Estimating Style Weights of Mutual Funds by Monte Carlo Filter with Generalized Simulated Annealing
44 Pages Posted: 8 Jun 2016
Date Written: June 5, 2016
Abstract
This paper proposes a new approach to style analysis by applying a general state space model and Monte Carlo filter. Particularly, we regard coefficients of style indices as state variables in the state space model and employ Monte Carlo filter as an estimation method.
Moreover, we utilize a generalized simulated annealing for estimating parameters, which seems the first attempt in particle filtering methods for a statistical application. Finally, an empirical analysis with actual funds’ data confirms the validity of our approach.
Keywords: Style Weights, Mutual Fund, General State Space Model, Monte Carlo filer, Generalized Simulated Annealing
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