岭南学术论坛-金融学系列Seminar-Stock market volatility predictability in a data-rich world: New insight

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612期岭南学术论坛(金融学系列Seminar

报告题目:Stock market volatility predictability in a data-rich world: New insight

  告 人:马锋 (西南交通大学经济与管理学院 副教授)

  持 人:刘彦初(中山大学岭南学院 副教授)

       间:2022513日(周五)下午14:30

       点:MBA902+线上(腾讯会议号:457-303-184

       言:中文+英文

 

Abstract:

This study develops a prevailing shrinkage method, LASSO with a Markov regime-switching model (MRS-LASSO), to predict US stock market volatility. Totally 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.

 

报告人介绍:

       马锋,西南交通大学经济与管理学院副教授,主要研究方向为金融计量、预测及风险管理,在金融市场波动与收益率建模预测等领域取得了系列成果。发表学术论文多篇,主要研究成果发表在Journal of Banking & FinanceJournal of Empirical FinanceInternational Journal of Forecasting、《管理科学学报》等国内外高水平期刊。目前共有6篇论文入选ECONOMICS & BUSINESS(经济与商学)ESI高被引论文。担任China Finance Review International期刊青年编委,2020-2021连续两年入选爱思唯尔中国高被引学者。

        讲座报告人主页:https://glxy.swjtu.edu.cn/info/1254/12565.htm

 

 

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