Neural Networks for Economic and Financial Mode Lling
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Nova Science Publishers Inc | 2010 | 76 pages | ISBN-13: 9781616686796 | ISBN-10: 1616686790 | You save 20%
Neural Networks for Economic and Financial Mode Lling new edition
Download free books for Credit Rating Modelling By Neural Networks Hajek, Peter
author peter hajek format paperback language english publication year 18 08 2010 subject management business economics industry subject 2 business accounting vocational textbooks study guides title credit rating modelling by neural networks author hajek peter publisher nova science pub inc publication date jul 01 2010 pages 76 binding paperback dimensions 6 00 wx 8 75 hx 0 25 d isbn 1616686790 subject business economics finance brand new paperback all orders get full access to our online statu
The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class
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 mode
"Today s financial markets are characterised by a large number of participants, with different appetites for risk, different time horizons, different motivations and reactions to unexpected news. The mathematical techniques and models used in the forecasting of financial markets have therefore grown ever more sophisticated as traders, analysts and investors seek to gain an edge on their competitors. Written by leading international researchers and practitioners, this book focuses on three major themes of today s state of the art financial research: modelling with high frequency data, the infor
Neural Networks for Economic and Financial Mode Lling Textbook
