C++ Neural Networks and Fuzzy Logic: Preface


  Three−Month Treasury Bill Yield 2



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C neural networks and fuzzy logic

1.  Three−Month Treasury Bill Yield

2.  30−Year Treasury Bond Yield

3.  NYSE Advancing/Declining issues

4.  NYSE New Highs/New Lows

5.  S&P 500 closing price

C++ Neural Networks and Fuzzy Logic:Preface

Choosing a Network Architecture

306



Raw data for the period from January 4, 1980 to October 28, 1983 is taken as the training period, for a total of

200 weeks of data. The following 50 weeks are kept on reserve for a test period to see if the predictions are

valid outside of the training interval. The last date of this period is October 19, 1984. Let’s look at the raw

data now. (You get data on the disk available with this book that covers the period from January, 1980 to

December, 1992.) In Figures 14.3 through 14.5, you will see a number of these indicators plotted over the

training plus test intervals:



  Figure 14.3 shows you the S&P 500 stock index.

Figure 14.3

  The S&P 500 Index for the period of interest.



  Figure 14.4 shows long−term bonds and short−term 3−month T−bill interest rates.

Figure 14.4

  Long−term and short−term interest rates.



  Figure 14.5 shows some breadth indicators on the NYSE, the number of advancing stocks/number

of declining stocks, as well as the ratio of new highs to new lows on the NYSE



Figure 14.5

  Breadth indicators on the NYSE: Advancing/Declining issues and New Highs/New

Lows.

A sample of a few lines looks like the following data in Table 14.1. Note that the order of parameters is the



same as listed above.

Table 14.1 Raw Data


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