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On Data-Driven Log-Optimal Portfolio: A Sliding Window Approach (2206.12148v1)
Published 24 Jun 2022 in q-fin.PM, cs.SY, eess.SY, math.OC, and q-fin.CP
Abstract: In this paper, we propose a data-driven sliding window approach to solve a log-optimal portfolio problem. In contrast to many of the existing papers, this approach leads to a trading strategy with time-varying portfolio weights rather than fixed constant weights. We show, by conducting various empirical studies, that the approach possesses a superior trading performance to the classical log-optimal portfolio in the sense of having a higher cumulative rate of returns.