Option Pricing Under a Mixed-Exponential Jump Diffusion Model
This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exp...
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| Veröffentlicht in: | Management science Jg. 57; H. 11; S. 2067 - 2081 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Hanover, MD
INFORMS
01.11.2011
Institute for Operations Research and the Management Sciences |
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| ISSN: | 0025-1909, 1526-5501 |
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| Abstract | This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models, because the mixed-exponential distribution can approximate
any
distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day.
This paper was accepted by Michael Fu, stochastic models and simulation. |
|---|---|
| AbstractList | This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models,, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. [PUBLICATION ABSTRACT] This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. This paper was accepted by Michael Fu, stochastic models and simulation. This paper aims to extend the analytical tractability of the Black–Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. This paper was accepted by Michael Fu, stochastic models and simulation. This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models,, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. Key words: jump diffusion; mixed-exponential distributions; lookback options; barrier options; Merton's normal jump diffusion model; first passage times History: Received December 30, 2008; accepted May 1, 2011, by Michael Fu, stochastic models and simulation. Published online in Articles in Advance August 12, 2011. This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing models, such as hyperexponential and double-exponential jump diffusion models, because the mixed-exponential distribution can approximate any distribution as closely as possible, including the normal distribution and various heavy-tailed distributions. The mixed-exponential jump diffusion model can lead to analytical solutions for Laplace transforms of prices and sensitivity parameters for path-dependent options such as lookback and barrier options. The Laplace transforms can be inverted via the Euler inversion algorithm. Numerical experiments indicate that the formulae are easy to implement and accurate. The analytical solutions are made possible mainly because we solve a high-order integro-differential equation explicitly. A calibration example for SPY options shows that the model can provide a reasonable fit even for options with very short maturity, such as one day. Reprinted by permission of the Institute for Operations Research and Management Science (INFORMS) |
| Audience | Trade Academic |
| Author | Cai, Ning Kou, S. G. |
| Author_xml | – sequence: 1 givenname: Ning surname: Cai fullname: Cai, Ning – sequence: 2 givenname: S. G. surname: Kou fullname: Kou, S. G. |
| BackLink | http://www.econis.eu/PPNSET?PPN=681262109$$DView this record in ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24771737$$DView record in Pascal Francis |
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| Keywords | Euler equation Exponential distribution Differential equation Black Scholes model Gaussian distribution Inversion Modeling jump diffusion mixed-exponential distributions Stock exchange Pricing Diffusion process Jump process barrier options Integrodifferential equation Analytical solution Mixed distribution Heavy tail Calibration Mean estimation Weighting first passage times lookback options Mixed model Merton's normal jump diffusion model First passage time Distribution tail Laplace transformation Financial option Tariffication Maturity |
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| Snippet | This paper aims to extend the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely,... This paper aims to extend the analytical tractability of the Black–Scholes model to alternative models with arbitrary jump size distributions. More precisely,... |
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| SubjectTerms | Algorithms Alternative approaches Applications Applied sciences Approximation Asset pricing barrier options Calibration Call options Diffusion index Diffusion models Distribution Distribution theory Economic models European option Exact sciences and technology Experimental economics Experiments first passage times Insurance, economics, finance jump diffusion Jump diffusion model Laplace transformation Laplace transforms lookback options Management science Mathematical economics Mathematical models Mathematics Merton's normal jump diffusion model Microelectromechanical systems mixed-exponential distributions Modeling Monte Carlo methods Normal distribution Operational research and scientific management Operational research. Management science Option pricing Options (Finance) Portfolio theory Prices Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Securities prices Size distribution Statistics Stochastic models Studies |
| Title | Option Pricing Under a Mixed-Exponential Jump Diffusion Model |
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