Based on the previous studies that Markov-type GARCH models exhibit inconsistent
predictive ability over different horizons, we conduct the improvement of predictive power of …

Accurately predicting volatility has always been the focus of government decision-making
departments, financial regulators and academia. Therefore, it is very crucial to precisely …

The purpose of this paper is to explore whether the categorical Economic Policy Uncertainty
(EPU) indices are predictable for the volatility of carbon futures, in the mixed data sampling …

This article develops an artificial intelligent based forecasting model for the day ahead stock
market profit. The suggested model is constructed based on the long short term memory …

This paper adds the decomposed components of realized volatility to investigate China's
stock market volatility based on the mixed data sampling (MIDAS) framework. Empirical …

This paper proposes an industry volatility concentration indicator measured by the
Herfindahl index (HHI) of industry volatilities. Based on data from January 1928 to …

The stock market forecast is an important and challenging issue. Its distribution forecast of
returns can provide information that is more complete, compared to point forecast and …

This paper introduces an asymmetric robust weighted least squares (ARLS) approach to
improve the forecasting performance of the heterogeneous autoregressive model for …

This thesis comprises a trilogy of manuscripts that share a common focus on volatility–a
critical measure of the uncertainty associated with movements in asset prices. Volatility plays …

Price variation and market liquidity are intimately related to the market conditions under
which the arrival of new information is being priced-in. However, the literature is limited on …