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Implementing option pricing models when asset returns follow an autoregressive moving average process

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  • Wang, Chou-Wen
  • Wu, Chin-Wen
  • Tzang, Shyh-Weir

Abstract

Motivated by the empirical findings that asset returns or volatilities are predictable, this paper studies the pricing of European options on stock or volatility, the instantaneous changes of which depend upon an autoregressive moving average (ARMA) process. The pricing formula of an ARMA-type option is similar to that of Black and Scholes, except that the total volatility input depends upon the AR and MA parameters. From numerical analyses, the option values are increasing functions of the levels of AR or MA parameters across all moneyness levels. Specifically, the AR effect is more significant than the MA effect. Finally, based on the daily closing prices of TAIEX options from 2004 to 2008, the ad hoc ARMA(1,1) model provides the best in-sample fit and the second best out-of-sample fit, whereas the variance gamma model provides the second best in-sample fit and the best out-of-sample fit. Therefore, both variance gamma model and ad hoc ARMA model are superior models for pricing TAIEX options.

Suggested Citation

  • Wang, Chou-Wen & Wu, Chin-Wen & Tzang, Shyh-Weir, 2012. "Implementing option pricing models when asset returns follow an autoregressive moving average process," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 8-25.
    • Handle: RePEc:eee:reveco:v:24:y:2012:i:c:p:8-25
    DOI: 10.1016/j.iref.2011.12.003
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    1. Dilip B. Madan & Peter P. Carr & Eric C. Chang, 1998. "The Variance Gamma Process and Option Pricing," Review of Finance, European Finance Association, vol. 2(1), pages 79-105.
    2. Lo, Andrew W & Wang, Jiang, 1995. "Implementing Option Pricing Models When Asset Returns Are Predictable," Journal of Finance, American Finance Association, vol. 50(1), pages 87-129, March.
    3. Athanassios N. Avramidis & Pierre L'Ecuyer, 2006. "Efficient Monte Carlo and Quasi-Monte Carlo Option Pricing Under the Variance Gamma Model," Management Science, INFORMS, vol. 52(12), pages 1930-1944, December.
    4. Bruce D. Grundy, "undated". "Option Prices and the Underlying Asset's Return Distribution (Reprint 012)," Rodney L. White Center for Financial Research Working Papers 11-91, Wharton School Rodney L. White Center for Financial Research.
    5. Roll, Richard, 1977. "An analytic valuation formula for unprotected American call options on stocks with known dividends," Journal of Financial Economics, Elsevier, vol. 5(2), pages 251-258, November.
    6. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
    7. Grunbichler, Andreas & Longstaff, Francis A., 1996. "Valuing futures and options on volatility," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 985-1001, July.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Madan, Dilip B & Seneta, Eugene, 1990. "The Variance Gamma (V.G.) Model for Share Market Returns," The Journal of Business, University of Chicago Press, vol. 63(4), pages 511-524, October.
    10. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    11. Harrison, J. Michael & Pliska, Stanley R., 1981. "Martingales and stochastic integrals in the theory of continuous trading," Stochastic Processes and their Applications, Elsevier, vol. 11(3), pages 215-260, August.
    12. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," The Journal of Business, University of Chicago Press, vol. 61(4), pages 409-425, October.
    13. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    14. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    15. Bruce N. Lehmann, 1990. "Fads, Martingales, and Market Efficiency," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(1), pages 1-28.
    16. Jérôme Detemple & Carlton Osakwe, 2000. "The Valuation of Volatility Options," Review of Finance, European Finance Association, vol. 4(1), pages 21-50.
    17. Kittiakarasakun, Jullavut & Tse, Yiuman, 2011. "Modeling the fat tails in Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 20(3), pages 430-440, June.
    18. Chopra, Navin & Lakonishok, Josef & Ritter, Jay R., 1992. "Measuring abnormal performance : Do stocks overreact?," Journal of Financial Economics, Elsevier, vol. 31(2), pages 235-268, April.
    19. Szu‐Lang Liao & Chao‐Chun Chen, 2006. "The valuation of European options when asset returns are autocorrelated," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(1), pages 85-102, January.
    20. A. Ronald Gallant & Chien-Te Hsu & George Tauchen, 1999. "Using Daily Range Data To Calibrate Volatility Diffusions And Extract The Forward Integrated Variance," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 617-631, November.
    21. J. Michael Harrison & Stanley R. Pliska, 1981. "Martingales and Stochastic Integrals in the Theory of Continous Trading," Discussion Papers 454, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    22. Dimitris Psychoyios & George Skiadopoulos, 2006. "Volatility options: Hedging effectiveness, pricing, and model error," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(1), pages 1-31, January.
    23. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    24. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    25. Grundy, R.D., 1991. "Option Prices and the Underlying Asset's Return Distribution," Weiss Center Working Papers 11-91, Wharton School - Weiss Center for International Financial Research.
    26. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    27. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    28. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    29. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
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    More about this item

    Keywords

    ARMA process; Option pricing; Martingale;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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