Option valuation based on the neural regression model
Expert Systems with Applications: An International Journal
Intelligent technologies for investing: a review of engineering literature
Intelligent Decision Technologies
A Simple Method of Forecasting Option Prices Based on Neural Networks
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
European Option Pricing by Using the Support Vector Regression Approach
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Training a Neural Logic Network to predict financial returns: a case study
International Journal of Electronic Finance
A fuzzy time series-based neural network approach to option price forecasting
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
Application notes: dynamic physical behavior analysis for financial trading decision support
IEEE Computational Intelligence Magazine
A learning-based contrarian trading strategy via a dual-classifier model
ACM Transactions on Intelligent Systems and Technology (TIST)
Pricing options in hong kong market based on neural networks
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Pricing And Hedging Short Sterling Options Using Neural Networks
International Journal of Intelligent Systems in Accounting and Finance Management
Dilemmas in knowledge-based evolutionary computation for financial investing
Intelligent Decision Technologies
| Hi-index | 0.00 |
In the past decade, many studies across various financial markets have shown conventional option pricing models to be inaccurate. To improve their accuracy, various researchers have turned to artificial neural networks (ANNs). In this work a neural network is constrained in such a way that pricing must be rational at the option-pricing boundaries. The constraints serve to change the regression surface of the ANN so that option pricing accuracy is improved in the locale of the boundaries. These constraints lead to statistically and economically significant out-performance, relative to both the most accurate conventional and nonconventional option pricing models.