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Singular inverse Wishart distribution and its application to portfolio theory
Department of Mathematics, Stockholm University, Stockholm, Sweden.
Department of Statistics, Lund University, Lund, Sweden. (Statistics)ORCID-id: 0000-0002-1395-9427
Department of Statistics, Lund University, Lund, Sweden.
2016 (engelsk)Inngår i: Journal of Multivariate Analysis, ISSN 0047-259X, E-ISSN 1095-7243, Vol. 143, s. 314-326Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The inverse of the standard estimate of covariance matrix is frequently used in the portfolio theory to estimate the optimal portfolio weights. For this problem, the distribution of the linear transformation of the inverse is needed. We obtain this distribution in the case when the sample size is smaller than the dimension, the underlying covariance matrix is singular, and the vectors of returns are independent and normally distributed. For the result, the distribution of the inverse of covariance estimate is needed and it is derived and referred to as the singular inverse Wishart distribution. We use these results to provide an explicit stochastic representation of an estimate of the mean-variance portfolio weights as well as to derive its characteristic function and the moments of higher order. The results are illustrated using actual stock returns and a discussion of practical relevance of the model is presented. 

sted, utgiver, år, opplag, sider
Elsevier, 2016. Vol. 143, s. 314-326
Emneord [en]
Singular Wishart distribution, Mean-variance portfolio, Sample estimate of precision matrix, Moore-Penrose inverse
HSV kategori
Forskningsprogram
Matematik
Identifikatorer
URN: urn:nbn:se:oru:diva-54837DOI: 10.1016/j.jmva.2015.09.021ISI: 000366885300019Scopus ID: 2-s2.0-84945144193OAI: oai:DiVA.org:oru-54837DiVA, id: diva2:1066853
Forskningsfinansiär
Swedish Research Council, 2013-5180Riksbankens Jubileumsfond, P13-1024:1Tilgjengelig fra: 2017-01-19 Laget: 2017-01-19 Sist oppdatert: 2018-10-19bibliografisk kontrollert

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