We study a consumption based asset pricing model with incomplete information and alpha-stable shocks. Incomplete information leads to a non-Gaussian filtering problem. Bayesian updating generates fluctuating confidence in the agents' estimate of the persistent component of the dividends’...

Forecast performance of artificial neural network models are investigated using Ashley et al . (1980) and the neural network nonlinearity test proposed by Lee et al . (1993) is employed to find possible existence of business cycle asymmetries in Canada, France, Japan, UK and USA real GDP growth...

Monthly inflation in the United States indicates non-normality in the form of either occasional big shocks or marked changes in the level of the series. We develop a univariate state space model with symmetric stable shocks for this series. The non-Gaussian model is estimated by the...

We investigate time varying risk premia in forward dollar/pound monthly exchange rates over the last two decades. We study this issue using a signal plus noise model and separately using regression techniques. Our models account for time varying volatility and non-normalities in the observed...

We investigate whether business cycle dynamics in seven industrialized countries (the G7) are characterized by asymmetries in conditional mean. We provide evidence on this issue using a variety of time series models. Our approach is fully parametric. Our testing strategy is robust to any...

WWe explore the effects of fat tails on the equilibrium implications of the long run risks model of asset pricing by introducing innovations with dampened power law to consumption and dividends growth processes. We estimate the structural parameters of the proposed model by maximum likelihood....