Multi-criteria optimization in regression

Tsionas, Mike G. (2021) Multi-criteria optimization in regression. Annals of Operations Research, 306 (1-2): 1. pp. 7-25. ISSN 0254-5330

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In this paper, we consider standard as well as instrumental variables regression. Specification problems related to autocorrelation, heteroskedasticity, neglected non-linearity, unsatisfactory out-of-small performance and endogeneity can be addressed in the context of multi-criteria optimization. The new technique performs well, it minimizes all these problems simultaneously, and eliminates them for the most part. Markov Chain Monte Carlo techniques are used to perform the computations. An empirical application to NASDAQ returns is provided.

Item Type:
Journal Article
Journal or Publication Title:
Annals of Operations Research
Uncontrolled Keywords:
?? regressioninstrumental variablesautocorrelationheteroskedasticityspecification errormulti-criteria optimizationdecision sciences(all)management science and operations research ??
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Deposited On:
07 Oct 2021 14:00
Last Modified:
12 Feb 2024 00:42