Performance analysis of log-optimal portfolio strategies with transaction costs

Authored by Mihaly Ormos, Andras Urban

Date Published: 2013-10-01

DOI: 10.1080/14697688.2011.570368

Sponsors: No sponsors listed

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Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

In this paper we introduce an empirical approximation of the log-optimal investment strategy that guarantees an almost optimal growth rate of investments. The proposed strategy also considers the effects of portfolio rearrangement costs on growth optimality and recommends a suboptimal portfolio for discrete investment periods. We do not assume any parametric structure for the market process, only a first-order Markov property. The model introduced is based on kernel-based agents' (experts') approximation of the maximum theoretical growth rate with transaction costs. Although the optimal solution is theoretically a complex Bellman programming problem, our suboptimal empirical result appears to be attractive for Dow Jones 30 shares. The paper presents a performance analysis where the return of the empirical log-optimal portfolio is compared with passive portfolio counterparts compiled from similar components using the CAPM, the three-factor model and the four-factor model. The proposed methods, in the presence of transaction costs, provide a significant positive abnormal return compared with the preceding equilibrium models, and is even a survivorship bias-free setup.

Tags

Transaction costs Agent based modelling Performance evaluation Learning in financial models Multi-factor models Portfolio optimization