Pricing vulnerable options with constant elasticity of variance versus stochastic elasticity of variance

Min Ku Lee, Sung Jin Yang, Jeong Hoon Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In order to handle option writer’s credit risk, a different underlying price model is required beyond the well-known Black-Scholes model. This paper adopts a recently developed model, which characterizes the 2007-2009 global financial crisis in a unique way, to determine the no-arbitrage price of European options vulnerable to writer’s default possibility. The underlying model is based on the randomization of the elasticity of variance parameter capturing the leverage or inverse leverage effect. We obtain an analytic formula explicitly for the stochastic elasticity of variance correction to the Black-Scholes price of vulnerable options and show how the correction effect is compared with the one given by the constant elasticity of variance model. The result can help to design a dynamic investment strategy reducing option writer’s credit risk more effectively.

Original languageEnglish
Pages (from-to)233-247
Number of pages15
JournalEconomic Computation and Economic Cybernetics Studies and Research
Volume51
Issue number1
Publication statusPublished - 2017

Bibliographical note

Funding Information:
The research of M.-K. Lee was supported by National Research Foundation of Korea NRF-2016R1D1A3B03933060 and Brain Korea 21 plus Mathematical Science Team for Global Women Leaders. The research of J.-H. Kim was supported by the National Research Foundation of Korea NRF-2016K2A9A1A01951934.

Funding Information:
The research of M.-K. Lee was supported byNational Research Foundation of Korea NRF-2016R1D1A3B03933060 and Brain Korea 21 plus Mathematical Science Team for Global Women Leaders. The research of J.-H. Kim was supported by the National Research Foundation of Korea NRF-2016K2A9A1A01951934.

Publisher Copyright:
© 2017, Bucharest University of Economic Studies. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics
  • Computer Science Applications
  • Applied Mathematics

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