In many applications one is interested to detect certain (known) patterns in the mean of a process with smallest delay. Using an asymptotic framework which allows to capture that feature, we study a class of appropriate sequential nonparametric kernel procedures under local nonparametric...

The FI-A-PARCH process has been developed by Tse (1998) to model essential characteristics of financial market returns. However, due to the nonstationarity described by Níguez (2002) the process exhibits infinite conditional second moments and no statements about the autocovariance function can...

Finanzmarktdaten wie Zinsen, Aktien- oder Wechselkurse und andere spekulative Preise setzen sich durch verschiedene Besonderheiten von sonstigen ökonomischen Zeitreihendaten ab. Dieser Artikel untersucht die Konsequenzen dieser Besonderheiten für die rationale Bewertung von Finanzinstrumenten...

An attractive nonparametric method to detect change-points sequentially is to apply control charts based on kernel smoothers. Recently, the strong convergence of the associated normed delay associated with such a sequential stopping rule has been studied under sequences of out-of-control models....

Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if...

Recent results on so-called SEMIFAR models introduced by Beran (1997) are discussed. The nonparametric deterministic trend is estimated by a kernel method. The differencing and fractional differencing parameters as well as the autoregressive coefficients are estimated by an approximate maximum...

We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind...

The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the...

We derive the limiting null distributions of the standard and OLS based CUSUM-tests for structural change of the coecients of a linear regression model in the context of long memory disturbances. We show that both tests behave fundamentally different in a long memory environment, as compared to...

Stock returns are often modeled as having infinite second or fourth moments with consequences for test statistics which have not yet been fully explored. Conclusions on the existence of moments are usually drawn from a generalized Pareto or simple Pareto tail index estimate. In a recent study...