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Anomalies as New Hedge Fund Factors

Published online by Cambridge University Press:  10 October 2025

Yong Chen ,
Sophia Zhengzi Li ,
Yushan Tang  and
Guofu Zhou Open the ORCID record for Guofu Zhou [Opens in a new window]
Yong Chen
Affiliation:
Texas A&M University Mays Business School ychen@mays.tamu.edu
Sophia Zhengzi Li
Affiliation:
Rutgers University Rutgers Business School, Department of Finance and Economics zhengzi.li@business.rutgers.edu
Yushan Tang
Affiliation:
Shanghai University of Finance and Economics Dishui Lake Advanced Finance Institute tangyushan@sufe.edu.cn
Guofu Zhou*
Affiliation:
Washington University in St. Louis Olin Business School
*
zhou@wustl.edu (corresponding author)
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Abstract

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We identify a parsimonious set of factors from a large pool of candidates for explaining hedge fund returns, ranging from equity market, anomaly, and trend-following factors to macroeconomic factors. The resulting 9-factor model, including five anomaly factors, outperforms existing hedge fund models both in sample and out of sample, with a significant reduction in alphas while showing substantial cross sectional performance heterogeneity. Further analysis based on fund holdings confirms the model’s ability to capture returns from arbitrage trading. Overall, the anomaly factors help quantify hedge fund strategies and risk exposures and improve fund performance evaluation.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 34
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We are extremely grateful to Hendrik Bessembinder (the editor) and two anonymous referees for their detailed and insightful comments that have substantially improved the article. We thank Vikas Agarwal, Tim Bollerslev, Oleg Bondarenko, Charles Cao, Gregory Eaton, Amit Goyal, Clifton Green, Bing Liang, Alan Moreira, Sugata Ray, Andrea Rossi, Zhen Shi, seminar and conference participants at Aalto University, Texas A&M University, the 16th Annual Hedge Fund Research Conference, and the XJTLU AI and Big Data in Accounting and Finance Research Conference for helpful comments and suggestions. We also thank Vikas Agarwal, Turan Bali, Ken French, Amit Goyal, David Hsieh, Ralph Koijen, Lubos Pastor, and Grigory Vilkov for making a large amount of data available through their websites or direct sharing.

