Flexible covariance dynamics, high-frequency data, and optimal futures hedging

This paper investigates the out-of-sample performance of hedged portfolios constructed using a novel rotated ARCH (RARCH) model class, which enables flexible covariance dynamics for spot and futures returns. The model’s empirical fit can be significantly improved when it incorporates rotated realized covariance matrix measures. The empirical results suggest that a highly risk-averse hedger implementing the restricted RARCH model would be willing to pay substantial switching fees to capture the incremental gains generated by the flexible and informative alternative; this thus supports the economic importance of incorporating high-frequency data into flexible RARCH modeling processes for the construction of optimal hedged portfolios.