A Bayesian Generalized Factor Model with Comparative Analysis (Genellestirilmis Faktor Modellerinin Bayesyen Yaklasimi ve Karsilastirmali Analizi)

Abstract

This paper has two major objectives. First, we develop and implement a Bayesian generalized factor model that allows for non-orthogonality of the idiosyncratic factors and the flexibility of cross-sectional and time series dimensions. Second, we evaluate the significance of the orthogonality assumption in factor models, a controversial assumption discussed in the recent literature. To this end, we propose a simple methodology to choose the generalized factor model that best determines the idiosyncratic correlations and provide a comparative analysis between the classical and generalized factor models. The proposed methodology is applied to both the simulated data and the foreign exchange rate data.Factor model, Bayesian time series, MCMC simulation, Model selection.