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This paper proposes a new approach to style analysis of mutual funds in a general state space framework with particle filtering and generalized simulated annealing (GSA). Speci cally, we regard the ex-posure of each style index as a latent state variable in a state space model and employ a Monte Carlo filter as a particle filtering method, where GSA is effectively applied to estimating unknown parameters. An empirical analysis using data of three Japanese equity mu- tual funds with six standard style indexes con rms the validity of our method. Moreover, we create fund-specific style indexes to further improves estimation in the analysis

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  • Takaya Fukui

    (Graduate School of Economics, University of Tokyo)

  • Seisho Sato

    (Graduate School of Economics, University of Tokyo)

  • Akihiko Takahashi

    (Graduate School of Economics, University of Tokyo)

Abstract

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  • Takaya Fukui & Seisho Sato & Akihiko Takahashi, 2017. "This paper proposes a new approach to style analysis of mutual funds in a general state space framework with particle filtering and generalized simulated annealing (GSA). Speci cally, we regard the ex," CARF F-Series CARF-F-383, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  • Handle: RePEc:cfi:fseres:cf383
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    References listed on IDEAS

    as
    1. Laurens Swinkels & Pieter Van Der Sluis, 2006. "Return-based style analysis with time-varying exposures," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 529-552.
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    5. Akihiko Takahashi & Seisho Sato, 2001. "A Monte Carlo Filtering Approach for Estimating the Term Structure of Interest Rates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 50-62, March.
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