[PDF.71td] Principles of Neural Model Identification, Selection and Adequacy: With Applications to Financial Econometrics (Perspectives in Neural Computing)

Principles of Neural Model Identification, Selection and Adequacy: With Applications to Financial Econometrics (Perspectives in Neural Computing)

[PDF.fl75] Principles of Neural Model Identification, Selection and Adequacy: With Applications to Financial Econometrics (Perspectives in Neural Computing)

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 | #12016446 in Books |  Springer |  1999-05-28 |  1999-05-28 | Original language:English | PDF # 1 |  9.25 x.46 x6.10l,.68 | File type: PDF | 190 pages

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Neural networks have had considerable success in a variety of disciplines including engineering, control, and financial modelling. However a major weakness is the lack of established procedures for testing mis-specified models and the statistical significance of the various parameters which have been estimated. This is particularly important in the majority of financial applications where the data generating processes are dominantly stochastic and only partially determin...

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