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Commodity prices and related equity prices

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  • Shiu-Sheng Chen

Abstract

This paper shows that commodity-sensitive stock price indices have strong power in predicting nominal and real commodity prices at short horizons (one-month-ahead predictions) using both in- and out-of-sample tests. The forecasts based on commodity-sensitive stock price indices are able to significantly outperform naïve no-change forecasts. For example, the one-month-ahead forecasts for nominal commodity prices reduce the mean squared prediction error by between 1.5% (for natural gas prices) and 20% (for copper prices). Moreover, the one-month-ahead directional forecast is found to perform significantly better than a 50:50 coin toss. As stock prices are not subject to revision, the proposed variable, which reflects timely and readily available market information, can potentially be a valuable predictor and thereby help to improve the accuracy of commodity price forecasts.

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  • Shiu-Sheng Chen, 2016. "Commodity prices and related equity prices," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 949-967, August.
    • Handle: RePEc:cje:issued:v:49:y:2016:i:3:p:949-967
    DOI: 10.1111/caje.12220
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    5. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    6. Wang, Qiao & Balvers, Ronald, 2021. "Determinants and predictability of commodity producer returns," Journal of Banking & Finance, Elsevier, vol. 133(C).

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    JEL classification:

    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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