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Style Analysis with Particle Filtering and Generalized Simulated Annealing

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Listed:
  • Takaya Fukui

    (Graduate School of Economics, The University of Tokyo)

  • Seisho Sato

    (Faculty of Economics, The University of Tokyo)

  • Akihiko Takahashi

    (Faculty of Economics, The University of Tokyo)

Abstract

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). Specifically, 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 confirms the validity of our method. Moreover, we create fund-specific style indexes to further improves estimation in the analysis.

Suggested Citation

  • Takaya Fukui & Seisho Sato & Akihiko Takahashi, 2016. "Style Analysis with Particle Filtering and Generalized Simulated Annealing," CIRJE F-Series CIRJE-F-1010, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2016cf1010
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    References listed on IDEAS

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