We investigate the impact of modeling fat tails observed in the empirical distributions of macroeconomic time series on the implications of theoretical macroeconomic models. We study this issue in the context of the widely used consumption-based asset-pricing model. We derive exact analytical...

We study the constant discount rate present value model for stock pricing in a stochastic setting where the exogenous dividend stream is modeled as a random walk with innovations drawn from the family of stable distributions. We derive an exact analytical solution for the fundamental stock...

We study the constant discount rate present value model for stock pricing in a stochastic setting where the exogenous dividend stream is modeled as a random walk with innovations drawn from the family of stable distributions. We derive an exact analytical solution for the fundamental stock...

We study a consumption-based asset pricing model with incomplete information and a- 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' growth...

We extend the constant discount factor model with intrinsic bubbles developed in Froot and Obstfeld (1991) to account for serial correlation in dividend growth rates. We derive an exact analytical expression for both the present value stock price and an intrinsic bubble component when dividend...

We investigate forecast performance of artificial neural network models using Ashley, et al. (1980) and employ neural network nonlinearity test proposed by Lee, et al. (1993) to find possible existence of business cycle asymmetries in Canada, France, Japan, UK, and USA real GDP growth rates. Our...

We study the consumption based asset pricing model due to Lucas (1978). The exogenous endowment sequence is modeled as a linear stochastic process driven by stable shocks in an otherwise standard framework. The Gaussian process emerges as a special case. We derive exact analytical solutions for...

We search for time-varying predictable components in monthly excess stock index returns over the risk free rates in the G7 countries. The predictable components provide an estimate of the expected excess returns. Our unobserved components model improves on Conrad and Kaul (1988) by taking into...

This paper uses an artificial neural network (ANN) model to forecast broad dividends, and computes fundamental stock prices with a stochastic discount factor (SDF). Broad dividends are used because they measure payouts to shareholders more accurately. Since nonlinearity is found in broad...

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...