IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1908.03007.html
   My bibliography  Save this paper

Anomalous diffusions in option prices: connecting trade duration and the volatility term structure

Author

Listed:
  • Antoine Jacquier
  • Lorenzo Torricelli

Abstract

Anomalous diffusions arise as scaling limits of continuous-time random walks (CTRWs) whose innovation times are distributed according to a power law. The impact of a non-exponential waiting time does not vanish with time and leads to different distribution spread rates compared to standard models. In financial modelling this has been used to accommodate for random trade duration in the tick-by-tick price process. We show here that anomalous diffusions are able to reproduce the market behaviour of the implied volatility more consistently than usual L\'evy or stochastic volatility models. We focus on two distinct classes of underlying asset models, one with independent price innovations and waiting times, and one allowing dependence between these two components. These two models capture the well-known paradigm according to which shorter trade duration is associated with higher return impact of individual trades. We fully describe these processes in a semimartingale setting leading no-arbitrage pricing formulae, and study their statistical properties. We observe that skewness and kurtosis of the asset returns do not tend to zero as time goes by. We also characterize the large-maturity asymptotics of Call option prices, and find that the convergence rate is slower than in standard L\'evy regimes, which in turn yields a declining implied volatility term structure and a slower decay of the skew.

Suggested Citation

  • Antoine Jacquier & Lorenzo Torricelli, 2019. "Anomalous diffusions in option prices: connecting trade duration and the volatility term structure," Papers 1908.03007, arXiv.org, revised Apr 2020.
  • Handle: RePEc:arx:papers:1908.03007
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1908.03007
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    2. Cartea, Álvaro & del-Castillo-Negrete, Diego, 2007. "Fractional diffusion models of option prices in markets with jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(2), pages 749-763.
    3. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    4. Leif Andersen & Alexander Lipton, 2012. "Asymptotics for Exponential Levy Processes and their Volatility Smile: Survey and New Results," Papers 1206.6787, arXiv.org.
    5. Chakrabarty, Arijit & Meerschaert, Mark M., 2011. "Tempered stable laws as random walk limits," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 989-997, August.
    6. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    7. Álvaro Cartea & Thilo Meyer-Brandis, 2010. "How Duration Between Trades of Underlying Securities Affects Option Prices," Review of Finance, European Finance Association, vol. 14(4), pages 749-785.
    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. Álvaro Cartea, 2013. "Derivatives pricing with marked point processes using tick-by-tick data," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 111-123, January.
    2. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 91-114, March.
    3. Henryk Gurgul & Robert Syrek & Christoph Mitterer, 2016. "Price duration versus trading volume in high-frequency data for selected DAX companies," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 17(2), pages 241-260.
    4. Torricelli, Lorenzo, 2020. "Trade duration risk in subdiffusive financial models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    5. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    6. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Dionne, Georges & Pacurar, Maria & Zhou, Xiaozhou, 2015. "Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 202-219.
    8. Álvaro Cartea & Thilo Meyer-Brandis, 2010. "How Duration Between Trades of Underlying Securities Affects Option Prices," Review of Finance, European Finance Association, vol. 14(4), pages 749-785.
    9. David Easley & Robert F. Engle & Maureen O'Hara & Liuren Wu, 2008. "Time-Varying Arrival Rates of Informed and Uninformed Trades," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 171-207, Spring.
    10. Ping-Hung Chou & Pei-Shan Wu & Teng-Tsai Tu, 2014. "The Impact of Trader Behavior on Options Price Volatility," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(4), pages 503-516, April.
    11. Yang, Joey Wenling, 2011. "Transaction duration and asymmetric price impact of trades--Evidence from Australia," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 91-102, January.
    12. Simonsen, Ola, 2006. "The Impact of News Releases on Trade Durations in Stocks -Empirical Evidence from Sweden," Umeå Economic Studies 688, Umeå University, Department of Economics.
    13. Maria Pacurar, 2008. "Autoregressive Conditional Duration Models In Finance: A Survey Of The Theoretical And Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 711-751, September.
    14. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    15. Wong, Woon K. & Tan, Dijun & Tian, Yixiang, 2009. "Informed trading and liquidity in the Shanghai Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 66-73, March.
    16. Mengyu Zhang & Thanos Verousis & Iordanis Kalaitzoglou, 2022. "Information and the arrival rate of option trading volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 605-644, April.
    17. Simonsen, Ola, 2006. "Stock Data, Trade Durations, And Limit Order Book Information," Umeå Economic Studies 689, Umeå University, Department of Economics.
    18. Engle, Robert F. & Patton, Andrew J., 2004. "Impacts of trades in an error-correction model of quote prices," Journal of Financial Markets, Elsevier, vol. 7(1), pages 1-25, January.
    19. Cartea, Álvaro & Karyampas, Dimitrios, 2011. "Volatility and covariation of financial assets: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3319-3334.
    20. Karaa, Rabaa & Slim, Skander & Hmaied, Dorra Mezzez, 2018. "Trading intensity and the volume-volatility relationship on the Tunis Stock Exchange," Research in International Business and Finance, Elsevier, vol. 44(C), pages 88-99.

    More about this item

    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:arx:papers:1908.03007. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.