IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v39y2007i2p253-260.html
   My bibliography  Save this article

Options trading driven by volatility directional accuracy

Author

Listed:
  • K. Maris
  • K. Nikolopoulos
  • K. Giannelos
  • V. Assimakopoulos

Abstract

Analysts have claimed over the last years that the volatility of an asset is caused solely by the random arrival of new information about the future returns from the underlying asset. It is a common belief that volatility is of great importance in finance and it is one of the critical factors determining option prices and consequently driving option-trading strategies. This article discusses an empirical option trading methodology based on efficient volatility direction forecasts. Although in most cases accurate volatility forecasts are hard to obtain, forecasting the direction is significantly easier. Increase in the directional accuracy leads to profitable investment strategies. The net gain is depended on the size of the changes as well; however successful volatility forecasts in terms of directional accuracy was found to be sufficient for positive results. In order to evaluate the proposed methodology weekly data from CAX40, DAX and the Greek FTSE/ASE 20 stock indices were used.

Suggested Citation

  • K. Maris & K. Nikolopoulos & K. Giannelos & V. Assimakopoulos, 2007. "Options trading driven by volatility directional accuracy," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 253-260.
  • Handle: RePEc:taf:applec:v:39:y:2007:i:2:p:253-260
    DOI: 10.1080/00036840500427999
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840500427999
    Download Restriction: Access to full text is restricted to subscribers.

    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. Bruce Grace, 2000. "Black-Scholes option pricing via genetic algorithms," Applied Economics Letters, Taylor & Francis Journals, vol. 7(2), pages 129-132.
    2. Assimakopoulos, V. & Nikolopoulos, K., 2000. "The theta model: a decomposition approach to forecasting," International Journal of Forecasting, Elsevier, vol. 16(4), pages 521-530.
    3. Andersen, Lars, 2002. "How Options Analysis Can Enhance Managerial Performance," European Management Journal, Elsevier, vol. 20(5), pages 505-511, October.
    4. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    5. Vicent AragO-Manzana & M Angeles Fernandezizquierdo, 2003. "Monthly seasonality of the returns and volatility of the IBEX-35 index and its futures contract," Applied Economics Letters, Taylor & Francis Journals, vol. 10(3), pages 129-133.
    6. Buckley, Adrian & Tse, Kalun & Rijken, Herbert & Eijgenhuijsen, Hans, 2002. "Stock Market Valuation with Real Options:: lessons from Netscape," European Management Journal, Elsevier, vol. 20(5), pages 512-526, October.
    7. Mohsen Bahmani-Oskooee, 2002. "Does black market exchange rate volatility deter the trade flows? Iranian experience," Applied Economics, Taylor & Francis Journals, vol. 34(18), pages 2249-2255.
    8. Carlos Bautista, 2005. "How volatile are East Asian stocks during high volatility periods?," Applied Economics Letters, Taylor & Francis Journals, vol. 12(5), pages 319-326.
    9. William Pedersen, 1998. "Capturing all the information in foreign currency option prices: solving for one versus two implied variables," Applied Economics, Taylor & Francis Journals, vol. 30(12), pages 1679-1683.
    10. Lux, T. & M. Marchesi, "undated". "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B 437, University of Bonn, Germany, revised Jul 1998.
    11. K. Maris & G. Pantou & K. Nikolopoulos & E. PagourtzI & V. Assimakopoulos, 2004. "A study of financial volatility forecasting techniques in the FTSE/ASE 20 index," Applied Economics Letters, Taylor & Francis Journals, vol. 11(7), pages 453-457.
    12. N'zue Fofana & B. Wade Brorsen, 2001. "GARCH option pricing with implied volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 8(5), pages 335-340.
    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. Her-Jiun Sheu & Yu-Chen Wei, 2011. "Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(2), pages 31-47, March.
    2. Konstantinos Nikolopoulos, 2010. "Forecasting with quantitative methods: the impact of special events in time series," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 947-955.
    3. Her-Jiun Sheu & Yu-Chen Wei, 2011. "Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(2), pages 31-47, March.
    4. Vicky Bamiatzi & Konstantinos Bozos & Konstantinos Nikolopoulos, 2010. "On the predictability of firm performance via simple time-series and econometric models: evidence from UK SMEs," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 279-282, February.

    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:taf:applec:v:39:y:2007:i:2:p:253-260. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.