DocumentCode
3334811
Title
Bond rating: a nonconservative application of neural networks
Author
Dutta, Soumitra ; Shekhar, Shashi
Author_Institution
Div. of Comput. Sci., California Univ., Berkeley, CA, USA
fYear
1988
fDate
24-27 July 1988
Firstpage
443
Abstract
The authors apply neural networks to a generalization problem of predicting the ratings of corporate bonds, where conventional mathematical modeling techniques have yielded poor results and it is difficult to build rule-based artificial-intelligence systems. The results indicate that neural nets are a useful approach to generalization problems in such nonconservative domains, performing much better than mathematical modeling techniques like regression.<>
Keywords
neural nets; stock markets; bond rating; corporate bonds; neural networks; nonconservative application; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1988., IEEE International Conference on
Conference_Location
San Diego, CA, USA
Type
conf
DOI
10.1109/ICNN.1988.23958
Filename
23958
Link To Document