We estimate a generalized version of the Long-Run Risk model in a panel of developed and developing countries using consumption, dividend growth, and asset returns data by utilizing the particle filter, while allowing for measurement errors in consumption data at quarterly and annual...

This chapter presents an empirical application of Bayesian MCMC estimation to the three main asset pricing models in use in the financial econometrics literature, namely, the Capital Asset Pricing Model (CAPM), the Fama-French (1992) three-factor model, and the Carhart (1997) four-factor model...

Particle filtering is a useful statistical tool which can be used to make inference on the latent variables and the structural parameters of state space models by employing it inside MCMC algorithms (Flury and Shephard, 2011). It only relies on two assumptions (Gordon et al, 1993): a: The...