Academic Engagement (Representative)    | 
    Publications  | 
    [1] Chao Liang, Feng Ma, Lu Wang, et al. The   Information Content of Uncertainty Indices for Natural Gas Futures Volatility   Forecasting. Journal of Forecasting, 2021, 40(7): 1310-1324. [2] Yongan Xu, Jianqiong Wang, Zhonglu Chen, Chao   Liang. Economic Policy Uncertainty and Stock Market Returns: New Evidence.   The North American Journal of Economics and Finance, 2021, 58: 101525. [3] Chao Liang, Yan Li, Feng Ma, et al. Global   Equity Market Volatilities Forecasting: A Comparison of Leverage Effects,   Jumps, and Overnight Information. International Review of Financial Analysis,   2021, 75(8): 101750. [4] Chao Liang, Yu Wei, Likun Lei, Feng Ma.   Global Equity Market Volatility Forecasting: New Evidence. International   Journal of Finance&Economics, 2021, 27(1): 594-609. [5] eng Ma, Chao Liang, Qing Zeng, Haibo Li.   Jumps and Oil Futures Volatility Forecasting: A New Insight. Quantitative   Finance, 2021, 21(5): 853-863. [6] Jiqian Wang, Feng Ma, Chao Liang, et al.   Volatility Forecasting Revisited Using Markov‐switching with Time‐varying Probability Transition. International   Journal of Finance&Economics, 2021, 27(1): 1387-1400. [7] Yaojie Zhang, Feng Ma, Chao Liang, et al.   Good Variance, Bad Variance, and Stock Return Predictability. International   Journal of Finance&Economics, 2021, 26(3): 4410-4423. [8] Zhonglu Chen, Chao Liang, Muhammad Umar. Is   Investor Sentiment Stronger Than VIX and Uncertainty Indices in Predicting   Energy Volatility? Resources Policy, 2021, 74: 102391. [9] Yongan Xu, Jianqiong Wang, Zhonglu Chen, Chao   Liang. Sentiment Indices and Stock Returns: Evidence from China.   International Journal of Finance&Economics, 2021. [10] Chao Liang, Feng Ma, Ziyang Li, et al. Which   Types of Commodity Price Information Are More Useful for Predicting US Stock   Market Volatility? Economic Modelling, 2020, 93: 642-650. [11] Chao Liang, Yaojie Zhang, Xiafei Li, Feng Ma.   Which Predictor Is More Predictive for Bitcoin Volatility? And Why?   International Journal of Finance&Economics, 2020, 27(2): 1947-1961. [12] Feng Ma, Chao Liang, Yuanhui Ma, et al.   Cryptocurrency Volatility Forecasting: A Markov Regime‐switching MIDAS Approach. Journal of   Forecasting, 2020, 39(8): 1277-1290. [13] Yan Li, Chao Liang, Feng Ma, et al. The Role of   the IDEMV in Predicting European Stock Market Volatility During the COVID-19   Pandemic. Finance research letters, 2020, 36: 101749. [14] Yan Li, Lian Luo, Chao Liang, Feng Ma. The   Role of Model Bias in Predicting Volatility: Evidence from The US Equity   Markets. China Finance Review International, 2020.  | 
    
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