讲座时间：9月16日下午16：30
讲座地点：九里校区零号楼0411室
讲座题目：Stock market volatility predictability in a data-rich world: New insight
讲座摘要：This study develops a prevailing shrinkage method, LASSO with a Markov regime-switching model (MRS-LASSO), to predict US stock market volatility. In total, 17 well-known macroeconomic and financial factors are used in this research. The out-of-sample results reveal that the MRS-LASSO model can successfully predict volatility from statistical and economic viewpoints. We further investigate the predictability of MRS-LASSO in terms of the different market conditions, business cycles, and variable selection. Three factors (equity market returns, short-term reversal factor, and consumer sentiment index) are the most frequent predictors. To investigate the practical implications, we construct the expected variance risk premium (VRP) by using volatility forecasts generated from the LASSO and MRS-LASSO models to forecast future stock returns and find that those models are also powerful.
主讲人简介：马锋，副教授 博导，现任金融与财务学系老师。2019年12月入选四川省“天府万人计划”，2020年6月入选学校“雏鹰计划”。 2021年3月，入选第十三批四川省学术和技术带头人后备人选。现主持国家自然科学基金面上、青年及教育部人文社科项目各一项，参与国家级课题多项。发表学术期刊80余篇，主要研究工作发表在Journal of Banking & Finance、Journal of Empirical Finance、International Journal of Forecasting、Journal of Forecasting等期刊。2021年4月，入选2020年爱思唯尔中国高被引学者（应用经济学）。
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