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Constant Rebalanced Portfolio Optimization Under Nonlinear Transaction Costs

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Abstract

We study the constant rebalancing strategy for multi-period portfolio optimization via conditional value-at-risk (CVaR) when there are nonlinear transaction costs. This problem is difficult to solve because of its nonconvexity. The nonlinear transaction costs and CVaR constraints make things worse; state-of-the-art nonlinear programming (NLP) solvers have trouble in reaching even locally optimal solutions. As a practical solution, we develop a local search algorithm in which linear approximation problems and nonlinear equations are iteratively solved. Computational results are presented, showing that the algorithm attains a good solution in a practical time. It is better than the revised version of an existing global optimization. We also assess the performance of the constant rebalancing strategy in comparison with the buy-and-hold strategy.

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Authors and Affiliations

  1. Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba-shi, 305–8573, Ibaraki, Japan

    Yuichi Takano

  2. Department of Industrial and Systems Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, 112-8551, Tokyo, Japan

    Jun-ya Gotoh

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  1. Yuichi Takano
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  2. Jun-ya Gotoh
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Correspondence to Jun-ya Gotoh.

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Takano, Y., Gotoh, Jy. Constant Rebalanced Portfolio Optimization Under Nonlinear Transaction Costs. Asia-Pac Financ Markets 18, 191–211 (2011). https://doi.org/10.1007/s10690-010-9130-4

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