<p>This dissertation studies the impact of mutual fund managers' beliefs on fund performance in the first chapter and focuses on the impact of firm behavior on stock performance in the second chapter. </p> <p><br></p> <p>In the first chapter, I utilize the Revealed Preference Theory to recover fund manager belief formation directly from their actual trading activities. By relating stock holdings in a fund's portfolio to past factor returns, I document three facts about managers' belief formation: 1. In contrast to belief extrapolation, a substantial fraction of mutual fund managers act as contrarian investors who expect lower factor returns after a good factor performance; 2. Whether a fund trades in an extrapolative or contrarian way is due to its managers' expectation biases rather than fund style investment strategy, fund catering strategy or fund risk preference; and 3. Contrarian managers generate superior performance, are more experienced investors, charge higher expense ratios, and manage smaller US equity funds. The top (contrarian) managers significantly outperform the bottom (extrapolative) managers by a return of 3.4% per annum after adjusting by FFC4 factor models.</p> <p><br></p> <p>The second chapter is co-authored paper with Yan Liu and Feng Zhang. In this chapter, we systematically replicate the bulk of long-run event studies conducted in the last three decades from 1990 to 2020 using extended samples and four long-run performance measures. The final sample contains 62 papers of long-run event studies and 148 corporate events. Our findings suggest that long-run return anomalies documented in the last three decades are not robust, and firms do not earn long-run abnormal returns following various types of corporate events. Only 2% of the 148 corporate events we replicate earn post-event abnormal returns that are statistically significant at the 5% level based on all the four performance measures, and the fraction further shrinks to 0% at the 1% significance level. Viewed together, our findings suggest that these long-run abnormal returns after corporate events are likely the result of data mining or "p-hacking".</p>

<p>  </p> <p>In the first chapter, we developed a dynamic equilibrium model of multiple stocks with extrapolators under the framework of Barberis, Greenwood, Jin, and Shleifer (2015a). Our model builds on the fact that extrapolative investors assign different relative weights of recent versus distant past return when forming their beliefs. We find that stock price increases in its own past performance measure, and is additionally associated with the past performance measure of the other stock if their dividends are correlated. The stock with higher relative weight have higher stock price, higher stock volatility, and lower risk premium. Both the own stock’s and the other stock’s past performance measure negatively predicts future stock price changes. </p> <p><br></p> <p>The second chapter includes Adem Atmaz, Stefano Cassella, and Huseyin Gulen as co-authors. In this chapter, we document considerable cross-sectional variation in survey expectations about aggregate stock market returns. While most investors are extrapolators who expect higher returns after a good market performance, some are contrarians who expect lower returns after a good performance. More notably, compared to extrapolators, contrarians have less persistent expectations that are corrected more quickly. Accordingly, we develop a dynamic equilibrium model accounting for these differences in expectations and find that the equilibrium stock price exhibits short-term momentum and long-term reversal as in the data. Furthermore, we test the key predictions of the model linking the shortterm momentum to observable differences between extrapolators and contrarians and find supportive evidence for our mechanism. </p> <p><br></p> <p>The third chapter includes Adem Atmaz and Suleyman Basak as co-authors. In this chapter, we develop a dynamic model of costly stock short-selling and lending market and obtain implications simultaneously supporting many empirical regularities. In our model, investors’ belief disagreement leads to lenders and short-sellers, who pay shorting fees to borrow stocks from lenders. Our main novel results are as follows. Short interest predicts future stock returns negatively and has a stronger predictive power than the corresponding dividend-price ratio. Higher short-selling risk can be associated with lower stock returns and less short-selling activity. Stock volatility is increased under costly short-selling. An application to the GameStop episode yields implications consistent with observed patterns. </p>