Please use this identifier to cite or link to this item:
Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Forecasting Stock Returns: Do Commodities Prices Help?
Author(s): Black, Angela
Klinkowska, Olga
McMillan, David
McMillan, Fiona
Contact Email:
Keywords: stock prices
commodity prices
Issue Date: Dec-2014
Date Deposited: 15-Jan-2016
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.
DOI Link: 10.1002/for.2314
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.
Licence URL(s):

Files in This Item:
File Description SizeFormat 
Black_et_al-2014-Journal_of_Forecasting.pdfFulltext - Published Version375.94 kBAdobe PDFUnder Embargo until 2999-12-21    Request a copy

Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.