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Träfflista för sökning "L773:0233 1888 OR L773:1029 4910 srt2:(2020-2021)"

Sökning: L773:0233 1888 OR L773:1029 4910 > (2020-2021)

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1.
  • Bertin, Karine, et al. (författare)
  • Least-square estimators in linear regression models under negatively superadditive dependent random observations
  • 2021
  • Ingår i: Statistics (Berlin). - : Taylor & Francis. - 0233-1888 .- 1029-4910. ; 55:5, s. 1018-1034
  • Tidskriftsartikel (refereegranskat)abstract
    • In this article, we study the asymptotic behaviour of the least-square estimator in a linear regression model based on random observation instances. We provide mild assumptions on the moments and dependence structure on the randomly spaced observations and the residuals under which the estimator is strongly consistent. In particular, we consider observation instances that are negatively superadditive dependent within each other, while for the residuals we merely assume that they are generated by some continuous function. We complement our findings with a simulation study providing insights on finite sample properties.
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2.
  • Karlsson, Sune, Professor, 1960-, et al. (författare)
  • Statistical inference for the tangency portfolio in high dimension
  • 2021
  • Ingår i: Statistics. - : Taylor & Francis. - 0233-1888 .- 1029-4910. ; 55:3, s. 532-560
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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