Trading ebook Finance - Neural Prediction of Weekly Stock Market Index

1 with 10 different values for a a 01 for the index

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Unformatted text preview: nd averages are all normalized using eq. (1), with 10 different values for A (A = 0.1 for the index and the averages and is = 0.02 for the absolute value of the 3 first order differences). The interest rates fluctuate about a certain value and there is no cumulative or time integral effect on their behavior, hence, the interest rates are not detrended and these are normalized using simple linear normalization. The same applies for the absolute difference of the interest rates. All the trends have a value of either 0.8, 0.2 or 0.0 and as such don’t need further normalization. This completes the data normalization for the neural network. The same techniques and constants are used for any other range of training and testing data. 4. Test results The neural network was trained using standard backpropagation for 2 different test cases, which are of critical interest from the point of view of desired performance. Fig. 1 shows the variation of the S&P 500 index and is reproduced below for ready reference. It can be seen that there is a big market crash around the 730th data point (October, 10th, 1986) and there is a strong bull market beginning around...
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