Combining forecasting procedures: Some theoretical results Yang, Yuhong
dc.contributor.department Statistics 2018-02-16T21:40:04.000 2020-07-02T06:55:54Z 2020-07-02T06:55:54Z 2000-03-01
dc.description.abstract <p>We study some methods of combining procedures for forecasting a continuous random variable. Statistical risk bounds under the square error loss are obtained under distributional assumptions on the future given the current outside information and the past observations. The risk bounds show that the combined forecast automatically achieves the best performance among the candidate procedures up to a constant factor and an additive penalty term. In terms of the rate of convergence, the combined forecast performs as well as if the best candidate forecasting procedure were known in advance. Empirical studies suggest that combining procedures can sometimes improve forecasting accuracy over the original procedures. Risk bounds are derived to theoretically quantify the potential gain and price of linearly combining forecasts for improvement. The result supports the empirical finding that it is not automatically a good idea to combine forecasts. Indiscriminate combining can degrade performance dramatically as a result of the large variability in estimating the best combining weights. An automated combining method is shown in theory to achieve a balance between the potential gain and the complexity penalty (the price of combining), to take advantage (if any) of sparse combining, and to maintain the best performance (in rate) among the candidate forecasting procedures if linear or sparse combining does not help.</p>
dc.description.comments <p>This preprint was published as Yuhong Yang, "Combining Forecasting Procedures: Some Theoretical Results", <em>Econometric Theory</em> (2004): 176-222, doi: <a href="" target="_blank">10.1017/S0266466604201086</a>.</p>
dc.identifier archive/
dc.identifier.articleid 1113
dc.identifier.contextkey 7446308
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/121
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 19:12:43 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords combining forecasts
dc.subject.keywords combining for adaptation
dc.subject.keywords combining for improvement
dc.title Combining forecasting procedures: Some theoretical results
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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