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Alternative Methods to Derive Option Pricing Models

  • Cheng-Few LeeEmail author
  • Hong-Yi Chen
  • John Lee
Chapter

Abstract

The main purposes of this paper are: (1) to review three alternative methods for deriving option pricing models, (2) to discuss the relationship between binomial option pricing model and Black–Scholes model, (3) to compare Cox et al. method and Rendleman and Bartter method for deriving Black–Scholes model, (4) to discuss lognormal distribution method to derive Black–Scholes model, and (5) to show how the Black–Scholes model can be derived by stochastic calculus. This paper shows that the main methodologies used to derive the Black–Scholes model are: binomial distribution, lognormal distribution, and differential and integral calculus. If we assume risk neutrality, then we do not need stochastic calculus to derive the Black–Scholes model. However, the stochastic calculus approach for deriving the Black–Scholes model is still presented in this chapter. In sum, this paper can help statisticians and mathematicians understand how alternative methods can be used to derive the Black–Scholes option pricing model.

Keywords

Binomial option pricing model Black–Scholes option pricing model Lognormal distribution method Stochastic calculus 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Finance and Economics, Rutgers Business SchoolRutgers UniversityPiscatawayUSA
  2. 2.Department of FinanceNational Chengchi UniversityTaipeiTaiwan
  3. 3.Center for PBBEF ResearchMorris PlainsUSA

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