We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models …-share equity indices, bond indices and real estate security indices at the country level. Furthermore, we investigate …

volatility índices (namely the originally created RTSVX and the new RVI that has replaced it), using daily data over the period … assumed to follow a white noise or autocorrelated process, it is confirmed by the rolling window estimation, and it holds for …

the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a … vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to … monetary policy shocks. Although the increase in the volatility risk premium, futures-trading volume, and leverage appear to …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our … countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other … results show that by considering time-varying return and volatility spillovers when calculating the risk-minimising portfolio …

between markets and somewhat weaker temporal effects with regard to the US equity market - volatility spillovers decrease when … volatility spillovers during global financial crisis and tranquil periods. The resulting market interconnectedness is depicted by … markets are characterized by greater temporal proximity. Volatility spillovers also present a high degree of …