Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization

Kasper Johansson, Thomas Schmelzer and Stephen Boyd

Papers from arXiv.org

Abstract: We propose a new method for finding statistical arbitrages that can contain more assets than just the traditional pair. We formulate the problem as seeking a portfolio with the highest volatility, subject to its price remaining in a band and a leverage limit. This optimization problem is not convex, but can be approximately solved using the convex-concave procedure, a specific sequential convex programming method. We show how the method generalizes to finding moving-band statistical arbitrages, where the price band midpoint varies over time.

Date: 2024-02
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