This paper suggests how to quantify asymmetries in volatility spillovers that emerge due to bad and good volatility … stocks at the disaggregate level. Moreover, the spillovers of bad and good volatility are transmitted at different magnitudes …

Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in … volatility may spill over at different magnitudes. This paper fills this gap with two contributions. One, we suggest how to … quantify asymmetries in volatility spillovers due to bad and good volatility. Two, using high frequency data covering most …

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …

-varying volatility of the data generating process can have rather adverse effects when inferring about its persistence; e.g. unit root … conditional heteroskedasticity). The paper explores the influence of time-varying volatility on fractionally integrated processes …. Concretely, we discuss how to model long memory in the presence of time-varying volatility, and analyze the effects of such …

- and out-of-sample, using predictive variables such as the dividend yield or the volatility risk premium …

This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of … discriminate different smoothness classes of the underlying stochastic volatility process. In a high-frequency framework we prove … extremely mild smoothness assumptions on the stochastic volatility we thereby derive a consistent test for volatility jumps. A …