I develop a framework to analyze demand curves for multiple risky securities at extended horizons in a setting with limits-to-arbitrage. Following an unexpected change in uninformed investor demand for several assets, I predict returns of each security to be proportional to the contribution of that security's demand shock to the risk of a diversified arbitrage portfolio. I show that securities that are not affected by demand shocks but are correlated with securities undergoing changes in demand should experience returns related to their hedging role in arbitrageurs' portfolios. Finally, I predict a negative cross-sectional relation between post-event returns and the initial return associated with the change in demand. I confirm these predictions using data from a unique redefinition of the Nikkei 225 index in Japan, in which 255 stocks simultaneously undergo significant changes in index investor demand, causing more than ¥2,000 billion of trading in one week and large price changes followed by subsequent reversals for all of the reweighted stocks

The cash conversion cycle (CCC) is important for fundamental analysis as an indicator of management effectiveness in cash and financing. However, there is a lack of empirical evidence for its implications on asset pricing except for the very recent findings that high CCCs negatively predict stock returns in the U.S. By investigating 47 developed and emerging markets from 1993 to 2018, we find a mild CCC effect across the globe. The Low-minus-High equal-weighted hedge portfolios sorted by components of CCC yield significant Fama-French five-factor alphas ranging from 0.277 to 0.730% per month. Our results are consistent with a mispricing explanation by analyzing earnings prediction, announcement returns around future earnings, and limits of arbitrage although there is also some evidence for a risk-based explanation. Moreover, the CCC effect is stronger in emerging markets than developed markets and for markets with more political risk and less integrated with the global market

Hazard stocks are the opposite of lottery stocks. We proxy hazard stocks with the minimum daily idiosyncratic return over the past month, “IMIN,” and examine the relation between hazard stocks and expected returns. The literature on lottery stocks implies that investors should discount hazard stocks. Anomalously, we find a negative relation between IMIN and future returns. Hedge portfolios that are long high IMIN stocks and short low IMIN stocks generate monthly alphas of -0.52% to -0.76%. The results are robust after controlling for numerous firm characteristics and corporate events. The hazard stock anomaly is primarily driven by limits to arbitrage and, to a lesser degree, by firm-level information uncertainty. Via the Reg SHO pilot program, we provide causal evidence that the apparent asymmetric preferences across lottery and hazard stocks are due to arbitrage asymmetry as described by Stambaugh et al. (2015). This demonstrates that asymmetric arbitrage may yield what appear to be asymmetric preferences

Empirical studies linking liquidity provision to asset prices follow naturally from inventory models. Liquidity suppliers and market markers profit from providing immediacy to less patient investors, but have limited inventory-carrying and risk-bearing capacity. Similarly, limits to arbitrage arguments rely on certain market participants accommodating buying or selling pressure. These liquidity suppliers/arbitrageurs are willing to accommodate trades—and, therefore, hold suboptimal portfolios—only if they are able to buy (sell) at a discount (premium) relative to future prices. Thus, large liquidity-supplier inventories should coincide with large buying or selling pressure, which causes price movements that subsequently reverse themselves. By identifying and studying the inventories of traders who are central to the trading process and whose primary roll is to provide liquidity—New York Stock Exchange (NYSE) market

The recent credit crisis has highlighted the importance of market liquidity and its interaction with the price of credit risk. We investigate this interaction by relating the liquidity of corporate bonds to the basis between the credit default swap (CDS) spread of the issuer and the par-equivalent bond yield spread. The liquidity of a bond is measured using a recently developed measure called latent liquidity , which is defined as the weighted average turnover of funds holding the bond, where the weights are their fractional holdings of the bond. We find that bonds with higher latent liquidity are more expensive relative to their CDS contracts after controlling for other realized measures of liquidity. Analysis of interaction effects shows that highly illiquid bonds of firms with a greater degree of uncertainty are also expensive, consistent with limits to arbitrage between CDS and bond markets, due to the higher costs of “shorting” illiquid bonds. Additionally, we document the positive effects of liquidity in the CDS market on the CDS-bond basis. We also find that several firm- and bond-level variables related to credit risk affect the basis, indicating that the CDS spread does not fully capture the credit risk of the bond

