State Space Models for Dynamic Style Analysis of Portfolios

Abstract

This paper presents a framework and methods for the estimation of linear and non-linear state space (SS) models, occasionally subject to restrictions, to construct and estimate several models for style analysis with time varying exposures. The study is conducted by applying these models to an artificial portfolio and to return series of Brazilian investment funds. The results confirm the belief that dynamic allocations in a portfolio are a more realistic assumption for investment funds management.