This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be...

We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...

There is increasing demand for models of time-varying and non-Gaussian dependencies for mul- tivariate time-series. Available models suffer from the curse of dimensionality or restrictive assumptions on the parameters and the distribution. A promising class of models are the hierarchical...

The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach which make it different from the classical one are: (1) the study is non-asymptotic, that is, the sample size is fixed and does not tend to infinity; (2) the parametric assumption is possibly...

Most of the available monthly interest data series consist of monthlyaverages of daily observations. It is well-known that this averaging introduces spurious autocorrelation effectsin the first differences of the series. It isexactly this differenced series we are interested in when...

In this paper we examine the asymptotic properties of the estimator of the long-run coefficient (LRC) in a dynamic regression model with integrated regressors and serially correlated errors. We show that the OLS estimators of the regression coefficients are inconsistent but the OLS-based...

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives sufficient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation that estimated GARCH-parameters often...

We provide a method for distinguishing long-range dependence from deterministic trends such as structural breaks. The method is based on the comparison of standard log-periodogram regression estimation of the memory parameter with its tapered counterpart. The difference of these estimators...

Wir verwenden eine neue, auf der Burr-Verteilung basierende Spezifikation aus der Familie der Autoregressive Conditional Duration (ACD) Modelle zur ökonometrischen Analyse der Transaktionsintensitäten während der Börseneinführung (IPO) der Deutsche Telekom Aktie. In diesem Fallbeispiel wird...