Deep Decoding of Strategies
20 Pages Posted: 16 Jun 2022 Last revised: 5 May 2024
Date Written: June 6, 2022
Abstract
To the best of our knowledge, the application of machine learning and in particular graphical models in the field of quantitative risk management is still a relatively recent and new phenomenon. This paper presents a new and effective methodology for decoding strategies. Given an investment universe, we calculate dynamic weights for a sparse portfolio whose aim is to replicate the strategy with the most stable allocation rules. Naturally, this can be formulated as a reinforcement learning problem whose reward is a weighted sum of tracking error and turnover. We show on stylized examples that we can accurately decode strategies or funds with meaningful factors and allocations.
Keywords: Decoding, risk management
JEL Classification: G12, G13
Suggested Citation: Suggested Citation