In a complete financial market every contingent claim can be hedged perfectly. In an incomplete market it is possible to stay on the safe side by superhedging. But such strategies may require a large amount of initial capital. Here we study the question what an investor can do who is unwilling...

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...

Testing the cointegrating rank of a vector autoregressive process with an intercept is considered. In addition to the likelihood ratio (LR) tests developed by Johansen and Juselius and others we also consider an alternative class of tests which is based on estimating the trend parameters of the...

Tests for the cointegrating rank of a vector autoregressive process are considered which allow for possible exogenous shifts in the mean of the data generation process. The break points are assumed to be known a priori. It is proposed to estimate and remove the deterministic terms such as mean,...

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...

Testing the cointegrating rank of a vector autoregressive process which may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else remove the linear...

The impact of the choice of the lag length on tests for the number of cointegration relations in a vector autoregressive (VAR) process is investigated. It is shown that the asymptotic distribution of likelihood ratio (LR) tests for the cointegrating rank remains unchanged if the true data...

This paper improves previous sufficient conditions for stationarity obtained in the context of a general nonlinear vector autoregressive model with nonlinear autoregressive conditional heteroskedasticity. The results are proved by using the stability theory developed for Markov chains....

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,...

In this paper, the structural vector autoregressive (SVAR) model is used to analyze short-run and contemporaneous relationships between monetary aggregates and other macroeconomic variables. This requires imposing restrictions on the correlation structure of the VAR residuals. Different...