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Statistical arbitrage: Factor investing approach

Author

Listed:
  • Akyildirim, Erdinc
  • Goncu, Ahmet
  • Hekimoglu, Alper
  • Nguyen, Duc Khuong
  • Sensoy, Ahmet

Abstract

We introduce a continuous time model for stock prices in a general factor representation with the noise driven by a geometric Brownian motion process. We derive the theoretical hitting probability distribution for the long-until-barrier strategies and the conditions for statistical arbitrage. We optimize our statistical arbitrage strategies with respect to the expected discounted returns and the Sharpe ratio. Bootstrapping results show that the theoretical hitting probability distribution is a realistic representation of the empirical hitting probabilities. We test the empirical performance of the long-until-barrier strategies using US equities and demonstrate that our trading rules can generate statistical arbitrage profits.

Suggested Citation

  • Akyildirim, Erdinc & Goncu, Ahmet & Hekimoglu, Alper & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Statistical arbitrage: Factor investing approach," MPRA Paper 105766, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:105766
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Statistical arbitrage; factor models; trading strategies; geometric Brownian motion; Monte Carlo simulation.;
    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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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