This paper entertains the notion that disturbances on the demand side play a central role in our understanding of the Great Depression. In fact, from Euler equation residuals we are able to identify a series of unusually large negative demand shocks that appeared to have hit the U. S. economy...

We emphasize the importance of properly identifying the long-run relations underlying the monetary model of the exchange rate. The separate estimation of long-run money demands leads to a "structural" error correction equation which allows an interpretation of the various channels affecting the...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

We consider two multivariate long-memory ARCH models, which extend the univariate long-memory ARCH models, we first consider a long-memory extension of the restricted constant conditional correlations (CCC) model introduced by Bollerslev (1990), and we propose a new unrestricted conditional...

Multivariate Volatility Models belong to the class of nonlinear models for financial data. Here we want to focus on multivariate GARCH models. These models assume that the variance of the innovation distribution follows a time dependent process conditional on information which is generated by...

This paper studies the smooth transition regression model where regressors are I(1) and errors are I(0). The regressors and errors are assumed to be dependent both serially and contemporaneously. Using the triangular array asymptotics, the nonlinear least squares estimator is shown to be...

We propose a new approach to the pricing and hedging of contingent claims under transaction costs in a general incomplete market in discrete time. Under the assumptions of a bounded mean-variance tradeoff, substantial risk and a nondegeneracy condition on the conditional variances of asset...

We determine the increase of the maximum risk over the minimax risk in the case that the optimally robust estimator for the false radius is used. This is done by numerical solution of the implicit equations which determine optimal robustness, for location, scale, and linear regression models,...

Credit risk refers to the risk of incurring losses due to unexpected changes in the credit quality of a counterparty or issuer. In this paper we give an introduction to the modeling of credit risks and the valuation of credit-risky securities. We consider individual as well as correlated credit...