Financial risk forecasting with nonlinear dynamics and support vector regression

H K K Tung () and Michael Wong
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H K K Tung: City University of Hong Kong

Journal of the Operational Research Society, 2009, vol. 60, issue 5, 685-695

Abstract: Abstract 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).

Keywords: deterministic system; nonlinear dynamics; support vector regression; forecast (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1057/palgrave.jors.2602594

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