IDEAS home Printed from https://ideas.repec.org/p/arx/papers/cond-mat-0404684.html
   My bibliography  Save this paper

Option pricing with fractional volatility

Author

Listed:
  • Rui Vilela Mendes
  • Maria Joao Oliveira

Abstract

Based on empirical market data, a stochastic volatility model is proposed with volatility driven by fractional noise. The model is used to obtain a risk-neutrality option pricing formula and an option pricing equation.

Suggested Citation

  • Rui Vilela Mendes & Maria Joao Oliveira, 2004. "Option pricing with fractional volatility," Papers cond-mat/0404684, arXiv.org.
  • Handle: RePEc:arx:papers:cond-mat/0404684
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/cond-mat/0404684
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    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. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010. "Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
    2. Yu Wang & Haicheng Shu, 2019. "Evaluating the Performance of Factor Pricing Models for Different Stock Market Trends: Evidence from China," Working Papers 2019-10-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    3. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    4. Muniandy, Sithi V. & Uning, Rosemary, 2006. "Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 585-598.
    5. Liudas Giraitis & Piotr Kokoszka & Remigijus Leipus & Gilles Teyssière, 2000. "Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity," Statistical Inference for Stochastic Processes, Springer, vol. 3(1), pages 113-128, January.
    6. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is What? A Simple Time-Domain Test of Long-memory vs. Structural Breaks," Working Papers 258, Barcelona School of Economics.
    7. Ruggero Grilli & Gabriele Tedeschi & Mauro Gallegati, 2015. "Markets connectivity and financial contagion," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 287-304, October.
    8. Anders Tolver Jensen & Theis Lange, 2009. "On IGARCH and convergence of the QMLE for misspecified GARCH models," CREATES Research Papers 2009-06, Department of Economics and Business Economics, Aarhus University.
    9. Nazarian, Rafik & Gandali Alikhani, Nadiya & Naderi, Esmaeil & Amiri, Ashkan, 2013. "Forecasting Stock Market Volatility: A Forecast Combination Approach," MPRA Paper 46786, University Library of Munich, Germany.
    10. Arthur J. Lin & Hai-Yen Chang, 2020. "Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    11. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    12. Alicia Garcia-Herrero & Eric Girardin & Hermann Gonzalez, 2017. "Analyzing the Impact of Monetary Policy on Financial Markets in Chile," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 32(1), pages 3-21, April.
    13. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
    14. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    15. Kaiwen Hou, 2023. "Adaptive Bayesian Learning with Action and State-Dependent Signal Variance," Papers 2311.12878, arXiv.org, revised Nov 2023.
    16. Grossmann, Axel & Orlov, Alexei G., 2022. "Exchange rate misalignments, capital flows and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    17. David McMillan & Alan Speight, 2006. "Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(13), pages 959-972.
    18. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
    19. Ibrahim A. ONOUR & Bruno S. SERGI, 2011. "Modeling and forecasting volatility in global food commodity prices," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 57(3), pages 132-139.
    20. Menelaos Karanasos, "undated". "The Covariance Structure of Mixed ARMA Models," Discussion Papers 00/11, Department of Economics, University of York.

    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:cond-mat/0404684. 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.