Trading ebook Finance - Neural Prediction of Weekly Stock Market Index

The value of the faz index is predicted for the next

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Unformatted text preview: irst order difference. The value of the FAZ index is predicted for the next week based on this data. The network is trained using data for the past M weeks and is then tested based on data for the next L weeks, where M is called the training window and L is called the testing window. For successive prediction, the windows are moved ahead and the network is retrained. Three different networks are compared each having a different set of inputs, one of which has only the last 10 FAZ index values as the input. It is seen that the network fed with technical indicator data performs better than the one trained only on past index values. Normalization of training data is done so as to keep the data within 0.1 and 0.9, however, the normalization method is not given. This approach is particularly suitable to the aim of this project and is hence, used as the basic method in this project with certain modifications. Radial basis function approach Komo, Chang and Ko [8] use a radial basis function network to predict the future stock index values based on past data of the index and other technical indicators such as transaction costs, bond market valu...
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