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 … asymmetric volatility models each in Normal, Student's-t and generalized error distributions with the view to selecting the best …

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 …

forecasting technique with respect to various volatility estimators. The methodology of volatility estimation included Close …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 …

forecasting technique with respect to various volatility estimators. The methodology of volatility estimation includes Close …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 …

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 …

dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …

volatility of individual stock returns and exchange rate returns. …

volatility estimation in terms of volatility jumps being examined and modeled for the international equity market, using such a … properties of jumps. These volatility-estimation and jump properties are also evident in jump modeling based on statistical and …Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six …