Prediction in chaotic time series: methods and comparisons with an application to financial intra-day data |
| |
Authors: | D Guégan L Mercier |
| |
Institution: | 1. ENSAE-CREST , Malakoff Cedex, France guegan@ecogest.ens-cachan.fr;3. CREST Laboratoire de statistique , Malakoff Cedex, France |
| |
Abstract: | Different prediction methods for chaotic deterministic systems are compared. Two methods of reconstructing the dynamics of the systems are considered with a view to producing a profitable trading model. The methods developed are the ‘nearest neighbours’ method and the ‘radial basis functions’ method. The optimal prediction horizon according to the sampling time step, and a reliable method to measure the prediction error are discussed. These methods are applied to the intra-day series of exchange rates, namely DEM/FRF. Developments concerning the importance of noise when chaotic systems are studied are provided. |
| |
Keywords: | Chaotic systems nearest neighbors prediction radial basis functions |
|
|