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. |
|
