Artikel
Robust inference in the capital asset pricing model using the multivariate t-distribution
In this paper, we consider asset pricing models under the multivariate t-distribution with finite second moment. Such a distribution, which contains the normal distribution, offers a more flexible framework for modeling asset returns. The main objective of this work is to develop statistical inference tools, such as parameter estimation and linear hypothesis tests in asset pricing models, with an emphasis on the Capital Asset Pricing Model (CAPM). An extension of the CAPM, the Multifactor Asset Pricing Model (MAPM), is also discussed. A simple algorithm to estimate the model parameters, including the kurtosis parameter, is implemented. Analytical expressions for the Score function and Fisher information matrix are provided. For linear hypothesis tests, the four most widely used tests (likelihood-ratio, Wald, score, and gradient statistics) are considered. In order to test the mean-variance efficiency, explicit expressions for these four statistical tests are also presented. The results are illustrated using two real data sets: the Chilean Stock Market data set and another from the New York Stock Exchange. The asset pricing model under the multivariate t-distribution presents a good fit, clearly better than the asset pricing model under the assumption of normality, in both data sets.
- Sprache
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Englisch
- Erschienen in
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 6 ; Pages: 1-22 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
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capital asset pricing model
estimation of systematic risk
tests of mean-variance efficiency
t-distribution
generalized method of moments
multifactor asset pricing model
- Ereignis
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Geistige Schöpfung
- (wer)
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Galea, Manuel
Cademártori Rosso, David
Curci, Roberto
Molina, Alonso
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
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Basel
- (wann)
-
2020
- DOI
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doi:10.3390/jrfm13060123
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Galea, Manuel
- Cademártori Rosso, David
- Curci, Roberto
- Molina, Alonso
- MDPI
Entstanden
- 2020
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