This project will result in fundamental advances in non-linear time series modelling and forecasting. It will suggests the possible class of various modelling techniques incorporating soft computing techniques and non-linear statistical modelling for forecasting Australian stock data, Australian foreign exchange rate data, currency data and other economic, financial and environmental time series data.

The significance of this research is that it will:

· determine a methodology for selecting stocks/indices that have a higher probability of providing abnormal returns,

· contribute to the understanding of how chaos theory and artificial intelligence/soft computing methods can be applied to financial time series forecasting, and

· assist in the understanding and the determination of the appropriate forecasting methods to use for making financial decisions involving forecasting,

· formalize a methodology in the design of a hybrid financial trading system that can make abnormal returns for a given amount of risk.

Prof. Clarence N W Tan

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