In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily … persistence of volatility, meaning that the conditional volatility tends to revert faster to the long-term mean than the other … statistically significant and positive (thus confirming the hypothesis that an increase in volatility leads an increase in future …

and counterparty risks does not improve forecast accuracy and the predictability seems to derive from the econometric …

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset … forecast market volatilities. Using various evaluation methods, we verify that those high-dimensional models have better … predictive performance relative to the standard volatility models. Furthermore, we construct volatility timing portfolios and …

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

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments … implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors …, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …

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 …

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 …

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