This paper introduces the Markov-Switching Multifractal Duration (MSMD) model by adapting the MSM stochastic volatility … feature of durations generated by the MSMD process propagates to counts and realized volatility. We employ a quasi …

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 …

Volatility has been used as an indirect means for predicting risk accompanied with an asset. Volatility explains the … variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the … different volatility estimators and determined the most efficient volatility estimator. The study described the accuracy of the …

Volatility had been used as an indirect means for predicting risk accompanied with the asset. Volatility explains the … variations in returns. Forecasting volatility had been a stimulating problem in the financial systems. The study examined the … different volatility estimators and determined the efficient volatility estimator. The study described the accuracy of …

volatility of the Standard and Poors 500 index among recent extensions of the heterogeneous autoregressive model. While we find …, improvements achieved by the inclusion of implied volatility turn out to be insignificant. …

appropriate volatility measure for most financial applications. For a wide variety of markets, the GARCH, EGARCH, and GJR (or … Guan (2005, JFM) does not. Furthermore, the GARCH and GJR forecasts are especially biased following high volatility days … which cause a large jump in forecast volatility which is rarely fully realized …