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Optimal Trading with Alpha Predictors

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  • Filippo Passerini
  • Samuel E. Vazquez

Abstract

We study the problem of optimal trading using general alpha predictors with linear costs and temporary impact. We do this within the framework of stochastic optimization with finite horizon using both limit and market orders. Consistently with other studies, we find that the presence of linear costs induces a no-trading zone when using market orders, and a corresponding market-making zone when using limit orders. We show that, when combining both market and limit orders, the problem is further divided into zones in which we trade more aggressively using market orders. Even though we do not solve analytically the full optimization problem, we present explicit and simple analytical recipes which approximate the full solution and are easy to implement in practice. We test the algorithms using Monte Carlo simulations and show how they improve our Profit and Losses.

Suggested Citation

  • Filippo Passerini & Samuel E. Vazquez, 2015. "Optimal Trading with Alpha Predictors," Papers 1501.03756, arXiv.org, revised Jan 2015.
    • Handle: RePEc:arx:papers:1501.03756
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    References listed on IDEAS

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    Cited by:

    1. Erhan Bayraktar & Alexander Munk, 2017. "Mini-Flash Crashes, Model Risk, and Optimal Execution," Papers 1705.09827, arXiv.org, revised Aug 2018.

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