Estimating the Inverse Function of Compound Options Pricing Model Using Artificial Neural Networks
| dc.contributor.author | Hasanabadi, Hamed Shafiee | |
| dc.contributor.author | Mayorga, Rene V. | |
| dc.date.accessioned | 2014-05-20T15:45:13Z | |
| dc.date.available | 2014-05-20T15:45:13Z | |
| dc.date.issued | 2014-05-20 | |
| dc.description.abstract | Compound options are second order derivatives which give their holders the right for exercising over other derivatives. They are options on options. Compound options have many financial applications. Pricing methods for exotic options such as compounds are much more complex than the regular options. There are different models for pricing compound options. Simulating direct function of compound option pricing model based on the Black-Scholes model needs 7 input variables including current underlying asset price, basic option strike price, the time to expiration of the basic option, the volatility of the underlying asset price, the risk-free interest rate, compound option strike price, and time to expiration of the compound option. | en_US |
| dc.description.authorstatus | Faculty | en_US |
| dc.description.peerreview | yes | en_US |
| dc.identifier.uri | https://hdl.handle.net/10294/5320 | |
| dc.language.iso | en | en_US |
| dc.subject | Black-Scholes model | en_US |
| dc.subject | Artificial Neural Networks | en_US |
| dc.title | Estimating the Inverse Function of Compound Options Pricing Model Using Artificial Neural Networks | en_US |
| dc.type | Report | en_US |