IDEAS home Printed from https://ideas.repec.org/a/wsi/rpbfmp/v15y2012i01ns0219091511500032.html
   My bibliography  Save this article

New Insights on the Implied and Realized Volatility Relation

Author

Listed:
  • Lloyd P. Blenman

    (University of North Carolina-Charlotte, Belk College of Business, Charlotte, NC 28223, USA)

  • Guan Jun Wang

    (Florida A&M University, School of Business and Industry, Tallahassee, FL 32307, USA)

Abstract

Existing studies on the informational content of at-the-money implied volatility (ATMIV) and past realized volatility (PRV) and the relation between the two have mainly focused on a single short forecast horizon and conclude that ATMIV outperforms PRV. We examine the relation between implied and realized volatility over both short and longer forecasting horizons to provide a forecasting competition. We analytically demonstrate the option maturity effect on the sensitivity of the implied volatility (IV) estimation. As time to maturity increases, vega increases but at a decreasing rate, up to$\overline{T}$. At shorter (longer) maturities, small pricing changes should have greater (smaller) corrective impact on IVs. We find that IV outperforms PRV over a one month forecast horizon. However, as the forecast horizon increases, PRV outperforms IV and subsumes the information contained in it. These mixed results may be attributed to the reduced efficiency of longer dated sections of the S&P 500 options index market we analyze.

Suggested Citation

  • Lloyd P. Blenman & Guan Jun Wang, 2012. "New Insights on the Implied and Realized Volatility Relation," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 1-22.
    • Handle: RePEc:wsi:rpbfmp:v:15:y:2012:i:01:n:s0219091511500032
    DOI: 10.1142/S0219091511500032
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219091511500032
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219091511500032?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ederington, Louis H. & Guan, Wei, 2010. "Longer-Term Time-Series Volatility Forecasts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 1055-1076, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Yam Wing Siu, 2020. "Impact of Expected Shortfall Approach on Capital Requirement Under Basel," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-34, January.
    2. Leonidas S. Rompolis & Elias Tzavalis, 2017. "Retrieving risk neutral moments and expected quadratic variation from option prices," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 955-1002, May.
    3. Yam Wing Siu, 2018. "Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-48, June.
    4. Oleg Sokolinskiy, 2020. "Conditional dependence in post-crisis markets: dispersion and correlation skew trades," Review of Quantitative Finance and Accounting, Springer, vol. 55(2), pages 389-426, August.

    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. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    2. Ederington, Louis H. & Guan, Wei, 2010. "How asymmetric is U.S. stock market volatility?," Journal of Financial Markets, Elsevier, vol. 13(2), pages 225-248, May.
    3. Vogel, Harold L. & Werner, Richard A., 2015. "An analytical review of volatility metrics for bubbles and crashes," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 15-28.
    4. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2022. "Forecasting realized volatility of agricultural commodities," International Journal of Forecasting, Elsevier, vol. 38(1), pages 74-96.
    5. Eling, Martin & Jung, Kwangmin, 2020. "Risk aggregation in non-life insurance: Standard models vs. internal models," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 183-198.
    6. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    7. Jordan French, 2016. "Back to the Future Betas: Empirical Asset Pricing of US and Southeast Asian Markets," IJFS, MDPI, vol. 4(3), pages 1-13, July.
    8. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    9. Naqvi, Syed Muhammad Waqar Azeem & Rizvi, Syed Kumail Abbas & Orangzab & Ali, Muhammad, 2016. "Value at Risk at Asian Emerging Stock Markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(3), pages 311-319.
    10. Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
    11. Sudhi SHARMA & Miklesh YADAV, 2020. "Analyzing the robustness of ARIMA and neural networks as a predictive model of crude oil prices," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(623), S), pages 289-300, Summer.
    12. Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.

    More about this item

    Keywords

    Option; implied volatility; realized volatility; forecasting; informational content; vega;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance

    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:wsi:rpbfmp:v:15:y:2012:i:01:n:s0219091511500032. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/rpbfmp/rpbfmp.shtml .

    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.