Business cycle indicators are used to assess the economic situation of countries or regions. They are closely watched by the public, but are not easy to interpret. Does a current movement of the indicator signal a turning point or not? With the help of Markov Switching Models movements of...

Investment in equipment and machinery is a very important component of GDP. In this paper we examine whether data from business tendency sur- veys are useful for a timely assessment of current investment behavior. In addition we investigate whether the survey results are helpful for forecasting...

Results from business tendency surveys are often used to construct leading indicators. The indicators are then, for example, employed to forecast GDP growth. In this article more detailed results of business tendency surveys are used to forecast quarter-on-quarter GDP growth. The target series...

In der Literatur wurden verschiedene parametrische Modelle zur Analyse der Heteroskedastie in Zeitreihen von Finanzmarktdaten entwickelt. Eine Möglichkeit, die bedingte Volatilität nichtparametrisch zu erfassen, ist die Kernschätzung von bedingten Quantilen. In diesem Aufsatz werden einige...

In diesem Aufsatz wird die nichtparametrische Autoregression auf die Prognose von Quantilen angewendet. Verfahren der Kernregression werden benutzt, um zu autoregressiven Quantiisschätzern zu gelangen. Da die üblichen Maße zur Beurteilung der Prognose, wie etwa der mittlere quadratische...

Business climate indicators are used to receive early signals for turning points in the general business cycle. Therefore methods for the detection of turning points in time series are required. Estimations of slopes of a smooth component in the data can be calculated with local polynomial...

Business cycle indicators are used to assess the economic situation of countries or regions. They are closely watched by the public, but are not easy to interpret. Does a current movement of the indicator signal a turning point or not? With the help of Markov Switching Models movements of...

There are various parametric models to analyse the volatility in time series of financial market data. For maximum likelihood estimation these parametric methods require the assumption of a known conditional distribution. In this paper we examine the conditional distribution of daily DAX returns...