DocumentCode
2748752
Title
Neural networks models for the prediction of stock return volatility
Author
Catfolis, Thierry
Author_Institution
Dept. of Chem. Eng., Katholieke Univ., Leuven, Heverlee, Belgium
Volume
4
fYear
1996
fDate
3-6 Jun 1996
Firstpage
2118
Abstract
In this paper we will focus on the use of artificial neural networks (ANNs) for the prediction of stock return volatilities. This stock return volatility is an important and unknown parameter in the Black and Scholes formulas (1973) for the calculation of the value of stock options. We will demonstrate that it is feasible to implement a NARMAX-like structure with neural networks, and to use this architecture for predicting the stock return volatility
Keywords
autoregressive moving average processes; neural nets; stock markets; NARMAX-like structure; artificial neural networks; neural network models; stock option values; stock return volatility prediction; Artificial neural networks; Autoregressive processes; Chemical engineering; Delay lines; Expert systems; Finance; Mathematical model; Neural networks; Predictive models; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.549229
Filename
549229
Link To Document