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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Approximating stochastic volatility by recombinant trees |
| Organization Unit | |
| Authors |
|
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Annals of Applied Probability |
| Publisher | Institute of Mathematical Statistics |
| Geographical Reach | international |
| ISSN | 1050-5164 |
| Volume | 24 |
| Number | 5 |
| Page Range | 2176 - 2205 |
| Date | 2014 |
| Abstract Text | A general method to construct recombinant tree approximations for stochastic volatility models is developed and applied to the Heston model for stock price dynamics. In this application, the resulting approximation is a four tuple Markov process. The first two components are related to the stock and volatility processes and take values in a two-dimensional binomial tree. The other two components of the Markov process are the increments of random walks with simple values in {−1,+1}. The resulting efficient option pricing equations are numerically implemented for general American and European options including the standard put and calls, barrier, lookback and Asian-type pay-offs. The weak and extended weak convergences are also proved. |
| Free access at | DOI |
| Official URL | https://doi.org/10.1214/13-AAP977 |
| Digital Object Identifier | 10.1214/13-AAP977 |
| Other Identification Number | merlin-id:20846 |
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