This paper proposes a new intraday volatility forecasting model, particularly suitable for
modeling a large number of assets. We decompose volatility of high-frequency returns into …

Extensive studies have used stock market information to forecast crude oil prices, and stock
market can more easily derive high-frequency data than crude oil market due to no …

Many studies have documented that daily realized volatility estimates based on intraday
returns provide volatility forecasts that are superior to forecasts constructed from daily …

Basing on the features of emerging Chinese stock market, this article discusses whether
sharply deteriorating liquidity propels the stock market into a “crisis” state and investigates …

This study investigates whether different specifications of univariate GARCH models can
usefully forecast volatility in the foreign exchange market. The study compares in-sample …

This study investigates the impacts of the economic policy uncertainty (EPU) indexes of
China and the G7 countries on Chinese stock market volatility and further constructs a new …

Using the capital asset pricing model, this article critically assesses the relative importance
of computing 'realized'betas from high-frequency returns for Bitcoin and Ethereum—the two …

Realized volatilities observed across several assets show a common secular trend and
some idiosyncratic pattern which we accommodate by extending the class of Multiplicative …

This paper examines the dynamical impact of market wide liquidity on the volatility by using
the Markov switching-regime approach on the Heterogeneous Autoregressive model of the …

We propose and evaluate mixed-frequency multivariate GARCH models for forecasting low-
frequency (weekly) volatility based on high-frequency intraday returns (at 5-minute intervals) …