Approximation Theory and Neural Networks
نویسنده
چکیده
In many practical situations, one needs to construct a model for an input/output process. For example, one is interested in the price of a stock five years from now. The rating industry description for the stock typically lists such indicators as the increase in the price over the last year, the last 5 years, 10 years, life of the stock, P/E ratio, and alpha and beta risk factors. The buyer is expected to (but instructed not to!) believe that the price of the stock depends upon these parameters. Of course, no one knows a precise formula to compute this price as a closed form function of the parameters, but only has available data on the many stocks traded on the market. The general situation is as in Figure 1. In general, the model Pf has to be constructed
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