Spread Option Pricing Method Based on Nonparametric Predictive Inference Copula

This paper introduces a novel spread option pricing model, the nonparametric predictive inference–based copula spread option model (NPIC‐SOM), designed to evaluate the interdependence of multiple underlying assets. Through empirical analysis focused on Brent‐WTI spread options, a widely traded derivative, we compare the predictive performance of the NPIC‐SOM against the traditional geometric Brownian motion crack spread option model (GBM‐CSOM). Our findings reveal that the NPIC‐SOM not only forecasts spread option prices closer to empirical values but also captures market fluctuations more accurately than the GBM‐CSOM. This superiority extends across various option types, moneyness levels and delta hedge efficiency. Furthermore, the NPIC‐SOM's reliance on time‐varying parameters enhances prediction accuracy, particularly for extreme market scenarios. These results indicate the practicality and efficiency of the NPIC‐SOM as a robust spread option pricing model, offering valuable insights for option pricing strategies in financial markets.