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 …

We propose using a Realized GARCH (RGARCH) model to estimate the daily volatility of the
short-term interest rate in the euro–yen market. The model better fits the data and provides …

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

Due to technological advancements over the last two decades, algorithmic trading strategies
are now widely used in financial markets. In turn, these strategies have generated high …

The paper develops a novel realized matrix-exponential stochastic volatility model of
multivariate returns and realized covariances that incorporates asymmetry and long memory …

Successful condition monitoring of rotating machinery relies on the accurate prediction of the
remaining life of the rotating components. This paper proposes a physics-based prognostic …

Multivariate stochastic volatility models with leverage are expected to play important roles in
financial applications such as asset allocation and risk management. However, these …

The paper develops a novel realized stochastic volatility model of asset returns and realized
volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALM …

The aim of this book is to introduce recent developments in stochastic volatility models for
asset returns such as returns of stocks, foreign currencies, and interest rates. It is intended …

This study applies realized GARCH models by introducing several risk measures of intraday
returns into the measurement equation, to model the daily volatility of E-mini S&P 500 index …