IDEAS home Printed from https://ideas.repec.org/a/ris/integr/0545.html
   My bibliography  Save this article

Hedging Effectiveness in Energy Market during Economic Crisis : Better Way to Integration

Author

Listed:
  • Samitas, Aristeidis

    () (University of the Aegean)

  • Tsakalos, Ioannis

    () (University of the Aegean)

Abstract

This paper investigates hedging and risk management options in the energy sector. Energy firms tend to adopt risk management tools in order to cover their financial exposure. Taking into consideration that current crisis has a significant effect on their value; we check whether energy firms actually have better output when they use hedging tools. In order to measure the effectiveness of this strategy in the energy industry, we adopt Tobin’s Q methodology. The sample of this study consists energy firms on a worldwide basis. The empirical evidence of this research confirms that energy firms may avoid huge economic problems when they adopt risk management methods. It is better enery market integration.

Suggested Citation

  • Samitas, Aristeidis & Tsakalos, Ioannis, 2011. "Hedging Effectiveness in Energy Market during Economic Crisis : Better Way to Integration," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 463-476.
  • Handle: RePEc:ris:integr:0545
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Rose, Andrew Kenan, 1988. " Is the Real Interest Rate Stable?," Journal of Finance, American Finance Association, vol. 43(5), pages 1095-1112, December.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, pages 85-110.
    4. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    5. David K. Backus & Stanley E. Zin, 1993. "Long-memory inflation uncertainty: evidence from the term structure of interest rates," Proceedings, Federal Reserve Bank of Cleveland, pages 681-708.
    6. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    7. Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, pages 427-449.
    8. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    9. L. A. Gil-Alana & P. M. Robinson, 2001. "Testing of seasonal fractional integration in UK and Japanese consumption and income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 95-114.
    10. L.A. Gil-Alanaa, 2007. "Testing The Existence of Multiple Cycles in Financial and Economic Time Series," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 1-20, May.
    11. Luis A. Gil-Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
    12. Chambers, Marcus J, 1998. "Long Memory and Aggregation in Macroeconomic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1053-1072, November.
    13. Christopher F. Baum & John T. Barkoulas & Mustafa Caglayan, 1999. "Persistence in International Inflation Rates," Southern Economic Journal, Southern Economic Association, vol. 65(4), pages 900-913, April.
    14. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, pages 131-159.
    15. Chung, Ching-Fan & Baillie, Richard T, 1993. "Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models," Empirical Economics, Springer, vol. 18(4), pages 791-806.
    16. Ashley, Richard, 1998. "A new technique for postsample model selection and validation," Journal of Economic Dynamics and Control, Elsevier, vol. 22(5), pages 647-665, May.
    17. Hyung, Namwon & Franses, Philip Hans & Penm, Jack, 2006. "Structural breaks and long memory in US inflation rates: Do they matter for forecasting?," Research in International Business and Finance, Elsevier, vol. 20(1), pages 95-110, March.
    18. Chung, Ching-Fan, 1996. "Estimating a generalized long memory process," Journal of Econometrics, Elsevier, vol. 73(1), pages 237-259, July.
    19. Christopher F. Baum & John Barkoulas, 2006. "Long-memory forecasting of US monetary indices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 291-302.
    20. Gil-Alana, Luis A., 2002. "Seasonal long memory in the aggregate output," Economics Letters, Elsevier, vol. 74(3), pages 333-337, February.
    21. Gil-Alaña, L. A. & Robinson, Peter M., 2001. "Testing of seasonal fractional integration in UK and Japanese consumption and income," LSE Research Online Documents on Economics 298, London School of Economics and Political Science, LSE Library.
    22. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    23. Barsky, Robert B., 1987. "The Fisher hypothesis and the forecastability and persistence of inflation," Journal of Monetary Economics, Elsevier, vol. 19(1), pages 3-24, January.
    24. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March.
    25. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    26. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
    27. Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 219-261.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Energy; Tobin’s Q; Hedging Effectiveness; Financial Crisis;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ris:integr:0545. 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: (Jong-Eun Lee). General contact details of provider: http://edirc.repec.org/data/desejkr.html .

    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 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.

    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.