Fuertes, Ana-Maria and Zhao, Nan (2022): A Bayesian Perspective on Commodity Style Integration. Published in: Journal of Commodity Markets No. 30 (February 2023)
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Abstract
Commodity style integration is appealing because by forming a unique long-short portfolio with exposure to K mildly correlated factors, a larger and more stable risk premium can be extracted than with any of the standalone styles. A key decision that a commodity style-integration investor faces at each rebalancing time is the relative weighting of the factors. We propose a Bayesian optimized style-integration (BOI) strategy with excellent out-of-sample performance. Focusing on the problem of a commodity investor that seeks exposure to the carry, hedging pressure, momentum, skewness, and basis-momentum factors, the evidence suggests that the BOI portfolio achieves better Sharpe ratios and certainty equivalent returns, among other performance metrics, than the 1/K style-weighted integrated portfolio, and a battery of sophisticated optimized integrations. The findings survive the consideration of longer estimation windows, various commodity score schemes, and alternative Bayesian priors.
Item Type: | MPRA Paper |
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Original Title: | A Bayesian Perspective on Commodity Style Integration |
Language: | English |
Keywords: | Commodity risk premia; Style integration; Long-short portfolio; Parameter estimation risk; Bayesian portfolio optimization. |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General G - Financial Economics > G1 - General Financial Markets G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions G - Financial Economics > G1 - General Financial Markets > G13 - Contingent Pricing ; Futures Pricing |
Item ID: | 117831 |
Depositing User: | Professor Ana-Maria Fuertes |
Date Deposited: | 05 Jul 2023 14:04 |
Last Modified: | 05 Jul 2023 14:04 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/117831 |