Sharp L¹-approximation of the log-Heston stochastic differential equation by Euler-type methods

Annalena Mickel and Andreas Neuenkirch

Journal of Computational Finance

Abstract: We study the L1-approximation of the log-Heston stochastic differential equation at equidistant time points by Euler-type methods. We establish the convergence order 1/2 – ∊ for ∊ > 0 arbitrarily small if the Feller index v of the underlying Cox– Ingersoll–Ross process satisfies v > 1. Thus, we recover the standard convergence order of the Euler scheme for stochastic differential equations with globally Lipschitz coefficients. Moreover, we discuss the v ≥ 1 case and illustrate our findings with several numerical examples.

References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.risk.net/journal-of-computational-fina ... y-euler-type-methods (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rsk:journ0:7957030

Access Statistics for this article

More articles in Journal of Computational Finance from Journal of Computational Finance
Bibliographic data for series maintained by Thomas Paine ().