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Hedging derivative securities with genetic programming

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  • Shu‐Heng Chen
  • Wo‐Chiang Lee
  • Chia‐Hsuan Yeh

Abstract

One of the most recent applications of GP to finance is to use genetic programming to derive option pricing formulas. Earlier studies take the Black–Scholes model as the true model and use the artificial data generated by it to train and to test GP. The aim of this paper is to provide some initial evidence of the empirical relevance of GP to option pricing. By using the real data from S&P 500 index options, we train and test our GP by distinguishing the case in‐the‐money from the case out‐of‐the‐money. Unlike most empirical studies, we do not evaluate the performance of GP in terms of its pricing accuracy. Instead, the derived GP tree is compared with the Black–Scholes model in its capability to hedge. To do so, a notion of tracking error is taken as the performance measure. Based on the post‐sample performance, it is found that in approximately 20% of the 97 test paths GP has a lower tracking error than the Black–Scholes formula. We further compare our result with the ones obtained by radial basis functions and multilayer perceptrons and one‐stage GP. Copyright © 1999 John Wiley & Sons, Ltd.

Suggested Citation

  • Shu‐Heng Chen & Wo‐Chiang Lee & Chia‐Hsuan Yeh, 1999. "Hedging derivative securities with genetic programming," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 8(4), pages 237-251, December.
    • Handle: RePEc:wly:isacfm:v:8:y:1999:i:4:p:237-251
    DOI: 10.1002/(SICI)1099-1174(199912)8:43.0.CO;2-J
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    References listed on IDEAS

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    1. Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
    2. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    3. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    4. Mark Rubinstein., 1994. "Implied Binomial Trees," Research Program in Finance Working Papers RPF-232, University of California at Berkeley.
    5. Rubinstein, Mark, 1985. "Nonparametric Tests of Alternative Option Pricing Models Using All Reported Trades and Quotes on the 30 Most Active CBOE Option Classes from August 23, 1976 through August 31, 1978," Journal of Finance, American Finance Association, vol. 40(2), pages 455-480, June.
    6. Houthakker, Hendrik S. & Williamson, Peter J., 1996. "The Economics of Financial Markets," OUP Catalogue, Oxford University Press, number 9780195044072.
    7. 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.
    8. Rubinstein, Mark, 1994. "Implied Binomial Trees," Journal of Finance, American Finance Association, vol. 49(3), pages 771-818, July.
    9. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
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    Cited by:

    1. Daniel E. O'Leary, 2010. "Intelligent Systems in Accounting, Finance and Management: ISI journal and proceeding citations, and research issues from most‐cited papers," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(1), pages 41-58, January.
    2. Julia Bennell & Charles Sutcliffe, 2004. "Black–Scholes versus artificial neural networks in pricing FTSE 100 options," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 243-260, October.
    3. Daniel E. O'Leary, 2009. "Downloads and citations in Intelligent Systems in Accounting, Finance and Management," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 21-31, January.

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