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| Title: | Can neural networks learn the Black-Scholes model? A simplified approach |
| Author/Artist: |
Hamid, Shaikh A.
Habib, Abraham |
| Date: | 2005 |
| Abstract/Description: | Neural networks have been shown to learn complex relationships. It would be interesting to see if the networks can be trained to learn the nonlinear relationship underlying Black-Scholes type models. Interesting hypothetical questions that can be raised are: If option pricing model had not been developed, could a technique like neural networks have learnt the nonlinear form of the Black-Scholes type model to yield the fair value of an option? Could the networks have learnt to produce efficient implied volatility estimates? Our results from a simplified neural networks approach are rather encouraging, but more for volatility outputs than for call prices. |
| Description: | Version of Record |
| Subject: |
Black-Scholes model
neural networks implied volatility |
| Citation Link: | http://hdl.handle.net/10474/1662 |
| APA Citation: | Hamid, S. A. & Habib, A. (2005). Can neural networks learn the Black-Scholes model? A simplified approach (Working Paper No. 2005-01). Southern New Hampshire University, Center for Financial Studies. |