References

Agarwal, V.; Daniel, N. D.; and Naik, N. Y.. “Role of Managerial Incentives and Discretion in Hedge Fund Performance.” Journal of Finance, 64 (2009), 2221–2256.CrossRefGoogle Scholar
Agarwal, V.; Fos, V.; and Jiang, W.. “Inferring Reporting-Related Biases in Hedge Fund Databases from Hedge Fund Equity Holdings.” Management Science, 59 (2013), 1271–1289.CrossRefGoogle Scholar
Agarwal, V.; Green, T. C.; and Ren, H.. “Alpha or Beta in the Eye of the Beholder: What Drives Hedge Fund Flows.” Journal of Financial Economics, 127 (2018), 417–434.10.1016/j.jfineco.2018.01.006CrossRefGoogle Scholar
Agarwal, V., and Naik, N. Y.. “Risks and Portfolio Decisions Involving Hedge Funds.” Review of Financial Studies, 17 (2004), 63–98.10.1093/rfs/hhg044CrossRefGoogle Scholar
Aggarwal, R. K., and Jorion, P.. “The Performance of Emerging Hedge Funds and Managers.” Journal of Financial Economics, 96 (2010), 238–256.10.1016/j.jfineco.2009.12.010CrossRefGoogle Scholar
Ardia, D.; Barras, L.; Gagliardini, P.; and Scaillet, O.. “Is It Alpha or Beta? Decomposing Hedge Fund Returns When Models Are Misspecified.” Journal of Financial Economics, 154 (2023), 103805.10.1016/j.jfineco.2024.103805CrossRefGoogle Scholar
Avramov, D.; Kosowski, R.; Naik, N. Y.; and Teo, M.. “Hedge Funds, Managerial Skill, and Macroeconomic Variables.” Journal of Financial Economics, 99 (2011), 672–692.10.1016/j.jfineco.2010.10.003CrossRefGoogle Scholar
Bali, T. G.; Brown, S. J.; and Caglayan, M. O.. “Do Hedge Funds’ Exposures to Risk Factors Predict Their Future Returns.” Journal of Financial Economics, 101 (2011), 36–68.10.1016/j.jfineco.2011.02.008CrossRefGoogle Scholar
Bali, T. G.; Brown, S. J.; and Caglayan, M. O.. “Systematic Risk and the Cross-Section of Hedge Fund Returns.” Journal of Financial Economics, 106 (2012), 114–131.CrossRefGoogle Scholar
Bali, T. G.; Brown, S. J.; and Caglayan, M. O.. “Macroeconomic Risk and Hedge Fund Returns.” Journal of Financial Economics, 114 (2014), 1–19.CrossRefGoogle Scholar
Barras, L.; Gagliardini, P.; and Scaillet, O.. “Skill, Scale, and Value Creation in the Mutual Fund Industry.” Journal of Finance, 77 (2022), 601–638.CrossRefGoogle Scholar
Barras, L.; Scaillet, O.; and Wermers, R.. “False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas.” Journal of Finance, 65 (2010), 179–216.10.1111/j.1540-6261.2009.01527.xCrossRefGoogle Scholar
Belloni, A.; Chen, D.; Chernozhukov, V.; and Hansen, C.. “Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain.” Econometrica, 80 (2012), 2369—2429.Google Scholar
Belloni, A., and Chernozhukov, V.. “Least Squares after Model Selection in High-Dimensional Sparse Models.” Bernoulli, 19 (2013), 521–547.CrossRefGoogle Scholar
Brown, S. J.; Goetzmann, W.; Ibbotson, R. G.; and Ross, S. A.. “Survivorship Bias in Performance Studies.” Review of Financial Studies, 5 (1992), 553–580.10.1093/rfs/5.4.553CrossRefGoogle Scholar
Buraschi, A.; Kosowski, R.; and Trojani, F.. “When There Is No Place to Hide: Correlation Risk and the Cross-Section of Hedge Fund Returns.” Review of Financial Studies, 27 (2014), 581—616.10.1093/rfs/hht070CrossRefGoogle Scholar
Cao, C.; Chen, Y.; Goetzmann, W. N.; and Liang, B.. “Hedge Funds and Stock Price Formation.” Financial Analysts Journal, 74 (2018), 54–68.10.2469/faj.v74.n3.4CrossRefGoogle Scholar
Cao, C.; Chen, Y.; Liang, B.; and Lo, A. W.. “Can Hedge Funds Time Market Liquidity?” Journal of Financial Economics, 109 (2013), 492–516.10.1016/j.jfineco.2013.03.009CrossRefGoogle Scholar
Chen, A. Y., and Zimmermann, T.. “Open Source Cross-Sectional Asset Pricing.” Critical Finance Review, 11 (2022), 207–264.CrossRefGoogle Scholar
Chen, Y. “Timing Ability in the Focus Market of Hedge Funds.” Journal of Investment Management, 5 (2007), 66–98.Google Scholar
Chen, Y. “Derivatives Use and Risk Taking: Evidence from the Hedge Fund Industry.” Journal of Financial and Quantitative analysis, 46 (2011), 1073–1106.CrossRefGoogle Scholar
Chen, Y.; Cliff, M.; and Zhao, H.. “Hedge Funds: The Good, the Bad, and the Lucky.” Journal of Financial and Quantitative Analysis, 52 (2017), 1081–1109.CrossRefGoogle Scholar
Chen, Y.; Da, Z.; and Huang, D.. “Arbitrage Trading: The Long and the Short of It.” Review of Financial Studies, 32 (2019), 1608–1646.CrossRefGoogle Scholar
Chen, Y.; Han, B.; and Pan, J.. “Sentiment Trading and Hedge Fund Returns.” Journal of Finance, 76 (2021), 2001–2033.CrossRefGoogle Scholar
Chen, Y.; Kelly, B.; and Wu, W.. “Sophisticated Investors and Market Efficiency: Evidence from a Natural Experiment.” Journal of Financial Economics, 138 (2020), 316–341.CrossRefGoogle Scholar
Chen, Y., and Liang, B.. “Do Market Timing Hedge Funds Time the Market?” Journal of Financial and Quantitative Analysis, 42 (2007), 827–856.10.1017/S0022109000003410CrossRefGoogle Scholar
Cochrane, J. H. “Presidential Address: Discount Rates.” Journal of Finance, 66 (2011), 1047–1108.10.1111/j.1540-6261.2011.01671.xCrossRefGoogle Scholar
Diebold, F. X., and Mariano, R. S.. “Comparing Predictive Accuracy.” Journal of Business and Economic Statistics, 13 (1995), 253–263.CrossRefGoogle Scholar
