Jennifer(Jie) Li

Abstract:

This paper exploits a unique account-level dataset of structured funds to study how arbitrageurs trade during bubble periods (i.e., when large positive swings of mispricing occur in structured funds). I find that arbitrageurs can both ride bubbles during the bubble-formation periods and make arbitrage trades during the bubble-crashing periods. In particular, arbitrageurs ride bubbles more aggressively when local unsophisticated investors start to trade in the direction of fueling bubbles, and quit this strategy when mispricing becomes too high. Identification tests based on the social contagion effect of unsophisticated investors supports a causal interpretation. Moreover, arbitrageurs who can ride bubbles make more trading profits than those who only conduct arbitrage trades. These results suggest that arbitrageurs do not always trade in the direction of eliminating mispricing, and that local information may play a pivotal role in shaping their trading motivations.

Abstract:

We examine whether behavior bias related to mutual fund investment can be influenced by the social norms to which they are exposed. A higher level of social trust may elicit stronger investor reactions by increasing the perceived credibility of fund-reported performance. This effect enhances flow-performance sensitivity, which mitigates investors’ disposition effect. Alternatively, societal trust may reduce concerns about expropriation, thereby weakening investors’ need to react to poor performance. The resulting lower flow-performance sensitivity increases the disposition effect. Based on a proprietary dataset of complete account-level trading information for all investors in a large mutual fund family in China, we find compelling evidence 1) of a significant disposition effect among fund investors; 2) that a higher degree of social trust is associated with higher flow-performance sensitivity; and 3) that (high) trust-induced flows mitigate the disposition effect. Our results suggest that, in addition to cognitive biases, investor behavior is also strongly influenced by social norms.

Abstract:

Inspired by the recent health-science findings that air pollution affects mental health and cognition, we examine whether air pollution can intensify cognitive bias observed in the financial markets. Based on a proprietary dataset obtained from a large mutual fund family in China, which contains the complete trading information of over 773,198 accounts covering more than 200 cities, we find that air pollution significantly increases the disposition effect of investors. Analysis based on two plausible exogenous variations in air quality (the Huai-river policy and the vast dissipation of air pollution especially due to strong winds) supports a causal interpretation. Our results have important normative implications that air pollutions may incur severe indirect (social) costs associated with enhanced cognitive biases.