Predicting commodity returns with climate variables: Statistical loss functions vs. economic value
检验气候指标能否预测大宗商品期货收益,发现统计上预测力弱,但用于投资组合却能带来经济收益,说明统计显著性与经济价值存在脱节。
We test whether large-scale climate indicators contribute to the predictability of commodity futures returns and generate economic value for investors. Using monthly data on fourteen commodities, we conduct a pseudo out-of-sample forecasting exercise based on a range of models that include automatic variable selection and nonlinear regime-switching specifications. Climate-related predictors rarely outperform standard benchmarks in terms of statistical forecast accuracy. Yet, when embedded in a portfolio choice problem, they deliver economically meaningful gains. These results illustrate a disconnect between statistical predictability and economic relevance.