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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/22258

Title: Forecasting market returns: Bagging or combining?
Authors: Jordan, Steven J.
Vivian, Andrew
Wohar, Mark E.
Keywords: Return forecasting
Fundamentals
Macro variables
Technical indicators
Emerging markets
Asia
G7
Issue Date: 2016
Publisher: © Elsevier
Citation: JORDAN, S.J., VIVIAN, A. and WOHAR, M.E., 2016. Forecasting market returns: Bagging or combining?. International Journal of Forecasting, In press.
Abstract: This paper provides a rigorous and detailed analysis of the methods of bagging, which addresses both model and parameter uncertainty. We provide a multi-country study of bagging, of which there are very few to date, that examines out-of-sample forecasts for the G7 and a broad set of Asian countries. We find that, when portfolio weight restrictions are applied, bagging generally improves forecast accuracy and generates economic gains relative to the benchmark. Bagging also performs well compared to forecast combinations in this setting. We incorporate data mining critical values for appropriate inference on bagging and combination forecast methods. We provide new evidence that the results for bagging cannot be fully explained by data mining concerns. Finally, forecasting gains are highest for countries with high trade openness and high FDI. The potentially substantial economic gains could well be operational given the existence of index funds for most of these countries.
Description: This paper is in closed access until 24 months after publication.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/22258
Publisher Link: http://www.sciencedirect.com/science/journal/01692070
ISSN: 0169-2070
Appears in Collections:Closed Access (Business School)

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