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Efficient Option Pricing in Crisis Based on Dynamic Elasticity of Variance Model

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  • Congyin Fan
  • Kaili Xiang
  • Peimin Chen

Abstract

Market crashes often appear in daily trading activities and such instantaneous occurring events would affect the stock prices greatly. In an unstable market, the volatility of financial assets changes sharply, which leads to the fact that classical option pricing models with constant volatility coefficient, even stochastic volatility term, are not accurate. To overcome this problem, in this paper we put forward a dynamic elasticity of variance (DEV) model by extending the classical constant elasticity of variance (CEV) model. Further, the partial differential equation (PDE) for the prices of European call option is derived by using risk neutral pricing principle and the numerical solution of the PDE is calculated by the Crank‐Nicolson scheme. In addition, Kalman filtering method is employed to estimate the volatility term of our model. Our main finding is that the prices of European call option under our model are more accurate than those calculated by Black‐Scholes model and CEV model in financial crashes.

Suggested Citation

  • Congyin Fan & Kaili Xiang & Peimin Chen, 2016. "Efficient Option Pricing in Crisis Based on Dynamic Elasticity of Variance Model," Discrete Dynamics in Nature and Society, John Wiley & Sons, vol. 2016(1).
  • Handle: RePEc:wly:jnddns:v:2016:y:2016:i:1:n:7496539
    DOI: 10.1155/2016/7496539
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    References listed on IDEAS

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    1. Marc Chesney & Robert J. Elliott & Dilip Madan & Hailiang Yang, 1993. "Diffusion Coefficient Estimation and Asset Pricing When Risk Premia and Sensitivities Are Time Varying1," Mathematical Finance, Wiley Blackwell, vol. 3(2), pages 85-99, April.
    2. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," The Journal of Business, University of Chicago Press, vol. 47(2), pages 244-280, April.
    3. Marc Chesney & Robert J. Elliott & Dilip Madan & Hailiang Yang, 1993. "Diffusion coefficient estimation and asset pricing when risk premia and sensitivities are time varying," Working Papers hal-00610777, HAL.
    4. Cox, John C. & Ross, Stephen A., 1976. "The valuation of options for alternative stochastic processes," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 145-166.
    5. Fabrizio Lillo & Rosario N. Mantegna, 2001. "Power law relaxation in a complex system: Omori law after a financial market crash," Papers cond-mat/0111257, arXiv.org, revised Jun 2003.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. Finucane, Thomas J., 1989. "Black-Scholes Approximations of Call Option Prices with Stochastic Volatilities: A Note," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(4), pages 527-532, December.
    8. Yoon, Ji-Hun, 2015. "Pricing perpetual American options under multiscale stochastic elasticity of variance," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 14-26.
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