In this paper we consider the asymptotic distribution of S -estimators in the nonlinear regression model with long-memory error terms. S - estimators are robust estimates with a high breakdown point and good asymptotic properties in the i.i.d case. They are constructed for linear regression. In...

We show that there is strong evidence of long-range dependence in the volatilities of several German stock returns. This will be done by estimating the memory parameter of the absolute returns with classical log-periodogram regression as well as by employing the tapered periodogram. Both...

We investigate the behaviour of S - estimators in the linear regression model, when the error terms are long-memory Gaussian processes. It turns out that under mild regularity conditions S - estimators are still normally distributed with a similar variance - covariance structure as in the i.i.d...

We develop a Wald type test to distinguish between long memory and ESTARnonlinearity by using a directed-Wald statistic to overcome the problem of restricted parametersunder the alternative. The test is derived from two basic model specificationswhere the first is the standard model based on an...

Model risk as part of the operational risk is a serious problem for financial institutions.As the pricing of derivatives as well as the computation of the marketor credit risk of an institution depend on statistical models the application of awrong model can lead to a serious over- or...