In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the …-known stylized effects present in financial data. We consider an HAR model with asymmetric effects with respect to the volatility and …

volatility, correlation, beta, quadratic variation, jump variation, and other functionals of an underlying continuous …

, focusing on the relationship between returns and conditional volatility. The conditional mean follows a GARCH-M model, while … PGARCH) were tested. We examine how accurately these GARCH models forecast volatility under various error distributions … the following: (i) the Macedonian stock returns time series display stylized facts such as volatility clustering, high …

In theory, the price of equity is determined by the dividend yields and growth potentials of the firms. There exists … established empirical proof of the impact of macroeconomic changes to the equity markets. With the advent of Islamic equities, and … initial empirical proof for further research on the impact of specific economic variables on the changes in Islamic equity …

Markov-switching models, improves estimates and forecasts of stock return volatility over those of the more conventional …

prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to … simple daily ranges and explore the use of these more efficient volatility measures as predictors of daily ranges. The array … forecasts are produced by a realized range based HAR model with a GARCH volatility-of-volatility component. …

Empirical evidence shows that the dynamics of high frequency–based measures of volatility exhibit persistence and … occasional abrupt changes in the average level. By looking at volatility measures for major indices, we notice similar patterns … conditional expectation of realized volatility. This allows us to address the issues of a slow moving average level of volatility …

One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH …) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative … subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum …

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …