Financial risk forecasting with nonlinear dynamics and support vector regression

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)685-695
Journal / PublicationJournal of the Operational Research Society
Issue number5
Publication statusPublished - May 2009


We propose a dynamical description of financial time series capable of making short-term prediction utilizing support vector regression on neighbourhood points. We include in our analysis estimation on the uncertainty by capturing the exogenous from historical prediction errors and adopting a probabilistic description of the prediction. Evidences from a series of backtesting using financial time series indicate that our model provides accurate description of real market data comparable with GARCH(1,1). © 2009 Operational Research Society Ltd. All rights reserved.

Research Area(s)

  • Deterministic system, Forecast, Nonlinear dynamics, Support vector regression