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

Takaya Fukui, Seisho Sato and Akihiko Takahashi
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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

No CARF-F-383, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo

Pages: 41 pages
Date: 2017-03
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