一、主讲学生与论文题目：
毕嘉（2016级博士生）：
1. Value at risk, cross-sectional returns and the role of investor sentiment
2. Alternative lottery measure and cross-sectional returns
3. Large Transactions and the MAX Effect: Evidence from China
二、时间：2022年9月29日（周四）下午19:00-21:00
三、地点：腾讯会议
四、点评与讨论教师：
姜富伟 太阳集团tyc539 教授
朱一峰 太阳集团tyc539 副教授
张欣然 太阳集团tyc539 助理教授
五、主持人：朱一峰 太阳集团tyc539 副教授
六、论文摘要
1. Value at risk, cross-sectional returns and the role of investor sentiment
In this paper, we find that the relationship between the value-at-risk (VaR) and expected returns is negative and this negative relationship between the VaR and expected returns can be explained by volatility in the U.S. market. However, for different levels of investor sentiment, this relationship changes. For a high sentiment period, VaR is negatively related with the expected return and cannot be explained by momentum, short-term reversal, volatility, and financial distress. In comparison, the relation between the VaR and expected returns during a low sentiment period is mixed.
2. Alternative lottery measure and cross-sectional returns
We construct a new lottery measure (ALM) to evaluate the lottery preference feature of stocks. The new measure is different from the commonly used lottery proxies: maximum daily return (MAX) and skewness (SKEW). In the U.S. stock market, the relationship between the ALM and expected returns is negative and cannot be explained by MAX. Additionally, the negative predictability of ALM is significant and cannot be explained by other controls when the investor sentiment is high. While no significant relationship has been detected between the ALM and the stock returns during periods of low investor sentiment. Similar results are observed in the Chinese stock market as well. Additionally, we find that the lottery preference is sensitive to the institutional ownership ratio in the U.S., while it is not the case for the Chinese stock market.
3. Large Transactions and the MAX Effect: Evidence from China
In this paper, we confirm the existence of the maximum daily return (MAX) effect in the Chinese stock market. Furthermore, we find that MAX is driven by large transactions whereby their increasing relative transaction volume triggers the MAX effect. This paper proposes the economic mechanism for the MAX effect as follows: institutional investor trading increases first, which causes individual investors to follow so that the total transaction volume increased, finally the MAX effect formatted. After the daily stock return reaches its monthly highest, the institutional trading quickly decays. By contrast, trading by retail investors decreases much slower after the MAX day.
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