This paper applies the model confidence sets (MCS) procedure to a set of volatility models. A MSC is analogous to a … fifty-five volatility models, and the MCS includes about a third of these when evaluated by mean square error, whereas the …

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset … predictive performance relative to the standard volatility models. Furthermore, we construct volatility timing portfolios and …

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 …

varılmaktadır. The study aims to augment commonly applied volatility models with support vector machines and neural networks. The … returns in Istanbul ISE100 stock index. Results suggest that volatility clustering, asymmetry and nonlinearity characteristics …

frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …

while adjusting for the volatility risk premium. Relative model performance does not change during the global financial …

The contributions of error distributions have been ignored while modeling stock market volatility in Nigeria and … studies have shown that the application of appropriate error distribution in volatility model enhances efficiency of the model … asymmetric volatility models each in Normal, Student's-t and generalized error distributions with the view to selecting the best …

empirical application aiming at comparing estimates and predictions of the volatility of financial asset returns. The Dynamic …

In this paper, we estimate, model and forecast Realized Range Volatility, a realized measure and estimator of the … forecasting daily stocks volatility. We consider an HAR model with asymmetric effects with respect to the volatility and the … volatility series and they have a highly in-sample explanatory power. The analysis of the forecast performance in 16 NYSE stocks …

In this paper, we study the methods of combining different volatility forecasts using various GARCH models. Given that … the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from … the fact that there is no single best model for forecasting such volatility. Ample evidence suggests that most of the …