small minority of different cases. Investigating further we find that all volatility series show persistence breaks during …

Prediction of volatility is to a larger extent anchored on the properties of a volatility time series i.e. mean …-reversion or random-walk. The consistency of mean-reversion or random-walk on the ZSE stock price and return volatility remain … unexplored. This study therefore attempts to investigate the behavior of ZSE stock price and return volatility using the class of …

This study employs machine learning models to forecast and comprehend the implied volatility of China ETF50. We develop … a hybrid model named LSTM-ML, leveraging historical implied volatility, moneyness, and time-to-maturity as input … features. The LSTM component captures dynamic hidden information from time series of volatility to generate temporal features …

addition, we assess the relevance of distinct breaks for estimating models of volatility spillovers. We present evidence of … in the conditional correlations and provide evidence of contagion. We detect time-variation in volatility spillovers and …

empirical application aiming at comparing estimates and predictions of the volatility of financial asset returns. The Dynamic …

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 …