portfolio (Bayer, Siemens and Volkswagen). Classical V aR estimation methodology such as exponential moving average (EMA) as …

theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On …

estimation of the state vector and of the time-varying parameters. We use this method to study the time-varying relationship …

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 … a quasi-maximum likelihood estimation method for the parameter of the factor GARCH-Ito model. We also apply it to …

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with …

leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that … volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

estimation of the state vector and of the time-varying parameters. We use this method to study the timevarying relationship …