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Statistical Arbitrage and Securities Prices

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  • Oleg Bondarenko

Abstract

This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizon economy, a SAO is a zero-cost trading strategy for which (i) the expected payoff is positive, and (ii) the conditional expected payoff in each final state of the economy is nonnegative. Unlike a pure arbitrage opportunity, a SAO can have negative payoffs provided that the average payoff in each final state is nonnegative. If the pricing kernel in the economy is path independent, then no SAOs can exist. Furthermore, ruling out SAOs imposes a novel martingale-type restriction on the dynamics of securities prices. The important properties of the restriction are that it (1) is model-free, in the sense that it requires no parametric assumptions about the true equilibrium model, (2) can be tested in samples affected by selection biases, such as the peso problem, and (3) continues to hold when investors' beliefs are mistaken. The article argues that one can use the new restriction to empirically resolve the joint hypothesis problem present in the traditional tests of the efficient market hypothesis. Copyright 2003, Oxford University Press.

Suggested Citation

  • Oleg Bondarenko, 2003. "Statistical Arbitrage and Securities Prices," Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 875-919, July.
  • Handle: RePEc:oup:rfinst:v:16:y:2003:i:3:p:875-919
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    File URL: http://hdl.handle.net/10.1093/rfs/hhg016
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    References listed on IDEAS

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    1. Michael Ewens & Matthew Rhodes-Kropf, 2015. "Is a VC Partnership Greater Than the Sum of Its Partners?," Journal of Finance, American Finance Association, vol. 70(3), pages 1081-1113, June.
    2. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, pages 181-211.
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    Cited by:

    1. David S. Sun & Shih-Chuan Tsai & Wei Wang, 2013. "Behavioral Investment Strategy Matters: A Statistical Arbitrage Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S3), pages 47-61, July.
    2. Adrian, Tobias, 2009. "Inference, arbitrage, and asset price volatility," Journal of Financial Intermediation, Elsevier, vol. 18(1), pages 49-64, January.
    3. Ahmet Göncü, 2015. "Statistical arbitrage in the Black-Scholes framework," Quantitative Finance, Taylor & Francis Journals, pages 1489-1499.
    4. Schneider, Paul, 2015. "Generalized risk premia," Journal of Financial Economics, Elsevier, vol. 116(3), pages 487-504.
    5. repec:wsi:afexxx:v:12:y:2017:i:01:n:s201049521750004x is not listed on IDEAS
    6. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
    7. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2017. "Searching for Inefficiencies in Exchange Rate Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 405-432, March.
    8. Han, Bin, 2004. "Limits of Arbitrage, Sentiment and Pricing Kernal: Evidences from Index Options," Working Paper Series 2004-2, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    9. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
    10. Ivanov, Sergei, 2013. "Interest rate paradox," MPRA Paper 47723, University Library of Munich, Germany.
    11. Liu, Jun & Timmermann, Allan G, 2009. "Risky Arbitrage Strategies: Optimal Portfolio Choice and Economic Implications," CEPR Discussion Papers 7188, C.E.P.R. Discussion Papers.
    12. Matos, Joao Amaro de & Lacerda, Ana, 2006. "Dry Markets and Statistical Arbitrage Bounds for European Derivatives," FEUNL Working Paper Series wp479, Universidade Nova de Lisboa, Faculdade de Economia.
    13. Fajardo, José & Lacerda, Ana, 2010. "Statistical arbitrage with default and collateral," Economics Letters, Elsevier, vol. 108(1), pages 81-84, July.
    14. Ahmet Göncü, 2015. "Statistical arbitrage in the Black-Scholes framework," Quantitative Finance, Taylor & Francis Journals, pages 1489-1499.
    15. Alexakis, Christos, 2010. "Long-run relations among equity indices under different market conditions: Implications on the implementation of statistical arbitrage strategies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(4), pages 389-403, October.
    16. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "ETF arbitrage: Intraday evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3486-3498.
    17. Tu, Anthony H. & Hsieh, Wen-Liang G. & Wu, Wei-Shao, 2016. "Market uncertainty, expected volatility and the mispricing of S&P 500 index futures," Journal of Empirical Finance, Elsevier, pages 78-98.
    18. Matos, Joao Amaro de & Lacerda, Ana, 2004. "Dry Markets and Superreplication Bounds of American Derivatives," FEUNL Working Paper Series wp461, Universidade Nova de Lisboa, Faculdade de Economia.

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