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Statistical inference for the tangency portfolio in high dimension
Örebro University, Örebro University School of Business. Department of Statistics.ORCID iD: 0000-0003-0203-4688
Örebro University, Örebro University School of Business. Department of Statistics.ORCID iD: 0000-0002-1395-9427
Department of Mathematics, Stockholm University, Stockholm, Sweden; Department of Mathematics, College of Science and Technology, University of Rwanda, Kigali, Rwanda.
2021 (English)In: Statistics, ISSN 0233-1888, Vol. 55, no 3, p. 532-560Article in journal (Refereed) Published
Abstract [en]

In this paper, we study the distributional properties of the tangency portfolio (TP) weights assuming a normal distribution of the logarithmic returns. We derive a stochastic representation of the TP weights that fully describes their distribution. Under a high-dimensional asymptotic regime, i.e., the dimension of the portfolio, k, and the sample size, n, approach infinity such that k/n -> c is an element of (0, 1), we deliver the asymptotic distribution of the TP weights. Moreover, weconsider tests about the elements of the TP and derive the asymptotic distribution of the test statistic under the null and alternative hypotheses. In a simulation study, we compare the asymptotic distribution of the TP weights with the exact finite sample density. Wealso compare the high-dimensional asymptotic test with an exact small sample test. We document a good performance of the asymptotic approximations except for small sample sizes combined with c close to one. In an empirical study, we analyse the TP weights in portfolios containing stocks from the S&P 500 index.

Place, publisher, year, edition, pages
Taylor & Francis, 2021. Vol. 55, no 3, p. 532-560
Keywords [en]
Tangency portfolio, high-dimensional asymptotics, hypothesis testing
National Category
Probability Theory and Statistics Economics
Identifiers
URN: urn:nbn:se:oru:diva-93419DOI: 10.1080/02331888.2021.1951730ISI: 000675362300001Scopus ID: 2-s2.0-85110941947OAI: oai:DiVA.org:oru-93419DiVA, id: diva2:1583306
Available from: 2021-08-05 Created: 2021-08-05 Last updated: 2023-12-08Bibliographically approved

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Karlsson, SuneMazur, Stepan

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