IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/17415.html
   My bibliography  Save this paper

Tests d'arbitrage et surfaces de volatilité : analyse empirique sur données haute fréquence
[Arbitrage tests and surface of implied volatility: An empirical analysis of high frequency data]

Author

Listed:
  • Ardia, David

Abstract

This MSc thesis proposes the analysis of high frequency ODAX options during October 2001. It consists of three chapters investigating respectively market activity, arbitrage opportunities and performance of various implied volatility surfaces.

Suggested Citation

  • Ardia, David, 2002. "Tests d'arbitrage et surfaces de volatilité : analyse empirique sur données haute fréquence [Arbitrage tests and surface of implied volatility: An empirical analysis of high frequency data]," MPRA Paper 17415, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:17415
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/17415/1/MPRA_paper_17415.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    2. Evnine, Jeremy & Rudd, Andrew, 1985. "Index Options: The Early Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 743-756, July.
    3. Kamara, Avraham & Miller, Thomas W., 1995. "Daily and Intradaily Tests of European Put-Call Parity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(4), pages 519-539, December.
    4. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    5. Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
    6. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    7. R. L. Brown & S. A. Easton, 1992. "Empirical Evidence on Put-Call Parity in Australia: A Reconciliation and Further Evidence," Australian Journal of Management, Australian School of Business, vol. 17(1), pages 11-19, June.
    8. 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.
    9. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    10. Wiggins, James B., 1987. "Option values under stochastic volatility: Theory and empirical estimates," Journal of Financial Economics, Elsevier, vol. 19(2), pages 351-372, December.
    11. 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.
    12. Bernard Dumas & Jeff Fleming & Robert E. Whaley, 1998. "Implied Volatility Functions: Empirical Tests," Journal of Finance, American Finance Association, vol. 53(6), pages 2059-2106, December.
    13. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    14. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    2. Guidolin, Massimo & Timmermann, Allan, 2003. "Option prices under Bayesian learning: implied volatility dynamics and predictive densities," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 717-769, March.
    3. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    4. Cheng Few Lee & Yibing Chen & John Lee, 2020. "Alternative Methods to Derive Option Pricing Models: Review and Comparison," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 102, pages 3573-3617, World Scientific Publishing Co. Pte. Ltd..
    5. Mondher Bellalah, 2009. "Derivatives, Risk Management & Value," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7175.
    6. Jurczenko, Emmanuel & Maillet, Bertrand & Negrea, Bogdan, 2002. "Revisited multi-moment approximate option pricing models: a general comparison (Part 1)," LSE Research Online Documents on Economics 24950, London School of Economics and Political Science, LSE Library.
    7. Christoffersen, Peter & Heston, Steven & Jacobs, Kris, 2010. "Option Anomalies and the Pricing Kernel," Working Papers 11-17, University of Pennsylvania, Wharton School, Weiss Center.
    8. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    9. Siddiqi, Hammad, 2013. "Analogy Making, Option Prices, and Implied Volatility," MPRA Paper 48862, University Library of Munich, Germany.
    10. Siddiqi, Hammad, 2015. "Anchoring Heuristic in Option Pricing," MPRA Paper 63218, University Library of Munich, Germany.
    11. Jianhui Li & Sebastian A. Gehricke & Jin E. Zhang, 2019. "How do US options traders “smirk” on China? Evidence from FXI options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1450-1470, November.
    12. 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.
    13. Christoffersen, Peter & Jacobs, Kris & Ornthanalai, Chayawat & Wang, Yintian, 2008. "Option valuation with long-run and short-run volatility components," Journal of Financial Economics, Elsevier, vol. 90(3), pages 272-297, December.
    14. Lin, Sha & He, Xin-Jiang, 2021. "A closed-form pricing formula for forward start options under a regime-switching stochastic volatility model," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    15. Giulia Di Nunno & Kk{e}stutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From constant to rough: A survey of continuous volatility modeling," Papers 2309.01033, arXiv.org, revised Sep 2023.
    16. Siddiqi, Hammad, 2015. "Anchoring Heuristic in Option Pricing," Risk and Sustainable Management Group Working Papers 207677, University of Queensland, School of Economics.
    17. Kim, In Joon & Park, Gun Youb, 2006. "An empirical comparison of implied tree models for KOSPI 200 index options," International Review of Economics & Finance, Elsevier, vol. 15(1), pages 52-71.
    18. Hilliard, Jitka, 2013. "Testing Greeks and price changes in the S&P 500 options and futures contract: A regression analysis," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 51-58.
    19. Xue-Zhong He & Lei Shi, 2016. "A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs," Published Paper Series 2016-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    20. Hu, May & Park, Jason, 2019. "Valuation of collateralized debt obligations: An equilibrium model," Economic Modelling, Elsevier, vol. 82(C), pages 119-135.

    More about this item

    Keywords

    Option; test d'arbitrage; surface; volatilité implicite; haute fréquence;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:17415. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.