Convertible bond pricing with partial integro-differential equation model

Xiaofeng Yang, Jinping Yu, Mengna Xu and Wenjing Fan

Mathematics and Computers in Simulation (MATCOM), 2018, vol. 152, issue C, 35-50

Abstract: In this paper, we introduce the concept of Exponential Variance Gamma (EVG) model to the valuation of convertible bond (CB). Rather than evaluating derivatives with standard Black–Scholes approach, we describe the dynamic underlying asset log price with VG process, which is one of classical Lévy processes with non-normal distribution but skewness and leptokurtosis. For numerical purpose, we develop a discrete scheme with stability and convergence, which combines so-called multi-stage compound-option model (MCO) and explicit–implicit difference method (EXIM) to discretize the partial integro-differential equation (PIDE). By comparing our results with Black–Scholes approach, we can show that because of the ability to capture skewness and leptokurtosis features, the new approach does provide a lower price for the valuation of CB.

Keywords: Convertible bond; Exponential variance gamma model; Geometric Brownian Motion; Partial integro-differential equation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475418300910
Full text for ScienceDirect subscribers only

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:eee:matcom:v:152:y:2018:i:c:p:35-50

DOI: 10.1016/j.matcom.2018.04.005

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().