Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions
dc.contributor.author | Beaulieu, Marie-Claude | |
dc.contributor.author | Dufour, Jean Marie | |
dc.contributor.author | Khalaf, Lynda | |
dc.date.accessioned | 2006-09-22T19:56:41Z | |
dc.date.available | 2006-09-22T19:56:41Z | |
dc.date.issued | 2005 | |
dc.identifier.uri | http://hdl.handle.net/1866/533 | |
dc.format.extent | 204421 bytes | |
dc.format.mimetype | application/pdf | |
dc.publisher | Université de Montréal. Département de sciences économiques. | fr |
dc.subject | capital asset pricing model | |
dc.subject | mean-variance efficiency | |
dc.subject | non-normality | |
dc.subject | multivariate linear regression | |
dc.subject | stable distribution | |
dc.subject | skewness | |
dc.subject | kurtosis | |
dc.subject | asymmetry | |
dc.subject | uniform linear hypothesis | |
dc.subject | exact test | |
dc.subject | Monte Carlo test | |
dc.subject | nuisance parameter | |
dc.subject | specification test | |
dc.subject | diagnostics | |
dc.subject | [JEL:C3] Mathematical and Quantitative Methods - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors | en |
dc.subject | [JEL:C12] Mathematical and Quantitative Methods - Econometric and Statistical Methods: General - Hypothesis Testing | en |
dc.subject | [JEL:C33] Mathematical and Quantitative Methods - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors - Models with Panel Data | en |
dc.subject | [JEL:C15] Mathematical and Quantitative Methods - Econometric and Statistical Methods: General - Statistical Simulation Methods; Monte Carlo Methods; Bootstrap Methods | en |
dc.subject | [JEL:G1] Financial Economics - General Financial Markets | en |
dc.subject | [JEL:G12] Financial Economics - General Financial Markets - Asset Pricing; Trading volume; Bond Interest Rates | en |
dc.subject | [JEL:G14] Financial Economics - General Financial Markets - Information and Market Efficiency; Event Studies | en |
dc.subject | [JEL:C3] Mathématiques et méthodes quantitatives - Méthodes en économétrie; modèles à équations multiples et simultanées | fr |
dc.subject | [JEL:C12] Mathématiques et méthodes quantitatives - Économétrie et méthodes statistiques; généralités - Tests d'hypothèses | fr |
dc.subject | [JEL:C33] Mathématiques et méthodes quantitatives - Méthodes en économétrie; modèles à équations multiples et simultanées - Modèles avec données de panel | fr |
dc.subject | [JEL:C15] Mathématiques et méthodes quantitatives - Économétrie et méthodes statistiques; généralités - Méthodes de simulation statistique: la méthode Monte Carlo | fr |
dc.subject | [JEL:G1] Économie financière - Marchés financiers généraux | fr |
dc.subject | [JEL:G12] Économie financière - Marchés financiers généraux - Prix des actifs | fr |
dc.subject | [JEL:G14] Économie financière - Marchés financiers généraux - Information et efficacité du marché; études d'événements | fr |
dc.title | Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions | |
dc.type | Article | |
dc.contributor.affiliation | Université de Montréal. Faculté des arts et des sciences. Département de sciences économiques | |
dcterms.abstract | In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis. | |
dcterms.isPartOf | urn:ISSN:0709-9231 | |
UdeM.VersionRioxx | Version publiée / Version of Record | |
oaire.citationTitle | Cahier de recherche | |
oaire.citationIssue | 2005-04 |
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