A0442
Title: Modeling and forecasting the co-movement of international yield curve drivers
Authors: Maria Sprincenatu - Sofine, Meag Munich Ergo AssetManagement GmbH (Germany) [presenting]
Stefan Mittnik - Ludwig Maximilians University Munich (Germany)
Abstract: New data-driven state-space models are developed to forecast the co-movement of yield curve drivers of different world regions. The models are designed to preserve the dynamic properties of the yield curve drivers embodied in their underlying data generation processes. The models allow forecasting the co-movement of yield curves of different world regions by forecasting their drivers. Using actively traded government bond yields for the US and Germany, it is shown that the models outperform both the domestic and the global Diebold-Li models at long forecast horizons. It is also shown that the curvature does have predictive power for short forecast horizons.
