Due to the high relevance of 1-day volatility forecasts and the increasing demand for zero-day-to-expiration (0DTE …) options on the S&P 500, the Cboe recently introduced the 1-Day Volatility Index (VIX1D). Compared to the longer …-term volatility indices of the VIX family, it is overall lower and more volatile, shows a weaker negative correlation with the S&P 500 …

A two-step estimation method of stochastic volatility models is proposed: In the first step, we estimate the …, standard estimation methods for fully observed diffusion processes are employed, but with the filtered volatility process … replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility …

-frequency intraday returns. It disentangles covariance estimation into variance and correlation components. This allows to estimate … covariance estimation and the jump robustness of the estimator are illustrated in a simulation study. In an application to the …

Availability of high frequency data has improved the capability of computing volatility in an efficient way …. Nevertheless, measuring volatility/covariance from the observation of the asset price is challenging for two main reasons: observed … multivariate volatility, with particular focus on using high frequency data. Exploiting the fact that the method allows to compute …

subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of … the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and … increased during the 2008 financial crisis while it has recently returned to its pre-crisis level. The extracted volatility …

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

. The first step applies a quasi-maximum likelihood estimation procedure, with the realized volatility as a proxy for the … conditional quantile estimation. Specifically, we model the conditional standard deviation as a realized GARCH model and employ … conditional standard deviation, realized volatility, realized quantile, and absolute overnight return as innovations in the …