A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted … Hedge Index). The results presented here show promising application in modelling and predicting volatility, as well as … identifying current volatility regimes predominating the market …

Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern … forecasting techniques, based on machine learning, can readily be employed when treating volatility as a univariate, daily time …-ahead volatility by using high-frequency data. We show that the dilated convolutional filters are ideally suited to extract relevant …

This paper analyses the implementation and calibration of the Heston Stochastic Volatility Model. We first explain how …

This paper analyses the implementation and calibration of the Heston Stochastic Volatility Model. We first explain how …

stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et …

developed time series operators can be used to directly compute statistical variables such as volatility from inhomogeneous data … volatility, but the conventional calculation from daily data, sampled at a certain daytime, is strongly sensitive to the choice …

This article proposes a simple and intuitive framework to combine a discrete volatility forecast series produced by a …-combining binomial trees that capture the distributional properties of the volatility forecasts. Finally, the framework is employed to …

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies … computationally attractive and feasible for large dimensions. We demonstrate its strong predictive potential for financial volatility …

volatility index was created to capture the investor expectations about the crypto-currency ecosystem. VCRIX is built based on … CRIX and offers a forecast for the mean annualized volatility of the next 30 days, re-estimated daily. The model was back …

high-frequency data better and produce more accurate forecasts than competing realized volatility and option …