IDEAS home Printed from https://ideas.repec.org/a/bla/finrev/v37y2002i1p93-104.html
   My bibliography  Save this article

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

Author

Listed:
  • Mohammad Najand

Abstract

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH‐class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH‐M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.

Suggested Citation

  • Mohammad Najand, 2002. "Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models," The Financial Review, Eastern Finance Association, vol. 37(1), pages 93-104, February.
    • Handle: RePEc:bla:finrev:v:37:y:2002:i:1:p:93-104
    DOI: 10.1111/1540-6288.00006
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1540-6288.00006
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1540-6288.00006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manh Ha Nguyen & Olivier Darné, 2018. "Forecasting and risk management in the Vietnam Stock Exchange," Working Papers halshs-01679456, HAL.
    2. Francesco Guidi, 2009. "Volatility and Long-Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK," The IUP Journal of Financial Economics, IUP Publications, vol. 0(2), pages 7-39, June.
    3. Čermák, M. & Malec, K. & Maitah, M., 2017. "Price Volatility Modelling – Wheat: GARCH Model Application," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(4).
    4. Ana Filipa Carvalho & Jose Sa da Costa & Jose Assis Lopes, 2006. "A systematic modelling strategy for futures markets volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 819-833.
    5. Stéphane Yen & Ming-Hsiang Chen, 2010. "Open interest, volume, and volatility: evidence from Taiwan futures markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 34(2), pages 113-141, April.
    6. Ezzat, Hassan, 2012. "The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns During Massive Shocks: The Empirical Case of Egypt," MPRA Paper 50530, University Library of Munich, Germany.
    7. Kam C. Chan & Louis T. W. Cheng & Peter P. Lung, 2005. "Asymmetric Volatility and Trading Activity in Index Futures Options," The Financial Review, Eastern Finance Association, vol. 40(3), pages 381-407, August.
    8. Ashish Kumar, 2015. "Impact of Currency Futures on Volatility in Exchange Rate," Paradigm, , vol. 19(1), pages 95-108, June.
    9. Ezzat, Hassan, 2012. "The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange," MPRA Paper 51584, University Library of Munich, Germany.

    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:bla:finrev:v:37:y:2002:i:1:p:93-104. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/efaaaea.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.