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Dead Alphas as Risk Factors

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  • Zura Kakushadze
  • Willie Yu

Abstract

We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. "flatlined" or "hockey-stick") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which there is no money to be made (and/or those bets are too volatile). In practice the number of dead alphas can be large compared with the number of underlying stocks and care is required in identifying the aforesaid directions.

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  • Zura Kakushadze & Willie Yu, 2017. "Dead Alphas as Risk Factors," Papers 1709.06641, arXiv.org.
    • Handle: RePEc:arx:papers:1709.06641
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Zura Kakushadze & Willie Yu, 2017. "Decoding Stock Market with Quant Alphas," Papers 1708.02984, arXiv.org.
    3. Zura Kakushadze, 2016. "101 Formulaic Alphas," Papers 1601.00991, arXiv.org, revised Mar 2016.
    4. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    5. Zura Kakushadze, 2015. "Heterotic Risk Models," Papers 1508.04883, arXiv.org, revised Jan 2016.
    6. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.
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