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Title: Forecasting market returns: bagging or combining?
Authors: Jordan, Steven J.
Vivian, Andrew J.
Wohar, Mark E.
Keywords: Return forecasting
Macro variables
Technical indicators
Emerging markets
Issue Date: 2016
Publisher: © International Institute of Forecasters. Published by Elsevier
Citation: JORDAN, S.J., VIVIAN, A. and WOHAR, M.E., 2016. Forecasting market returns: bagging or combining? International Journal of Forecasting, 33 (1), pp. 102-120.
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 was accepted for publication in the journal International Journal of Forecasting and the definitive published version is available at http://dx.doi.org/10.1016/j.ijforecast.2016.07.003
Version: Accepted for publication
DOI: 10.1016/j.ijforecast.2016.07.003
URI: https://dspace.lboro.ac.uk/2134/22258
Publisher Link: http://dx.doi.org/10.1016/j.ijforecast.2016.07.003
ISSN: 0169-2070
Appears in Collections:Published Articles (Business)

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