Strategic asset allocation under a fractional hidden markov model

Abstract

Strategic asset allocation is discussed in a discrete-time economy, where the rates of return from asset classes are explained in terms of some observable and hidden factors. We extend the existing models by incorporating long-term memory in the rates of return and observable economic factors, which have been documented in the empirical literature. Hidden factors are described by a discrete-time, finite-state, hidden Markov chain noisily observed in a fractional Gaussian process. The strategic asset allocation problem is discussed in a mean-variance utility framework. Filtering and parameter estimation are also considered in the hybrid model.