for volatility, correlation and covariance using high frequency financial data. It also implements complementary … paper first presents the issues associated with exploiting high frequency financial data. We then describe the volatility …

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence … of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component … of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two …

crises, liquidity variables have a negative influence on the volatility, in contrast to the time period after the outbrake of …

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 …

Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data … matrix and facilitates estimation of large volatility matrices. However, for predicting future volatility matrices, these …. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility …

allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a … provide a statistical approach to estimate the volatility of these factors. The efficacy of this approach relative to the use … of models based on squared returns is demonstrated for forecasts of the market volatility and a portfolio allocation …