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The Capacity of Trading Strategies

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  • Thesmar , David
  • Landier , Augustin

Abstract

Due to non-linear transaction costs, the financial performance of a trading strategy decreases with portfolio size. Using a dynamic trading model a la Garleanu and Pedersen (2013), the authors derive closed-form formulas for the performance-to-scale frontier reached by a trader 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. For an investor ready to accept a Sharpe reduction by 30%, portfolio scale (measured in dollar volatility) is given by a simple formula that is a function of the frictionless Sharpe, a measure of price impact, and a measure of the speed at which the signal fades away. They apply the framework to four well-known strategies. Because stocks have become more liquid, the capacity of strategies has increased in the 2000s compared to the 1990s. Due to high signal persistence, the capacity of a "quality" strategy is an order of magnitude larger than the others and is the only one highly scalable in the mid-cap range.

Suggested Citation

  • Thesmar , David & Landier , Augustin, 2015. "The Capacity of Trading Strategies," HEC Research Papers Series 1089, HEC Paris.
    • Handle: RePEc:ebg:heccah:1089
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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. Thesmar , David & Bouchaud , Jean-Philippe & Stefano , Ciliberti & Landier , Augustin & Simon , Guillaume, 2016. "The Excess Returns of 'Quality' Stocks: A Behavioral Anomaly," HEC Research Papers Series 1134, HEC Paris.
    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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