Decoding Stock Market with Quant Alphas

Zura Kakushadze and Willie Yu

Papers from arXiv.org

Abstract: We give an explicit algorithm and source code for extracting expected returns for stocks from expected returns for alphas. Our algorithm altogether bypasses combining alphas with weights into "alpha combos". Simply put, we have developed a new method for trading alphas which does not involve combining them. This yields substantial cost savings as alpha combos cost hedge funds around 3% of the P&L, while alphas themselves cost around 10%. Also, the extra layer of alpha combos, which our new method avoids, adds noise and suboptimality. We also arrive at our algorithm independently by explicitly constructing alpha risk models based on position data.

Date: 2017-08
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Published in Journal of Asset Management 19(1) (2018) 38-48

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