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 …

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. …

volatility of individual stock returns and exchange rate returns. …

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. …

An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily … heteroskedasticity, which are commonly observed in financial markets. The focus is on parameter estimation, inference and volatility … supported by the data in terms of finding significant threshold nonlinearity, diagnostic checking and volatility forecast …