Fama, E. F., and French, K. R.. “A Five-factor Asset Pricing Model.” Journal of Financial Economics, 116 (2015), 1–22.10.1016/j.jfineco.2014.10.010CrossRefGoogle Scholar
Fan, J., and Li, R.. “Variable Selection via Nonconcave Penalized Likelihood and Its Oracle Properties.” Journal of the American Statistical Association, 96 (2001), 1348–1360.CrossRefGoogle Scholar
Fung, W., and Hsieh, D. A.. “Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds.” Review of Financial Studies, 10 (1997), 275–302.CrossRefGoogle Scholar
Fung, W., and Hsieh, D. A.. “Performance Characteristics of Hedge Funds and Commodity Funds: Natural vs. Spurious Biases.” Journal of Financial and Quantitative Analysis, 35 (2000), 291–307.10.2307/2676205CrossRefGoogle Scholar
Fung, W., and Hsieh, D. A.. “The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers.” Review of Financial Studies, 14 (2001), 313–341.10.1093/rfs/14.2.313CrossRefGoogle Scholar
Fung, W., and Hsieh, D. A.. “Hedge Fund Benchmarks: A Risk-Based Approach.” Financial Analysts Journal, 60 (2004), 65–80.CrossRefGoogle Scholar
Getmansky, M.; Lo, A. W.; and Makarov, I.. “An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns.” Journal of Financial Economics, 74 (2004), 529–609.10.1016/j.jfineco.2004.04.001CrossRefGoogle Scholar
Gibbons, M. R.; Ross, S. A.; and Shanken, J.. “A Test of the Efficiency of a Given Portfolio.” Econometrica, 57 (1989), 1121–1152.10.2307/1913625CrossRefGoogle Scholar
Gromb, D., and Vayanos, D.. “Limits of Arbitrage.” Annual Review of Financial Economics, 2 (2010), 251–275.CrossRefGoogle Scholar
Harvey, C. R., and Liu, Y.. “Lucky Factors.” Journal of Financial Economics, 141 (2021), 413–435.10.1016/j.jfineco.2021.04.014CrossRefGoogle Scholar
Jensen, T. I.; Kelly, B.; and Pedersen, L. H.. “Is There a Replication Crisis in Finance?” Journal of Finance, 78 (2023), 2465–2518.CrossRefGoogle Scholar
Kelly, B., and Xiu, D.. “Financial Machine Learning.” Foundations and Trends in Finance, 13 (2023), 205–363.CrossRefGoogle Scholar
Koijen, R. S.; Moskowitz, T. J.; Pedersen, L. H.; and Vrugt, E. B.. “Carry.” Journal of Financial Economics, 127 (2018), 197–225.CrossRefGoogle Scholar
Kosowski, R.; Naik, N. Y.; and Teo, M.. “Do Hedge Funds Deliver Alpha? A Bayesian and Bootstrap Analysis.” Journal of Financial Economics, 84 (2007), 229–264.CrossRefGoogle Scholar
Lewellen, J.; Nagel, S.; and Shanken, J.. “A Skeptical Appraisal of Asset Pricing Tests.” Journal of Financial Economics, 96 (2010), 175–194.10.1016/j.jfineco.2009.09.001CrossRefGoogle Scholar
Liang, B. “Hedge Funds: The Living and the Dead.” Journal of Financial and Quantitative Analysis, 35 (2000), 309—326.CrossRefGoogle Scholar
Moskowitz, T. J.; Ooi, Y. H.; and Pedersen, L. H.. “Time Series Momentum.” Journal of Financial Economics, 104 (2012), 228–250.CrossRefGoogle Scholar
Newey, W., and West, K.. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55 (1987), 703–708.10.2307/1913610CrossRefGoogle Scholar
Pastor, L., and Stambaugh, R. F.. “Liquidity Risk and Expected Stock Returns.” Journal of Political Economy, 111 (2003), 642–685.CrossRefGoogle Scholar
Pedersen, L. H. Efficiently Inefficient. Princeton, NJ: Princeton University Press (2015).Google Scholar
Rapach, D. E.; Strauss, J. K.; and Zhou, G.. “International Stock Return Predictability: What Is the Role of the United States?” Journal of Finance, 68 (2013), 1633–1662.10.1111/jofi.12041CrossRefGoogle Scholar
Ross, S. A. “The Arbitrage Theory of Capital Asset Pricing.” Journal of Economic Theory, 13 (1976), 341–360.10.1016/0022-0531(76)90046-6CrossRefGoogle Scholar
Sadka, R. “Liquidity Risk and the Cross-Section of Hedge Fund Returns.” Journal of Financial Economics, 98 (2010), 54–71.10.1016/j.jfineco.2010.05.001CrossRefGoogle Scholar
Shleifer, A., and Vishny, R. W.. “The Limits of Arbitrage.” Journal of Finance, 52 (1997), 35–55.10.1111/j.1540-6261.1997.tb03807.xCrossRefGoogle Scholar
Stambaugh, R. F.; Yu, J.; and Yuan, Y.. “The Short of It: Investor Sentiment and Anomalies.” Journal of Financial Economics, 104 (2012), 288–302.CrossRefGoogle Scholar
Teo, M. “The Geography of Hedge Funds.” Review of Financial Studies, 22 (2009), 3531–3561.CrossRefGoogle Scholar
Teo, M. “The Liquidity Risk of Liquid Hedge Funds.” Journal of Financial Economics, 100 (2011), 24–44.10.1016/j.jfineco.2010.11.003CrossRefGoogle Scholar
Tibshirani, R. “Regression Shrinkage and Selection via the LASSO.” Journal of the Royal Statistical Society: Series B (Statistical Methodology), 58 (1996), 267—288.10.1111/j.2517-6161.1996.tb02080.xCrossRefGoogle Scholar
Titman, S., and Tiu, C.. “Do the Best Hedge Funds Hedge?” Review of Financial Studies, 24 (2011), 123–168.10.1093/rfs/hhq105CrossRefGoogle Scholar
Welch, I., and Goyal, A.. “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction.” Review of Financial Studies, 21 (2008), 1455–1508.10.1093/rfs/hhm014CrossRefGoogle Scholar
Zou, H. “The Adaptive Lasso and Its Oracle Properties.” Journal of the American Statistical Association, 101 (2006), 1418–1429.10.1198/016214506000000735CrossRefGoogle Scholar
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