Given that jumps in the implied volatility index (VIX) lead to rapid changes in the level of
volatility, they may contain significant predictive information for the realized variance (RV) of …

This article introduces a class of generative models based on the (G) ARCH-like continuous-
time framework to unify econometric and diffusion-based methods for pricing European …

This study analyzes the discrete jump volatility of the Chinese yuan/US dollar exchange rate
returns using high-frequency five-minute returns from June 2012 to April 2021. Using …

We extend the direct pricing framework and propose a new generalized model for VIX
futures by adding the time-varying component volatility as well as jump intensity to the …

We propose a novel hybrid approach for volatility index (VIX) futures pricing by combining
support vector regression (SVR) with parametric models. Realized semivariances calculated …

This study explores VIX forecasting by proposing a novel model to characterize the volatility
of volatility based on high‐frequency VIX. Specifically, the decomposed jumps, the short …

This article studies the pricing of VIX futures and options by directly modeling the dynamics
of VIX, based on realized semivariances computed from high‐frequency data of VIX. We …

This paper proposes to study volatility index (VIX) futures pricing by directly modeling the
logarithmic VIX while incorporating observable dynamic jumps of the VIX, which are derived …

We propose a DRLS framework to price VIX futures by modeling the logVIX series dynamics
using the ARFIMA and HAR models that introduce the random level shifts component …

As the volatility index (VIX) is nontradable, most investors use the exchange‐traded VIX
futures to hedge their exposures in VIX options. However, the information role of VIX futures …