Essays on anomalies in asset pricing

• Main Author: DUAN, Xinrui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/etd_coll/199; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1199&context=etd_coll
• Institution: Singapore Management University

In Chapter 1, we examine whether various anomalies can be driven by two common behavioral forces, namely, "subjective" sentiment (representing investors' subjective biased beliefs) and "objective" limited attention (representing investors' objective cognitive constraints). While sentiment explains well many anomalies that are more speculative on the short-leg, it fails to explain anomalies that are equally speculative on the long and short-leg, including momentum and post-earnings announcement drift. Market-wide attention shifts, proxied by number of news averaged across stocks, significantly attenuates underreaction-driven anomalies, beyond the effect of sentiment. Our findings suggest that increase in market-wide attention can temporarily reduce the cost of attending to market and improve price efficiency. In Chapter 2, we use systematic methods to solve factor timing problem and to improve the performance of factor investing. Past factor returns predict the cross section of factor returns, and this predictability is at its strongest at the one-month horizon (Arnott et al. 2019). We find that factor momentum is pervasive in international stock markets. We show that factor momentum can be captured by trading almost any set of factors. Industry momentum and size-B/M momentum stem from factor momentum. We further find that stock factor momentum, stock factor IVOL, and cross-assets factor momentum can generate alphas. These alphas cannot be explained by current asset pricing models. In Chapter 3, We take an optimal portfolio approach on investing in multiple anomalies. We find that a variety of estimated optimal rules outperform substantially investing in any single anomaly. In addition, although it has been documented that the publication of a given anomaly may significantly reduce its standalone economic value, we show that these anomalies are still valuable collectively in the optimal portfolio even after they are published.