Since the introduction of ARCH models close to 40 years ago, a wide range of models for
volatility estimation and prediction have been developed and integrated into asset …

This study provides a holistic and quantitative overview of over 800 mathematical methods
(eg, financial and risk models, statistical tests, statistics and advanced algorithms) taken out …

Advances in the various realized GARCH models have proven effective in taking account of
the bias in realized volatility (RV) introduced by microstructure noise and non-trading hours …

Traditional economic models have rigid-form transition functions when modeling time-
varying volatility of financial time series data and cannot capture other time-varying …

A comprehensive comparison of the volatility predictive abilities of different classes of time-
varying volatility models is considered. The models include the exponential GARCH …

This research introduces a new model, a realized hysteretic GARCH, that is similar to a three‐
regime nonlinear framework combined with daily returns and realized volatility. The setup …

This paper first evaluates the volatility modeling in the Bitcoin market in terms of its realized
volatility, which is considered to be a reliable proxy of its true volatility. Based on the 5 …

Although stochastic volatility and GARCH (generalized autoregressive conditional
heteroscedasticity) models have successfully described the volatility dynamics of univariate …

The realized-GARCH framework is extended to incorporate the two-sided Weibull
distribution, for the purpose of volatility and tail risk forecasting in a financial time series …

This study proposes a class of non-linear realized stochastic volatility (SV) model by
applying the Box–Cox (BC) transformation, instead of the logarithmic transformation, to the …