Incorporating weather information into commodity portfolio optimization

Dongna Zhang, Xingyu Dai*, Jianhao Xue

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This study investigates the out-of-sample performance of commodity portfolios by incorporating weather information within the Black-Litterman framework. The inclusion of weather information increases returns, reduces downside risk for energy and agricultural portfolios, and diminishes volatility in agricultural portfolios. We find significant enhancement in the efficiency of energy and agricultural portfolios with weather information. Notably, portfolios integrating low-temperature weather information outperform their counterparts across most performance measures. Our findings underscore the benefits of incorporating weather information in the optimization of commodity portfolios.
Original languageEnglish
Article number105672
Number of pages8
JournalFinance Research Letters
Early online date31 May 2024
Publication statusE-pub ahead of print - 31 May 2024

Cite this