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Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Forecasting Stock Returns: Do Commodities Prices Help?
Authors: Black, Angela
Klinkowska, Olga
McMillan, David
McMillan, Fiona
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Keywords: stock prices
commodity prices
Issue Date: Dec-2014
Publisher: Wiley-Blackwell
Citation: Black A, Klinkowska O, McMillan D & McMillan F (2014) Forecasting Stock Returns: Do Commodities Prices Help?, Journal of Forecasting, 33 (8), pp. 627-639.
Abstract: This paper examines the relationship between stock prices and commodity prices and whether this can be used to forecast stock returns. As both prices are linked to expected future economic performance they should exhibit a long-run relationship. Moreover, changes in sentiment towards commodity investing may affect the nature of the response to disequilibrium. Results support cointegration between stock and commodity prices, while Bai–Perron tests identify breaks in the forecast regression. Forecasts are computed using a standard fixed (static) in-sample/out-of-sample approach and by both recursive and rolling regressions, which incorporate the effects of changing forecast parameter values. A range of model specifications and forecast metrics are used. The historical mean model outperforms the forecast models in both the static and recursive approaches. However, in the rolling forecasts, those models that incorporate information from the long-run stock price/commodity price relationship outperform both the historical mean and other forecast models. Of note, the historical mean still performs relatively well compared to standard forecast models that include the dividend yield and short-term interest rates but not the stock/commodity price ratio.
Type: Journal Article
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Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: University of Aberdeen
University of Aberdeen
Accounting and Finance
University of Dundee

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