VIX term structure forecasting: New evidence based on the realized semi-variances

Abstract

Considering the asymmetric volatility response to positive and negative shocks, this paper investigates VIX term structure forecasting by incorporating the realized upside and downside semi-variances based on high-frequency data, named good volatility and bad volatility, into the discrete-time GARCH-type model. We derive the risk-neutral model specification and calculate the analytical expression of VIX term structure, then estimate parameters by the maximum likelihood method. The MoP strategy (momentum of predictability, Wang et al., 2018) is extended for VIX term structure forecasting. Our empirical results show that incorporating high frequency data and considering the asymmetric shocks of realized variance are necessary to get much more accurate forecasting. The application of MoP strategy demonstrates the superior forecasting ability of integrating the advantages of multiple individual models. The evaluation of economic significance further confirms the superiority of our newly proposed model and the combination of multiple individual models, and results are robust under the alternative realized measure.