We investigate a model in which we connect slowly time varying unconditional long-run volatility with short …-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …

We propose a multiplicative component model for intraday volatility. The model consists of a seasonality factor, as … volatility, while the latter two account for the impact of the state of the limit order book, utilizing an additive structure … non-linearities in the relationship between the limit order book and subsequent return volatility and underlines the …

This paper presents a variety of tests of volatility spillover that are robust to heavy tails generated by large errors …

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 …

and the specification form of the volatility process when modelling volatility with the parametric GARCH family models …. This paper examines the Chinese stock market volatility and the asymmetric effects in the Chinese stock volatility by a … empirical result from the GAMNP model demonstrates better performance for the volatility forecasts, particularly in the out …