Generalized cox-ross-rubinstein binomial models

San Lin Chung*, Pai Ta Shih

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

24 Scopus citations

Abstract

This paper generalizes the seminal Cox-Ross-Rubinstein (CRR) binomial model by adding a stretch parameter. The generalized CRR (GCRR) model allows us to fine-tune (via the stretch parameter) the lattice structure so as to efficiently price a range of options, such as barrier options. Our analysis provides insights into the fine structure of convergence of the general binomial model to the Black-Scholes formula. We also discuss how to improve the rate of convergence or the oscillatory behavior of the GCRR model. The numerical results suggest that the GCRR models with various modifications are efficient for pricing a range of options.

Original languageEnglish
Pages (from-to)508-520
Number of pages13
JournalManagement Science
Volume53
Issue number3
DOIs
StatePublished - 03 2007
Externally publishedYes

Keywords

  • Barrier option
  • Binomial model
  • Monotonic convergence
  • Rate of convergence
  • Smooth convergence
  • Trinomial model

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