Current models for predicting volatility do not incorporate information flow and are solely based on historical … predictor of its stock volatility. The results show that future stock volatility is better predicted by our method than the … flow or as an active source for new information influencing future volatility. Our data suggest that semantic content may …

Margin regulation raises two policy concerns. First, an alignment of margins to volatility can amplify procyclicality … following volatility spikes but does not immediately lower margins following volatility declines, implying that margin …

return and volatility than their non-Shariah compliant counterparts. …

, switching and herding all contribute to market volatility in price and return and to volatility clustering, their impacts are … increase in switching intensity reduces the return volatility and in particular a low switching intensity reduces the price … volatility and increases the level of the significant ACs, but the effect becomes opposite when the switching intensity is high …

The literature has shown that the volatility of Stock and Forex rate market returns shows the characteristic of long … memory. Another fact that is shown in the literature is that this feature may be spurious and volatility actually consists of …

which the price and the volatility are the main variables used by the function EVaR. …

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet …-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility …

individual effects on economic growth and volatility using the power-ARCH framework with annual data since the 1890s. The results …