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 …. Using Nigeria All Share Index from January 2, 2008 to February 11, 2013, this study estimates first order symmetric and …

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 …

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional … Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV … two standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV …

value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by … Muneer & Maheswaran (2018b). We show that the robust volatility ratio is unbiased both in the population as well as in finite … samples. We empirically test the robust volatility ratio on 9 global stock indices from America, Asia Pacific and EMEA markets …

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence … of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component … of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two …

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. …