline requires commercial data access. However, the regression itself is standard OLS. Estimated ~1 hour on 16 parallel workers for both markets.

The paper specifies MATLAB R2025b as the implementation environment, identifies data sources (ThetaData for option NBBO, Databento for futures BBO, FRED for NFCI and DGS), and describes the Azzone and Baviera (2021) identification pipeline in detail. However, no code repository is provided, ThetaData and Databento are commercial data vendors, and the full pipeline execution time (~1 hour on 16 workers) is noted but not shared. The OIS bootstrap procedure and sample filters are described but not fully reproducible without the raw data.