Academic research relies heavily on exogenous drivers to improve the forecasting accuracy of Bitcoin volatility. The present study provides additional insight into the role of macroeconomic and technical indicators in forecasting the realized volatility of Bitcoin. Using 17 famous macroeconomic...

In this paper, by taking the 5-min high frequency data of the Shanghai Composite Index as example, we compare the forecasting performance of HAR-RV and Multifractal volatility, Realized volatility, Realized Bipower Variation and their corresponding short memory model with rolling windows...

In this study, we examine the daily returns and daily range returns dependent on close–close and the high–low prices when forecasting multifractal volatility in the Chinese stock market. In in-sample forecasting we find that both the daily returns and range returns have a significant impact...

In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window...

In this paper, we investigate the cross-correlations between the stock market in China and markets in Japan, South Korea and Hong Kong. We use not only the qualitative analysis of the cross-correlation test, but also the quantitative analysis of the MF-X-DFA. Our findings confirm the existence...

Our research focuses on forecasting the GDP growth rate by taking a considerable number of economic indicators from various frequencies into account within a new penalty-based mixed-frequency data model called the MIDAS-LASSO model. The empirical findings reveal that the MIDAS-LASSO model has a...