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A multicriteria extension of the efficient market hypothesis

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A multicriteria extension of the efficient market hypothesis

dc.contributor.author	Salas-Molina, Francisco
dc.contributor.author	Pla Santamaría, David
dc.contributor.author	Mayor Vitoria, Fernando
dc.contributor.author	Vercher Ferrandiz, María Luisa
dc.date.accessioned	2022-04-24T16:11:58Z
dc.date.available	2022-04-25T04:45:06Z
dc.date.issued	2021	es_ES
dc.identifier.citation	Salas-Molina F, Pla-Santamaria D, Mayor-Vitoria F, Vercher-Ferrandiz ML. A Multicriteria Extension of the Efficient Market Hypothesis. Mathematics. 2021; 9(6):649.	es_ES
dc.identifier.uri	https://hdl.handle.net/10550/82356
dc.description.abstract	Challenging the Efficient Market Hypothesis (EMH) has been a recurrent topic for researchers and practitioners since its formulation. Hundreds of empirical studies claim to either prove or disprove the EMH by means of a number of heterogeneous methods. Even though the EMH is usually adjusted to a measure of risk, there is a lack of a formal analysis within a multiple-criteria context. In this paper, we propose a extension of the EMH that accommodates the foundations of multiple-criteria decision analysis. To this end, we rely on a family of parametric signed dissimilarity measures to assess multidimensional performance differences. Since normalization is a critical step in our approach to avoid meaningless comparisons, we present two novel theoretical results connecting different normalization techniques. This multicriteria extension provides a common framework on which to add empirical evidence regarding the EMH testing.	es_ES
dc.language.iso	en	es_ES
dc.subject	efficient market hypothesis	es_ES
dc.subject	multiple-criteria test	es_ES
dc.subject	signed measures	es_ES
dc.subject	normalization	es_ES
dc.title	A multicriteria extension of the efficient market hypothesis	es_ES
dc.type	journal article	es_ES
dc.subject.unesco	UNESCO::CIENCIAS ECONÓMICAS	es_ES
dc.identifier.doi	10.3390/math9060649	es_ES
dc.accrualmethod	S	es_ES
dc.embargo.terms	0 days	es_ES