On an efficient multiple time step Monte Carlo simulation of the SABR model
| Autor: | Lech A. Grzelak, Cornelis W. Oosterlee, A. Leitao Rodriguez |
|---|---|
| Přispěvatelé: | Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands |
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
Monte Carlo method 01 natural sciences Hybrid Monte Carlo 010104 statistics & probability Stochastic collocation 0502 economics and business Applied mathematics Copulas Quasi-Monte Carlo method 0101 mathematics Mathematics 050208 finance Monte Carlo methods for option pricing 05 social sciences Monte Carlo methods Fourier techniques Exotic options SABR model Dynamic Monte Carlo method Monte Carlo method in statistical physics Monte Carlo integration Exact simulation General Economics Econometrics and Finance Finance Monte Carlo molecular modeling |
| Zdroj: | Quantitative Finance, 17(10) Quantitative Finance, 17(10), 1549-1565 |
| ISSN: | 1469-7696 1469-7688 |
| DOI: | 10.1080/14697688.2017.1301676 |
| Popis: | In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math. Comput. 2017, 293, 461–479], for pricing European options in the context of the model calibration. A highly efficient method results, with many very interesting and nontrivial components, like Fourier inversion for the sum of log-normals, stochastic collocation, Gumbel copula, correlation approximation, that are not yet seen in combination within a Monte Carlo simulation. The present multiple time step Monte Carlo method is especially useful for long-term options and for exotic options. |
| Databáze: | OpenAIRE |
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