Style analysis with particle filtering and generalized simulated annealing

Takaya Fukui (), Seisho Sato () and Akihiko Takahashi ()
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Takaya Fukui: Graduate School of Economics, The University of Tokyo, Tokyo 113-8654, Japan
Seisho Sato: Graduate School of Economics, The University of Tokyo, Tokyo 113-8654, Japan
Akihiko Takahashi: Graduate School of Economics, The University of Tokyo, Tokyo 113-8654, Japan

International Journal of Financial Engineering (IJFE), 2017, vol. 04, issue 02n03, 1-29

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 exposure 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 mutual funds with six standard style indexes confirms the validity of our method. Moreover, we create fund-specific style indexes to further improve estimation in the analysis.

Keywords: Style analysis; particle filtering; Monte Carlo filter; generalized simulated annealing; mutual fund; state space model (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (10)

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DOI: 10.1142/S2424786317500372

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