Statistical estimation of optimal portfolios for locally stationary returns of assets

Hiroshi Shiraishi, Masanobu Taniguchi

2 引用 (Scopus)

抄録

This paper discusses the asymptotic property of estimators for optimal portfolios when the returns are vector-valued locally stationary processes. First, we derive the asymptotic distribution of a nonparametric portfolio estimator based on the kernel method. Optimal bandwidth and kernel function are given by minimizing the mean squares error of it. Next, assuming parametric models for non-Gaussian locally stationary processes, we prove the LAN theorem, and propose a parametric portfolio estimator ĝ based on a quasi-maximum likelihood estimator. Then it is shown that ĝ is asymptotically efficient based on the LAN. Numerical studies are provided to investigate the accuracy of the portfolio estimators parametrically and nonparametrically. They illuminate some interesting features of them.

元の言語 English 129-154 26 International Journal of Theoretical and Applied Finance 10 1 https://doi.org/10.1142/S0219024907004093 Published - 2007 2 Yes

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Assets
Statistical estimation
Optimal portfolio
Estimator
Stationary process
Local area networks
Kernel
Kernel methods
Asymptotic distribution
Quasi-maximum likelihood estimator
Asymptotic properties
Parametric model
Bandwidth

ASJC Scopus subject areas

• Economics, Econometrics and Finance(all)

これを引用

：: International Journal of Theoretical and Applied Finance, 巻 10, 番号 1, 02.2007, p. 129-154.

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