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 … different volatility estimators and determined the most efficient volatility estimator. The study described the accuracy of the …

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 … different volatility estimators and determined the efficient volatility estimator. The study described the accuracy of …

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in … the volatility time series provides us with new insights into the pricing of risk and increases the accuracy of our …

We propose a new class of conditional heteroskedasticity in the volatility (CH-V) models which allows for time …-varying volatility of volatility in the volatility of asset returns. This class nests a variety of GARCH-type models and the SHARV model … of Ding (2021b). CH-V models can be seen as a special case of the stochastic volatility of volatility model. We then …

forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures …