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Jeudi 31 Mai 2012

16H15 : Francesco AUDRINO (University of St Gallen)

17H30 : Siegfried HÖRMANN (Université Libre de Bruxelles)

16H15 : Francesco AUDRINO (University of St Gallen)

« Forecasting correlations during the late-2000s financial crisis: short-run component,

long-run component, and structural breaks»

The predictive power of the various components affecting correlations that have been recently introduced in the literature is investigated. The focus is on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover, models allowing the correlation dynamics to be subjected to regime-shift caused by threshold-based structural breaks of a different nature are also considered. The results indicate that in some cases there may be a superimposition of the long- and short-term movements in correlations. Therefore, care is called for in interpretations when estimating the two components. Testing the forecasting accuracy of correlations during the late-2000s financial crisis yields mixed results. In general component models allowing for a richer correlation specification possess an increased predictive accuracy.

Economically speaking, no relevant gains are found by allowing for more flexibility in the correlation dynamics.

17H30 : Siegfried HÖRMANN (Université Libre de Bruxelles)

« Monitoring the intraday volatility pattern»,

A functional time series consists of curves, typically one curve per day. The most impor- tant parameter of such a series is the mean curve. We propose two methods of detecting a change in the mean function of a functional time series. The change is detected on-line, as new functional observations arrive. The general methodology is motivated by and applied to the detection of a change in the average intraday volatility pattern. It is asymptot- ically justi ed by applying a new notion of weak dependence for functional time series.

We demonstrate applicability of our theoretical results to a functional version of the cel- ebrated ARCH model. Finally our methods are calibrated and validated by simulations based on real intraday volatility curves.