Statistical portfolio estimation under the utility function depending on exogenous variables

Kenta Hamada, Dong Wei Ye, Masanobu Taniguchi

    Research output: Contribution to journalArticle

    Abstract

    In the estimation of portfolios, it is natural to assume that the utility function depends on exogenous variable. From this point of view, in this paper, we develop the estimation under the utility function depending on exogenous variable. To estimate the optimal portfolio, we introduce a function of moments of the return process and cumulant between the return processes and exogenous variable, where the function means a generalized version of portfolio weight function. First, assuming that exogenous variable is a random process, we derive the asymptotic distribution of the sample version of portfolio weight function. Then, an influence of exogenous variable on the return process is illuminated when exogenous variable has a shot noise in the frequency domain. Second, assuming that exogenous variable is nonstochastic, we derive the asymptotic distribution of the sample version of portfolio weight function. Then, an influence of exogenous variable on the return process is illuminated when exogenous variable has a harmonic trend. We also evaluate the influence of exogenous variable on the return process numerically.

    Original languageEnglish
    Article number127571
    JournalAdvances in Decision Sciences
    Volume2012
    DOIs
    Publication statusPublished - 2012

    Fingerprint

    Utility Function
    Weight Function
    Asymptotic distribution
    Shot noise
    Exogenous variables
    Utility function
    Random processes
    Shot Noise
    Optimal Portfolio
    Cumulants
    Random process
    Frequency Domain
    Harmonic
    Moment
    Evaluate

    ASJC Scopus subject areas

    • Decision Sciences(all)
    • Applied Mathematics
    • Computational Mathematics
    • Statistics and Probability

    Cite this

    Statistical portfolio estimation under the utility function depending on exogenous variables. / Hamada, Kenta; Wei Ye, Dong; Taniguchi, Masanobu.

    In: Advances in Decision Sciences, Vol. 2012, 127571, 2012.

    Research output: Contribution to journalArticle

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