An investor faced with a contingent claim may eliminate risk by (super-)hedging in a financial market. As this is often quite expensive, we study partial hedges, which require less capital and reduce the risk. In a previous paper we determined quantile hedges which succeed with maximal...

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...

Motivated by a nonparametric GARCH model we consider nonparametric additive regression and autoregression models in the special case that the additive components are linked parametrically. We show that the parameter can be estimated with parametric rate and give the normal limit. Our procedure...

This paper proposes linear higher order conditions on the term structure that allow to compute valuation bounds for any deterministic cash stream. Starting from bounds on the forward rate curve and its derivatives, which are nonlinear in the discount factors, we derive linear conditions that are...

One puzzling behavior of asset returns for various frequencies is the often observed positive autocorrelation at lag 1. To some extent this can be explained by standard asset pricing models when assuming time varying risk premia. However, one often finds better results when directly fitting an...

In a model with private information of the worker about her ability and unobservable effort choice, the role of public and private employment services is analyzed. The coexistence of an inefficient employment exchange and an efficient private agency may lead to optimal screening with first best...

In this paper a two-sector growth model allowing indeterminacy to occur at relatively mild degrees of increasing returns is developed. It is shown that these economies of scale need only be present in one sector of the economy (investment). This feature of the model, therefore, builds on...

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...