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Option Pricing And Executive Stock Option Incentives: An Empirical Investigation Under General Error Distribution Stochastic Volatility Model

Author

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  • MIN PAN

    (School of Economics and Management, Wuhan University, Wuhan, Hubei 430072, P. R. China)

  • SHENGQIAO TANG

    (School of Economics and Management, Wuhan University, Wuhan, Hubei 430072, P. R. China)

Abstract

This article investigates the valuation of executive stock options when the stock return volatility is governed by the general error distribution stochastic volatility model, involving both the features of the stock return volatility and the abnormal fluctuations of the stock price at the expiration date. We estimate the parameters in the general error distribution stochastic volatility model using the Markov Chain Monte Carlo method with Shanghai & Shenzhen 300 Index in China as a sample, and compare the executive stock option values calculated by Black-Scholes option pricing model and the option pricing model under general error distribution stochastic volatility model. The results show that the general error distribution stochastic volatility model has greater veracity in describing the volatility of stock market returns, and there is divergence between the two values estimated by Black-Scholes option pricing model and the option pricing model under general error distribution stochastic volatility model. The divergence varies with the discrepancy between the price of underlying stock at the granting date and the strike price of the option.

Suggested Citation

  • Min Pan & Shengqiao Tang, 2011. "Option Pricing And Executive Stock Option Incentives: An Empirical Investigation Under General Error Distribution Stochastic Volatility Model," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 28(01), pages 81-93.
  • Handle: RePEc:wsi:apjorx:v:28:y:2011:i:01:n:s0217595911003065
    DOI: 10.1142/S0217595911003065
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    Cited by:

    1. Shuang Xiao & Guo Li & Yunjing Jia, 2017. "Estimating the Constant Elasticity of Variance Model with Data-Driven Markov Chain Monte Carlo Methods," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-23, February.

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