¹City University of Hong Kong, Hong Kong, China

Correspondence: MCS Wong, Department of Economics and Finance, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. E-mail: efmcw103@cityu.edu.hk

Received June 2007; Accepted January 2008; Published online 14 May 2008.

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).