Robust Optimization-Based Commodity Portfolio Performance

Ramesh Adhikari, Kyle J. Putnam and Humnath Panta
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Ramesh Adhikari: School of Business, Humboldt State University, Arcata, CA 95521, USA
Kyle J. Putnam: School of Business, Linfield University, McMinnville, OR 97128, USA
Humnath Panta: School of Business, Humboldt State University, Arcata, CA 95521, USA

IJFS, 2020, vol. 8, issue 3, 1-16

Abstract: This paper examines the performance of a naïve equally weighted buy-and-hold portfolio and optimization-based commodity futures portfolios for various lookback and holding periods using data from January 1986 to December 2018. The application of Monte Carlo simulation-based mean-variance and conditional value-at-risk optimization techniques are used to construct the robust commodity futures portfolios. This paper documents the benefits of applying a sophisticated, robust optimization technique to construct commodity futures portfolios. We find that a 12-month lookback period contains the most useful information in constructing optimization-based portfolios, and a 1-month holding period yields the highest returns among all the holding periods examined in the paper. We also find that an optimized conditional value-at-risk portfolio using a 12-month lookback period outperforms an optimized mean-variance portfolio using the same lookback period. Our findings highlight the advantages of using robust optimization for portfolio formation in the presence of return uncertainty in the commodity futures markets. The results also highlight the practical importance of choosing the appropriate lookback and holding period when using robust optimization in the commodity portfolio formation process.

Keywords: commodities; commodity futures; portfolio optimization (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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