Semi-closed form prices of barrier options in the time-dependent CEV and CIR models

Peter Carr, Andrey Itkin, Dmitry Muravey

Research output: Contribution to journalArticlepeer-review

Abstract

The authors continue a series of articles where prices of the barrier options written on the underlying, whose dynamics follow a one-factor stochastic model with time-dependent coefficients and the barrier, are obtained in semi-closed form; see Carr and Itkin (2020) and Itkin and Muravey (2020). This article extends this methodology to the Cox-Ingersoll-Ross model for zero-coupon bonds and to the constant elasticity of variance model for stocks, which are used as the corresponding underlying for the barrier options. The authors describe two approaches. One is a generalization of the method of heat potentials (for the heat equation) to the Bessel process, so it is named “the method of Bessel potentials.” The authors also propose a general scheme for constructing the potential method for any linear differential operator with time-independent coefficients. The second approach is the method of generalized integral transform, which is also extended to the Bessel process. In all cases, a semi-closed solution means that first, we need to numerically solve a linear Volterra equation of the second kind, and then the option price is represented as a one-dimensional integral. The authors demonstrate that their method is computationally more efficient than both the backward and forward finite difference methods, while providing better accuracy and stability. Also, it is shown that these methods do not duplicate, but instead they complement each other, as one provides very accurate results at shorter maturities and the other provides such results at longer maturities.

Original languageEnglish (US)
Pages (from-to)26-50
Number of pages25
JournalJournal of Derivatives
Volume28
Issue number1
DOIs
StatePublished - Sep 2020

Keywords

  • Options
  • Statistical methods

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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