Hostname: page-component-594f858ff7-hd6rl Total loading time: 0 Render date: 2023-06-08T09:48:49.629Z Has data issue: false Feature Flags: { "corePageComponentGetUserInfoFromSharedSession": true, "coreDisableEcommerce": false, "corePageComponentUseShareaholicInsteadOfAddThis": true, "coreDisableSocialShare": false, "useRatesEcommerce": true } hasContentIssue false

Anomaly Discovery and Arbitrage Trading

Published online by Cambridge University Press:  20 February 2023

Xi Dong
Affiliation:
City University of New York Baruch College xi.dong@baruch.cuny.edu
Qi Liu*
Affiliation:
Peking University Guanghua School of Management
Lei Lu
Affiliation:
University of Manitoba Asper School of Business lei.lu@umanitoba.ca
Bo Sun
Affiliation:
University of Virginia Darden School of Business sunb@darden.virginia.edu
Hongjun Yan
Affiliation:
DePaul University Driehaus College of Business hongjun.yan.2011@gmail.com
*
qiliu@gsm.pku.edu.cn (corresponding author)

Abstract

We analyze a model in which an anomaly is unknown to arbitrageurs until its discovery, and test the model implications on both asset prices and arbitrageurs’ trading activities. Using data on 99 anomalies documented in the existing literature, we find that the discovery of an anomaly reduces the correlation between the returns of its decile-1 and decile-10 portfolios. This discovery effect is stronger if the aggregate wealth of hedge funds is more volatile. Finally, hedge funds increase (reverse) their positions in exploiting anomalies when their aggregate wealth increases (decreases), further suggesting that these discovery effects operate through arbitrage trading.

Type
Research Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We thank Thummim Cho (the referee) and Jennifer Conrad (the editor) for their constructive comments. We also thank Nick Barberis, Bruno Biais, Alon Brav, David Brown, Bjorn Eraker, Will Goetzmann, Michael Gofman, Paul Goldsmith-Pinkham, David Hirshleifer, Jon Ingersoll, Wenxi Jiang, Marcin Kacperczyk, Andrew Karolyi, Leonid Kogan, Andrew Lo, Benjamin Loos, Steve Malliaris, David McLean, Alan Moreira, Justin Murfin, Lubos Pastor, Anna Pavlova, Jeff Pontiff, Mark Ready, Jialin Yu, Jianfeng Yu, and seminar participants at Boston University, DePaul University, Georgetown University, HKUST, Johns Hopkins University, PBCSF Tsinghua University, Peking University, Rutgers, SAIF, Temple University, SEM Tsinghua University, University of Florida, University of Toronto, University of Virginia, University of Wisconsin Madison, Yale, the 2019 American Economic Association Meetings (AEA), the 2016 European Finance Association Meetings (EFA), the 2016 European Summer Symposium in Financial Markets, the 2015 China International Conference in Finance (CICF), and the 2015 Northern Finance Association Meetings (NFA) for helpful discussions. Lu is grateful for financial support provided by Bryce Douglas Chair in Corporate Finance. An earlier version of this article was circulated under the title “A Model of Anomaly Discovery.”

