volatility. …

small minority of different cases. Investigating further we find that all volatility series show persistence breaks during …

volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate … that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in …

This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic … volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework … returns and logarithmic realized volatility but also enables flexible adjustments for estimation bias in realized volatility …

We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of … volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear …

Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and … the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper …, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an …

The inhomogeneity of the cross-sectional distribution of realized assets’ volatility is explored and used to build a …-sectional distribution of realized volatility is captured by a finite Gaussian mixture model plus a uniform component that represents … abnormal variations in volatility. Based on the cross-sectional mixture model, at each time point, memberships of assets to …

The aim of this paper is to investigate the relevance of structural breaks for forecasting the volatility of daily … evident. In forecasting volatility, the combination that averages forecasts obtained using different rolling estimation …

economics and financial markets, the effects of combining multiple news shocks on the volatility of tourism demand have not yet …), conditional heteroscedastic volatility models, and multiple news shocks are suitable for forecasting the volatility of the … Malaysian tourist industry. Among them, three primarily volatility models (GARCH, EGARCH, and GJRGARCH) are used in conjunction …

transformations. We forecasted risk (volatility) and price value and compared the results of all models using original, unmodified … prices. From the results, models showed that, on average, a logarithmic transformation achieved better volatility predictions … volatility predictions in terms of mean squared error and accuracy using logarithmic transformation instead of fractional …