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The Capacity of Trading Strategies

Author

Listed:
  • Augustin Landier

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique)

  • Guillaume Simon

    (UT2J - Université Toulouse - Jean Jaurès - UT - Université de Toulouse)

  • David Thesmar

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

Abstract

Due to non-linear transaction costs, the fi nancial performance of a trading strategy decreases with portfolio size. Using a dynamic trading model a la Garleanu and Pedersen (2013), we derive closed-form formulas for the performance-to-scale frontier reached by competitive traders endowed with a signal predicting stock returns. The decay with scale of the realized Sharpe ratio is slower for strategies that (1) trade more liquid stocks (2) are based on signals that do not fade away quickly and (3) have strong frictionless performance. We apply the framework to four well-known strategies. The capacity of strategies has increased in the 2000s compared to the 1990s due to increased liquidity. Because low volatility and past accounting profi tability are persistent characteristics, strategies based on them are highly scalable, including in the mid-cap range. When traders underestimate the number of competitors trading a similar signal, their performance is strongly negatively impacted.

Suggested Citation

  • Augustin Landier & Guillaume Simon & David Thesmar, 2015. "The Capacity of Trading Strategies," Working Papers hal-02011394, HAL.
    • Handle: RePEc:hal:wpaper:hal-02011394
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    Cited by:

    1. Itzhak Ben-DAVID & Francesco A. FRANZONI & Rabih MOUSSAWI & John SEDUNOV III, 2015. "The Granular Nature of Large Institutional Investors," Swiss Finance Institute Research Paper Series 15-67, Swiss Finance Institute, revised Apr 2016.
    2. Jean‐Philippe Bouchaud & Philipp Krüger & Augustin Landier & David Thesmar, 2019. "Sticky Expectations and the Profitability Anomaly," Journal of Finance, American Finance Association, vol. 74(2), pages 639-674, April.
    3. Albert J. Menkveld & Bart Zhou Yueshen, 2019. "The Flash Crash: A Cautionary Tale About Highly Fragmented Markets," Management Science, INFORMS, vol. 65(10), pages 4470-4488, October.
    4. Jean-Philippe Bouchaud & Stefano Ciliberti & Augustin Landier & Guillaume Simon & David Thesmar, 2016. "The Excess Returns of "Quality" Stocks: A Behavioral Anomaly," Papers 1601.04478, arXiv.org.
    5. Michael J. O'Neill & Geoffrey J. Warren, 2019. "Evaluating fund capacity: issues and methods," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(S1), pages 773-800, April.

    More about this item

    Keywords

    trading costs; asset pricing anomalies; asset management; arbitrage;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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