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Hermite Binomial Trees: A Novel Technique for Derivatives Pricing

Leccadito, Arturo, Toscano, Pietro, Tunaru, Radu (2012) Hermite Binomial Trees: A Novel Technique for Derivatives Pricing. International Journal of Theoretical and Applied Finance, 15 (8). pp. 1-36. ISSN 0219-0249. (doi:10.1142/S0219024912500586) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1142/S0219024912500586

Abstract

Edgeworth binomial trees were applied to price contingent claims when the underlying return distribution is skewed and leptokurtic, but with the limitation of working only for a limited set of skewness and kurtosis values. Recently, Johnson binomial trees were introduced to accommodate any skewness-kurtosis pair, but with the drawback of numerical convergence issues in some cases. Both techniques may suffer from non-exact matching of the moments of distribution of returns. A solution to this limitation is proposed here based on a new technique employing Hermite polynomials to match exactly the required moments. Several numerical examples illustrate the superior performance of the Hermite polynomials technique to price European and American options in the context of jump-diffusion and stochastic volatility frameworks and options with underlying asset given by the sum of two lognormally distributed random variables.

Item Type: Article
DOI/Identification number: 10.1142/S0219024912500586
Uncontrolled keywords: Option pricing; binomial trees; Hermite expansion; skewness and kurtosis.
Subjects: H Social Sciences > HG Finance
Divisions: Faculties > Social Sciences > Kent Business School > Accounting and Finance
Depositing User: Cathy Norman
Date Deposited: 18 Jan 2013 10:16 UTC
Last Modified: 29 May 2019 09:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/33016 (The current URI for this page, for reference purposes)
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