On rational pricing of derivative securities for a familiy of non-Gaussian processes

  • Linear and non-linear analogues of the Black-Scholes equation are derived when shocks can be described by a truncated Lévy process. A linear equation is derived under the perfect correlation assumption on returns for a derivative security and a stock, and its solutions for European put and call options are obtained. It is also shown that the solution violates the perfect correlation assumption unless a process is gaussian. Thus, for a family of truncated Lévy distributions, the perfect hedging is impossible even in the continuous time limit. A second linear analogue of the Black-Scholes equation is obtained by constructing a portfolio which eliminates fluctuations of the first order and assuming that the portfolio is risk-free; it is shown that this assumption fails unless a process is gaussian. It is shown that the di erence between solutions to the linear analogues of the Black-Scholes equations and solutions to the Black-Scholes equations are sizable. The equations and solutions can be written in a discretized approximate formLinear and non-linear analogues of the Black-Scholes equation are derived when shocks can be described by a truncated Lévy process. A linear equation is derived under the perfect correlation assumption on returns for a derivative security and a stock, and its solutions for European put and call options are obtained. It is also shown that the solution violates the perfect correlation assumption unless a process is gaussian. Thus, for a family of truncated Lévy distributions, the perfect hedging is impossible even in the continuous time limit. A second linear analogue of the Black-Scholes equation is obtained by constructing a portfolio which eliminates fluctuations of the first order and assuming that the portfolio is risk-free; it is shown that this assumption fails unless a process is gaussian. It is shown that the di erence between solutions to the linear analogues of the Black-Scholes equations and solutions to the Black-Scholes equations are sizable. The equations and solutions can be written in a discretized approximate form which uses an observed probability distribution only. Non-linear analogues for the Black-Scholes equation are derived from the non-arbitrage condition, and approximate formulas for solutions of these equations are suggested. Assuming that a linear generalization of the Black-Scholes equation holds, we derive an explicit pricing formula for the perpetual American put option and produce numerical results which show that the difference between our result and the classical Merton's formula obtained for gaussian processes can be substantial. Our formula uses an observed distribution density, under very weak assumptions on the latter.show moreshow less

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Metadaten
Author details:Sergei Z. Levendorskii, Svetlana I. Boyarchenko
URN:urn:nbn:de:kobv:517-opus-25196
Publication series (Volume number):Preprint ((1998) 07)
Publication type:Preprint
Language:English
Publication year:1998
Publishing institution:Universität Potsdam
Release date:2008/10/30
RVK - Regensburg classification:SI 990
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
DDC classification:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
Collection(s):Universität Potsdam / Schriftenreihen / Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partielle Differentialgleichungen und Komplexe Analysis
Universität Potsdam / Schriftenreihen / Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partielle Differentialgleichungen und Komplexe Analysis / 1998
License (German):License LogoKeine öffentliche Lizenz: Unter Urheberrechtsschutz
External remark:
Die Printversion kann in der Universitätsbibliothek Potsdam eingesehen werden:
Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partielle Differentialgleichungen und Komplexe Analysis, 1997-

Die Online-Fassung wird auf der Homepage des Instituts für Mathematik veröffentlicht.

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