Trading ebook Finance - Neural Prediction of Weekly Stock Market Index

It would be interesting to see how the network

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Unformatted text preview: the 1110th data point (January, 21st, 1994). It would be interesting to see how the network performs for these worst case examples, since, it would be expected to perform extremely well, when the training and testing data is in the same range. Fig. 1: S&P 500 index from 1972 through 1996 700 Crash October, 1986 600 S&P 500 index 500 400 300 200 Bull market since, Jan 1994 100 0 0 200 400 600 800 Data number 1000 1200 To test the network in these critical regions, it is trained using data from about 4 years prior to the crash of 1986 or the start of the 1994 bull run. For both these test cases, the network used has one hidden layer with 7 hidden neurons and 19 input neurons (input data plus a unity input for the offset). Weights are initialized to random values in the range [1,1]. The hidden and output layers use a sigmoidal activation function. While the offset for the hidden layer is provided by the fixed unity input of the 19th input neuron, there is no 11 offset for the sigmoids in the output layer. These test cases and t...
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This note was uploaded on 07/20/2012 for the course ECON 203 taught by Professor Girishdev during the Spring '12 term at Indian Institute of Technology, Kharagpur.

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