Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30639
Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Forecasting U.S. Stock Returns
Author(s): McMillan, David
Contact Email: david.mcmillan@stir.ac.uk
Keywords: Stock Returns
Forecasting
Time-Variation
Rolling
Recursive
Term Structure
Issue Date: 29-Jan-2020
Citation: McMillan D (2020) Forecasting U.S. Stock Returns. European Journal of Finance. https://doi.org/10.1080/1351847X.2020.1719175
Abstract: We forecast quarterly US stock returns using 25 predictor variables. We consider a breadth of forecast methods and metrics, including bi- and multi-variate regressions, linear and non-linear models, rolling and recursive techniques, forecast combinations and statistical and economic evaluation. In doing so, we extend existing research both in terms of the range of predictor series and the scope of the analysis. In common with much of literature, a broad view over the full set of predictor variables tends to indicate that such models are unable to beat the historical mean model. However, nuances to these results reveals forecast success varies according to how the forecasts are evaluated and over time. Notably, the results reveal that the term structure of interest rates consistently provides the preferred forecast performance, especially when evaluated using the Sharpe ratio. The purchasing managers index also consistently provides a strong forecast performance. Further results also reveal that forecast combinations over the full set of variables do not outperform the preferred single variable forecasts, while forecast combinations using an interest rate subset group do perform well. The success of the term structure and the purchasing managers index highlights the importance of, respectively, investor and firm expectations of future economic performance in providing valuable stock return forecasts. This is also consistent with asset pricing models that indicate movements in returns are conditioned by such expectations.
DOI Link: 10.1080/1351847X.2020.1719175
Rights: This item has been embargoed for a period. During the embargo 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. This is an Accepted Manuscript of an article published by Taylor & Francis Group in The European Journal of Finance on 29 Jan 2020, available online: http://www.tandfonline.com/10.1080/1351847X.2020.1719175.
Notes: Output Status: Forthcoming/Available Online
Licence URL(s): https://storre.stir.ac.uk/STORREEndUserLicence.pdf

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