Preface xi Richard H. Thaler Acknowledgments xix List of Abbreviations xxiii Chapter 1: A Survey of Behavioral Finance by Nicholas Barberis and Richard H. Thaler 1 Part I: Limits to Arbitrage Chapter 2: The Limits of Arbitrage by Andrei Shleifer and Robert W. Vishny 79 Chapter 3: How Are Stock Prices Affected by the Location of Trade? by Kenneth A. Froot and Emil M. Dabora 102 Chapter 4: Can the Market Add and Subtract? Mispricing in Tech Stock Carve-outs by Owen A. Lamont and Richard H. Thaler 130 Part II: I Stock Returns and the Equity Premium Chapter 5: Valuation Ratios and the Long-run Stock Market Outlook: An Update by John Y. Campbell and Robert J. Shiller 173 Chapter 6: Myopic Loss Aversion and the Equity Premium Puzzle by Shlomo Benartzi and Richard H. Thaler 202 Chapter 7: Prospect Theory and Asset Prices by Nicholas Barberis, Ming Huang, and Tano Santos 224 Part III: Empirical Studies of Overreaction and Underreaction Chapter 8: Contrarian Investment, Extrapolation, and Risk by Josef Lakonishok, Andrei Shleifer, and Robert W. Vishny 273 Chapter 9: Evidence on the Characteristics of Cross-sectional Variation in Stock Returns by Kent Daniel and Sheridan Titman 317 Chapter 10: Momentum by Narasimhan Jegadeesh and Sheridan Titman 353 Chapter 11: Market Efficiency and Biases in Brokerage Recommendations by Roni Michaely and Kent L. Womack 389 Part IV: Theories of Overreaction and Underreaction Chapter 12: A Model of Investor Sentiment by Nicholas Barberis, Andrei Shleifer, and Robert W. Vishny 423 Chapter 13: Investor Psychology and Security Market Under- and Overreaction by Kent Daniel, David Hirshleifer, and Avanidhar Subrahmanyam 460 Chapter 14: A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets by Harrison Hong and Jeremy C. Stein 502 Part V: Investor Behavior Chapter 15: Individual Investors by Brad M. Barber and Terrance Odean 543 Chapter 16: Naive Diversification Strategies in Defined Contribution Savings Plans by Shlomo Benartzi and Richard H. Thaler 570 Part VI: Corporate Finance Chapter 17: Rational Capital Budgeting in an Irrational World by Jeremy C. Stein 605 Chapter 18: Earnings Management to Exceed Thresholds by Francois Degeorge, Jayendu Patel, and Richard Zeckhauser 633 Chapter 19: Managerial Optimism and Corporate Finance by J. B. Heaton 667 List of Contributors 685 Index 695

Many empirical studies have rejected the law of one price. That prices of a good differ across locations has been explained by differences in product attributes and costs of local inputs, transport costs, trade barriers, and that buyers have imperfect information about prices in different locations; see Penelopi K. Goldberg and Michael M. Knetter (1997) for a survey. We examine the law of one price in situations where none of the mentioned reasons for its failure can be invoked. It has also been suggested that deviations from the law of one price are a consequence of rigid nominal prices and that different countries typically have different currencies. We explore whether this can contribute to our understanding of deviations from the law of one price. Our data are taken from three Scandinavian duty-free outlets, where each product (at the same location) has price tags in at least two currencies. Hence, a consumer has the option to choose between several prices for the same identical good. In such a setting there is a strong prior that the law of one price (LOP hereafter) holds well. However, the potential for arbitrage will arise because nominal prices are not continuously adjusted while exchange rates fluctuate daily. Based on standard tests, we reject LOP at all duty-free outlets. Given that LOP does not hold here, it is less surprising that many previous studies have found that prices of similar products at different locations differ significantly. Nevertheless, the main conclusion of the paper is that in this natural experiment, LOP remains a useful guide to the behavior of relative prices. As deviations become large, nominal prices are adjusted to reduce the deviations from LOP, thereby limiting arbitrage opportunities. The patterns at the duty-free outlets suggest that there is a band of inaction so that small deviations from LOP may persist (for almost a decade in one case), but that large deviations quickly lead firms to adjust relative prices. The findings are consistent with costly arbitrage and fixed costs of adjusting nominal prices