Predicting Stock Market Index Trading Signals Using Neural Networks
نویسندگان
چکیده
This study forecasts trading signals of the Australian All Ordinary Index (AORD), one day ahead. These forecasts were based on the current day’s relative return of the Close price of the US S&P 500 Index, the UK FTSE 100 Index, French CAC 40 Index and German DAX Index as well as the AORD. The forecasting techniques examined were feedforward and probabilistic neural networks. Performance of the networks was evaluated by using classification/misclassification rate and trading simulations. For both evaluation criteria, feedforward neural networks performed better. Trading simulations suggested that the predicted trading signals are useful for short term traders.
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