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Testing Option Pricing Models

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  • David S. Bates

Abstract

This paper discusses the commonly used methods for testing option pricing models, including the Black-Scholes, constant elasticity of variance, stochastic volatility, and jump-diffusion models. Since options are derivative assets, the central empirical issue is whether the distributions implicit in option prices are consistent with the time series properties of the underlying asset prices. Three relevant aspects of consistency are discussed, corresponding to whether time series-based inferences and option prices agree with respect to volatility, changes in volatility, and higher moments. The paper surveys the extensive empirical literature on stock options, options on stock index futures, and options on currencies and currency futures.

Suggested Citation

  • David S. Bates, "undated". "Testing Option Pricing Models," Rodney L. White Center for Financial Research Working Papers 14-95, Wharton School Rodney L. White Center for Financial Research.
    • Handle: RePEc:fth:pennfi:14-95
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    Cited by:

    1. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    2. Koulisianis, M.D & Papatheodorou, T.S, 2000. "A ‘moving index’ method for the solution of the American options valuation problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(4), pages 373-381.
    3. Hwang, Soosung & Satchell, Stephen E., 2000. "Market risk and the concept of fundamental volatility: Measuring volatility across asset and derivative markets and testing for the impact of derivatives markets on financial markets," Journal of Banking & Finance, Elsevier, vol. 24(5), pages 759-785, May.
    4. Olkhov, Victor, 2019. "New Essentials of Economic Theory," MPRA Paper 95065, University Library of Munich, Germany.
    5. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    6. Bruno Feunou & Jean-Sébastien Fontaine & Roméo Tédongap, 2017. "Implied volatility and skewness surface," Review of Derivatives Research, Springer, vol. 20(2), pages 167-202, July.
    7. Bakshi, Gurdip S. & Zhiwu, Chen, 1997. "An alternative valuation model for contingent claims," Journal of Financial Economics, Elsevier, vol. 44(1), pages 123-165, April.
    8. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Kozarski, R., 2013. "Pricing and hedging in the VIX derivative market," Other publications TiSEM 221fefe0-241e-4914-b6bd-c, Tilburg University, School of Economics and Management.
    10. Alessandro Beber & Luca Erzegovesi, 1999. "Distribuzioni di probabilità implicite nei prezzi delle opzioni," Alea Tech Reports 008, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    11. Malz, Allan M., 1996. "Using option prices to estimate realignment probabilities in the European Monetary System: the case of sterling-mark," Journal of International Money and Finance, Elsevier, vol. 15(5), pages 717-748, October.
    12. Kim, Jungmu & Park, Yuen Jung & Ryu, Doojin, 2018. "Testing CEV stochastic volatility models using implied volatility index data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 224-232.
    13. Cem Aysoy & Ercan Balaban, 1996. "The Term Structure of Volatility in the Turkish Foreign Exchange : Implications for Option Pricing and Hedging Decisions," Discussion Papers 9613, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    14. Schmitt, Christian, 1996. "Option pricing using EGARCH models," ZEW Discussion Papers 96-20, ZEW - Leibniz Centre for European Economic Research.
    15. David Chambers & Rasheed Saleuddin, 2020. "Commodity option pricing efficiency before Black, Scholes, and Merton," Economic History Review, Economic History Society, vol. 73(2), pages 540-564, May.
    16. Kyriakos Chourdakis, 2000. "Stochastic Volatility and Jumps Driven by Continuous Time Markov Chains," Working Papers 430, Queen Mary University of London, School of Economics and Finance.
    17. Koekebakker, Steen & Lien, Gudbrand D., 2002. "Term Structure of Volatility and Price Jumps in Agricultural Markets - Evidence from Option Data," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24874, European Association of Agricultural Economists.
    18. Aurell, Erik & Baviera, Roberto & Hammarlid, Ola & Serva, Maurizio & Vulpiani, Angelo, 2000. "Growth optimal investment and pricing of derivatives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 280(3), pages 505-521.
    19. Olkhov, Victor, 2019. "New Essentials of Economic Theory III. Economic Applications," MPRA Paper 94053, University Library of Munich, Germany.
    20. Kyriakos Chourdakis, 2000. "Stochastic Volatility and Jumps Driven by Continuous Time Markov Chains," Working Papers 430, Queen Mary University of London, School of Economics and Finance.
    21. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    22. Duan, Jin-Chuan & Zhang, Hua, 2001. "Pricing Hang Seng Index options around the Asian financial crisis - A GARCH approach," Journal of Banking & Finance, Elsevier, vol. 25(11), pages 1989-2014, November.
    23. Gurdip S. Bakshi & Zhiwu Chen, "undated". "An Alternative Model for Contingent Claims," Research in Financial Economics 9504, Ohio State University.
    24. Emilio Barucci & Paul Malliavin & Maria Elvira Mancino & Roberto Renò & Anton Thalmaier, 2003. "The Price‐Volatility Feedback Rate: An Implementable Mathematical Indicator of Market Stability," Mathematical Finance, Wiley Blackwell, vol. 13(1), pages 17-35, January.

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