An efficient Monte Carlo simulation for new uncertain Heston–CIR hybrid model
| Autor: | Behrouz Fathi-Vajargah, Mohammad Mirzazadeh, Sara Ghasemalipour |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Computer science Differential equation Monte Carlo method Computational intelligence 02 engineering and technology Theoretical Computer Science Option value 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Applied mathematics 020201 artificial intelligence & image processing Call option Geometry and Topology Hybrid model Software |
| Zdroj: | Soft Computing. 25:8539-8547 |
| ISSN: | 1433-7479 1432-7643 |
| DOI: | 10.1007/s00500-021-05702-8 |
| Popis: | In this paper, we consider two new stock models in which their differential equations are modeled by Liu process in uncertain environment. Firstly, we study the uncertain Schobel–Zhu–Hull–White hybrid model and obtain its closed European call option pricing using Liu calculus. Also, we solve this model by Monte Carlo simulation to ensure the performance of Monte Carlo method. Our main purpose is to present a new model, uncertain Heston–CIR hybrid model, in which its uncertain differential equations cannot be solved and so we can calculate the option value via Monte Carlo simulation. Finally, some examples are stated for illustrating these models to obtain successful results and show the efficiency of Monte Carlo method. |
| Databáze: | OpenAIRE |
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