References

Adrian, T.; Moench, E.; and Shin, H. S.. “Financial Intermediation, Asset Prices, and Macroeconomic Dynamics.” Staff Report, 422 (2010).Google Scholar
Agarwal, V.; Jiang, W.; Tang, Y.; and Yang, B.. “Uncovering Hedge Fund Skill from the Portfolio Holdings They Hide.” Journal of Finance, 68 (2013), 739783.CrossRefGoogle Scholar
Ali, A.; Chen, X.; Yao, T.; and Yu, T.. “Do Mutual Funds Profit from the Accruals Anomaly?Journal of Accounting Research, 46 (2008), 126.CrossRefGoogle Scholar
Ang, A.; Hodrick, R. J.; Xing, Y.; and Zhang, X.. “The Cross-Section of Volatility and Expected Returns.” Journal of Finance, 61 (2006), 259299.CrossRefGoogle Scholar
Basu, S.The Relationship Between Earnings’ Yield, Market Value and Return for NYSE Common Stocks: Further Evidence.” Journal of Financial Economics, 12 (1983), 129156.CrossRefGoogle Scholar
Brunnermeier, M., and Pedersen, L.. “Market Liquidity and Funding Liquidity.” Review of Financial Studies, 22 (2009), 22012238.CrossRefGoogle Scholar
Calluzzo, P.; Moneta, F.; and Topaloglu, S.. “When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?Management Science, 65 (2019), 45554574.CrossRefGoogle Scholar
Chen, Y.; Da, Z.; and Huang, D.. “Arbitrage Trading: The Long and the Short of It.” Review of Financial Studies, 32 (2019), 16081646.Google Scholar
Cho, T.Turning Alphas into Betas: Arbitrage and Endogeneous Risk.” Journal of Financial Economics, 137 (2020), 550570.CrossRefGoogle Scholar
DeVault, L.; Sias, R.; and Starks, L.. “Sentiment Metrics and Investor Demand.” Journal of Finance, 74 (2019), 9851024.CrossRefGoogle Scholar
Dong, X.; Feng, S.; and Sadka, R.. “Liquidity Risk and Mutual Fund Performance.” Management Science, 65 (2019), 10201041.CrossRefGoogle Scholar
Dong, X., Kang, N., and Peress, J.. “Fast and Slow Arbitrage: Fund Flows and Mispricing in the Frequency Domain.” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3688189 (2020).Google Scholar
Dong, X.; Li, Y.; Rapach, D. E.; and Zhou, G.. “Anomalies and the Expected Market Return.” Journal of Finance, 77 (2022), 639681.Google Scholar
Dow, J., and Gorton, G.. “Arbitrage Chains.” Journal of Finance, 49 (1994), 819849.CrossRefGoogle Scholar
Edelen, R. M.; Ince, O. S.; and Kadlec, G. B.. “Institutional Investors and Stock Return Anomalies.” Journal of Financial Economics, 119 (2016), 472488.CrossRefGoogle Scholar
Engelberg, J.; McLean, R. D.; and Pontiff, J.. “Anomalies and News.” Journal of Finance, 73 (2018), 19712001.CrossRefGoogle Scholar
Feng, G.; Giglio, S.; and Xiu, D.. “Taming the Factor Zoo: A Test of New Factors.” Journal of Finance, 75 (2020), 13271370.CrossRefGoogle Scholar
Fung, W.; Hsieh, D. A.; Naik, N. Y.; and Ramadorai, T.. “Hedge Funds: Performance, Risk, and Capital Formation.” Journal of Finance, 63 (2008), 17771803.CrossRefGoogle Scholar
Green, J.; Hand, J.; and Zhang, X. F.. “The Characteristics that Provide Independent Information About Average U.S. Monthly Stock Returns.” Review of Financial Studies, 30 (2017), 43894436.CrossRefGoogle Scholar
Gromb, D., and Vayanos, D.. “Equilibrium and Welfare in Markets with Financially Constrained Arbitrageurs.” Journal of Financial Economics, 66 (2002), 361407.CrossRefGoogle Scholar
Gu, S.; Kelly, B.; and Xiu, D.. “Empirical Asset Pricing via Machine Learning.” Review of Financial Studies, 33 (2020), 22232273.CrossRefGoogle Scholar
Guo, L.; Li, F. W.; and Wei, K. J.. “Security Analysts and Capital Market Anomalies.” Journal of Financial Economics, 137 (2020), 204230.CrossRefGoogle Scholar
Hanson, S. G., and Sunderam, A.. “The Growth and Limits of Arbitrage: Evidence from Short Interest.” Review of Financial Studies, 27 (2014), 12381286.CrossRefGoogle Scholar
Harvey, C.; Liu, Y.; and Zhu., H.… and the Cross-Section of Expected Returns.” Review of Financial Studies, 29 (2016), 568.CrossRefGoogle Scholar
He, Z., and Krishnamurthy, A.. “Intermediary Asset Pricing.” American Economic Review, 103 (2013), 732770.CrossRefGoogle Scholar
Hou, K.; Xue, C.; and Zhang, L.. “Replicating Anomalies.” Review of Financial Studies, 33 (2020), 20192133.CrossRefGoogle Scholar
Jacobs, H.Market Maturity and Mispricing.” Journal of Financial Economics, 122 (2016), 270287.CrossRefGoogle Scholar
Jacobs, H., and Muller, S.. “Anomalies Across the Globe: Once Public, No Longer Existent?Journal of Financial Economics, 135 (2020), 213230.CrossRefGoogle Scholar
Karolyi, G. A., and Van Nieuwerburgh, S.. “New Methods for the Cross-Section of Returns.” Review of Financial Studies, 33 (2020), 18791890.CrossRefGoogle Scholar
Koijen, R. S., Richmond, R. J., and Yogo, M.. “Which Investors Matter for Equity Valuations and Expected Returns?” NBER No. w27402. (2022).Google Scholar
Kozak, S.; Nagel, S.; and Santosh, S.. “Interpreting Factor Models.” Journal of Finance, 73 (2018), 11831223.CrossRefGoogle Scholar
Kyle, A., and Xiong, W.. “Contagion as a Wealth Effect of Financial Intermediaries.” Journal of Finance, 56 (2001), 14011440.CrossRefGoogle Scholar
Lewellen, J.Institutional Investors and the Limits of Arbitrage.” Journal of Financial Economics, 102 (2011), 6282.CrossRefGoogle Scholar
Liao, G. Y.Credit Migration and Covered Interest Rate Parity.” Journal of Financial Economics, 138 (2020), 504525.CrossRefGoogle Scholar
Lo, A. W., and Wang, J.. “Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory.” Review of Financial Studies, 13 (2000), 257300.CrossRefGoogle Scholar
Lou, D., and Polk, C.. “Comomentum: Inferring Arbitrage Activity from Return Correlations.” Review of Financial Studies, 35 (2022), 32723302.CrossRefGoogle Scholar
McLean, R. D., and Pontiff, J.. “Does Academic Research Destroy Stock Return Predictability?Journal of Finance, 71 (2016), 532.Google Scholar
Pontiff, J.Costly Arbitrage: Evidence from Closed-End Funds.” Quarterly Journal of Economics, 111 (1996), 11351151.Google Scholar
Pontiff, J.Costly Arbitrage and the Myth of Idiosyncratic Risk.” Journal of Accounting and Economics, 42 (2006), 3552.CrossRefGoogle Scholar
Puckett, A., and Yan, S.. “The Interim Trading Skill of Institutional Investors.” Journal of Finance, 66 (2011), 601633.CrossRefGoogle Scholar
Shleifer, A., and Vishny, R.. “The Limits of Arbitrage.” Journal of Finance, 52 (1997), 3555.CrossRefGoogle Scholar
Stambaugh, R.; Yu, J.; and Yuan, Y.. “The Short of It: Investor Sentiment and Anomalies.” Journal of Financial Economics, 104 (2012), 288302.CrossRefGoogle Scholar
Supplementary material: PDF

Dong et al. supplementary material

Online Appendix

Download Dong et al. supplementary material(PDF)
PDF 1 MB