one-month variance swap rate, i.e., the CBOE Volatility Index (VIX) accurately. Our research suggests that one should use …

methods indicate that volatility connectedness is higher than the return connectedness among these assets. Furthermore …

mean and volatility. The endogenous structural breakpoint unit root test, ARDL model, and alternative volatility models … price while the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in …

One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility … volatility were founded on econometric models. Research on bitcoin volatility forecasting using machine learning algorithms is … bitcoin's return volatility and Value at Risk. The objective of this study is to compare their out-of-sample performance in …

We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of … volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear …

degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which … forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation … distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized …