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Statistical Arbitrage and Securities Prices

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  • Oleg Bondarenko
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    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.

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    File URL: http://hdl.handle.net/10.1093/rfs/hhg016
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    Bibliographic Info

    Article provided by Society for Financial Studies in its journal The Review of Financial Studies.

    Volume (Year): 16 (2003)
    Issue (Month): 3 (July)
    Pages: 875-919

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    Handle: RePEc:oup:rfinst:v:16:y:2003:i:3:p:875-919

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    Cited by:
    1. Adrian, Tobias, 2009. "Inference, arbitrage, and asset price volatility," Journal of Financial Intermediation, Elsevier, vol. 18(1), pages 49-64, January.
    2. Sun, David & Tsai, Shih-Chuan & Wang, Wei, 2011. "Behavioral investment strategy matters: a statistical arbitrage approach," MPRA Paper 37281, University Library of Munich, Germany, revised 16 Jan 2012.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Ivanov, Sergei, 2013. "Interest rate paradox," MPRA Paper 47723, University Library of Munich, Germany.
    8. 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.
    9. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "ETF arbitrage: Intraday evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3486-3498.

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