DocumentCode
2075595
Title
Do-ahead replaces run-time: a neural network forecasts options volatility
Author
Malliaris, Mary ; Salchenberger, Linda
Author_Institution
Dept. of Manage. Sci., Loyola Univ., Chicago, IL, USA
fYear
1994
fDate
1-4 Mar 1994
Firstpage
480
Lastpage
481
Abstract
Compares three methods of estimating the volatility of daily S&P 100 Index stock market options. The implied volatility, calculated via the Black-Scholes model, is currently the most popular method of estimating volatility and is used by traders in the pricing of options. Historical volatility has been used to predict the implied volatility, but the estimates are poor predictors. A neural network for predicting volatility is shown to be far superior to the historical method
Keywords
finance; neural nets; stock markets; Black-Scholes model; do-ahead method; historical volatility; implied volatility prediction; neural network; options pricing; run-time method; stock market options volatility; stock market traders; Calendars; Economic forecasting; Forward contracts; History; Input variables; Motion measurement; Neural networks; Predictive models; Pricing; Runtime;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence for Applications, 1994., Proceedings of the Tenth Conference on
Conference_Location
San Antonia, TX
Print_ISBN
0-8186-5550-X
Type
conf
DOI
10.1109/CAIA.1994.323630
Filename
323630
Link To Document