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Return Reversal

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The short-term reversal anomaly, the phenomenon that stocks with relatively low returns over the past month or week earn positive abnormal returns in the following month or week, and stocks with high returns earn negative abnormal returns, is well-researched, where a lot of research has been made about this particular anomaly. However, the researchers hypothesize that reversal strategies require frequent trading and rebalancing in disproportionately high-cost securities, and this would lead to a situation where trading costs prevent profitable strategy execution.

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We aim to advance the understanding of what is driving short-term reversal profits in the сontext of these competing (but not mutually exclusive) hypotheses. If reversal comes from initial price overreaction to information, to what type of information is the price overreacting? Is it industry-level news or firm-specific news? Is it news about a firm’s cash flow or its discount rate? If, on the other hand, the reversal observed is due to liquidity shocks, has it remained economically relevant during recent years when market liquidity (by most measures) has improved greatly? Is it relevant even for the larger and more liquid stocks that make up the majority of the US equity universe? In answering these questions we hope to contribute to a better understanding of the short-term return reversal phenomenon. The framework for our analysis is a novel analytical decomposition of the short-term reversal profits. The reversal profit is first decomposed into an across-industry component and a withinindustry component. The across-industry component measures the profit to an across-industry reversal strategy that buys loser industries and sells winner industries; the within-industry component measures the profit to a within-industry reversal strategy that buys losers and sells winners within each industry.

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The cross section of individual stock returns over the coming week or month is strongly negatively related to the past returns of the same firms over the past week or month (Lehmann 1990, Jegadeesh 1990). This negative serial correlation is generally interpreted as evidence consistent with incomplete liquidity provision, and much empirical evidence is consistent with this: Chan (2003) and Tetlock (2011) show that large stock price moves exhibit more reversal if they are not associated with news. The evidence of Da, Liu, and Schaumburg (2013) suggests that industry returns exhibit weaker reversals than firmspecific reversals. In addition, Avramov, Chordia, and Goyal (2006) argue that the reversal effect is present only in small, illiquid stocks with high turnover, and Khandani and Lo (2007) document a dramatic decline over time in the efficacy of the strategy. Finally, the strength of the reversal strategy appears to depend on arbitrageurs ability to access capital: Nagel (2012) documents a strong positive correlation between the return of a short-term-reversal and the level of the VIX. He argues that this covariation is consistent with the “... withdrawal of liquidity supply and an associated increase in the expected returns from liquidity provision .

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For the most part, identifying the causes of short-term return reversal has important implications for empirical asset pricing tests, and more generally for understanding the limits of market efficiency. A simple short-term return reversal trading strategy based on the previous-month within-industry non-cash-flow shock generates a three-factor alpha of 1.34% per month (t-value = 9.28), four times the alpha of the standard short-term reversal strategy.While financial economists have long studied the profitability of a contrarian strategy of buying recent losers and selling recent winners, we have not had a complete understanding of what is driving short-term reversal profits.

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Khandani, Amir E., and Andrew W. Lo, 2007, What Happened To The Quants in August 2007?, Journal of Investment Management 5, 5–54.

King, Robert G., and Sergio T. Rebelo, 1993, Low frequency filtering and business cycles, Journal of Economic Dynamics and Control 17, 207–231.

Lehmann, Bruce N., 1990, Fads, martingales, and market efficiency, Quarterly Journal of Economics 105, 1–28.

Nagel, Stefan, 2012, Evaporating liquidity, Review of Financial Studies 25, 2005–2039.

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