"Style Analysis with Particle Filtering and Generalized Simulated Annealing"
Fukui, Takaya, Seisho Sato, and Akihiko Takahashi
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|Remarks||Revised in June 2016 and March 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). Specifucally, 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 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.