Robust portfolio estimation under skew-normal return processes

Masanobu Taniguchi*, Alexandre Petkovic, Takehiro Kase, Thomas DiCiccio, Anna Clara Monti

*この研究の対応する著者

研究成果: Article査読

4 被引用数 (Scopus)

抄録

In this paper, we study issues related to the optimal portfolio estimators and the local asymptotic normality (LAN) of the return process under the assumption that the return process has an infinite moving average (MA) (∞) representation with skew-normal innovations. The paper consists of two parts. In the first part, we discuss the influence of the skewness parameter δ of the skew-normal distribution on the optimal portfolio estimators. Based on the asymptotic distribution of the portfolio estimator ĝ for a non-Gaussian dependent return process, we evaluate the influence of δ on the asymptotic variance V(δ) of ĝ. We also investigate the robustness of the estimators of a standard optimal portfolio via numerical computations. In the second part of the paper, we assume that the MA coefficients and the mean vector of the return process depend on a lower-dimensional set of parameters. Based on this assumption, we discuss the LAN property of the return's distribution when the innovations follow a skew-normal law. The influence of δ on the central sequence of LAN is evaluated both theoretically and numerically.

本文言語English
ページ(範囲)1091-1112
ページ数22
ジャーナルEuropean Journal of Finance
21
13-14
DOI
出版ステータスPublished - 2015 11 14

ASJC Scopus subject areas

  • 経済学、計量経済学および金融学(その他)

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