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Principles of Model Identification, Selection and Adequacy
Zapranis, Achilleas; Refenes, Apostolos-Paul N.
€ 126.92
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Description for Principles of Model Identification, Selection and Adequacy
paperback. Based on developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into a financial econometrics tool for non-parametric modelling. It provides the theoretical framework and uses neural networks for complex financial phenomena. Series: Perspectives in Neural Computing. Num Pages: 199 pages, 34 black & white illustrations, biography. BIC Classification: KCH; KFF; UGK; UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 10. Weight in Grams: 320.
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 deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the ... Read more
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 deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the ... Read more
Product Details
Format
Paperback
Publication date
1999
Publisher
Springer London Ltd United Kingdom
Number of pages
199
Condition
New
Series
Perspectives in Neural Computing
Number of Pages
190
Place of Publication
England, United Kingdom
ISBN
9781852331399
SKU
V9781852331399
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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