IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2021-04-29.html
   My bibliography  Save this article

Futures Trading, Spot Price Volatility and Structural Breaks: Evidence from Energy Sector

Author

Listed:
  • Sanjeeta Shirodkar

    (Goa Business School, Goa University, Goa, 403206, India.)

  • Guntur Anjana Raju

    (Goa Business School, Goa University, Goa, 403206, India.)

Abstract

The present study empirically examines the impact of Stock Futures on India's underlying Energy Sector Stocks by incorporating the Structural breaks in the AR (1)-GARCH (1, 1) model. Although the issues relating to the effect of Derivatives trading on Cash Market Volatility have been empirically discussed in two ways: by evaluating Cash Market Volatilities during the Pre-and Post-Derivatives trading periods and, secondly, by determining the influence of Derivatives trading on the conduct of Cash Markets by comparing it with proxies. Nevertheless, these methodologies cannot isolate the influence of derivatives trading from the effects of other market reforms on the volatility of the underlying Cash Market. The study offers mixed results for the select sample of Energy sector stocks. However, there is evidence of a reduction in unconditional volatility for most energy sector stocks. The study's findings suggest that trading in Stock Futures may not necessarily be associated with the destabilization of the underlying Energy sector Stocks.

Suggested Citation

  • Sanjeeta Shirodkar & Guntur Anjana Raju, 2021. "Futures Trading, Spot Price Volatility and Structural Breaks: Evidence from Energy Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 230-239.
    • Handle: RePEc:eco:journ2:2021-04-29
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/11086/5915
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/11086/5915
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 33-55, March.
    2. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    3. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    4. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    5. repec:bla:jfinan:v:44:y:1989:i:5:p:1155-75 is not listed on IDEAS
    6. Cox, John C & Ross, Stephen A, 1976. "A Survey of Some New Results in Financial Option Pricing Theory," Journal of Finance, American Finance Association, vol. 31(2), pages 383-402, May.
    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. Manivannan Babu & A. Antony Lourdesraj & Gayathri Jayapal & G. Indhumathi & J. Sathya, 2022. "Effect of COVID-19 Pandemic on NSE Nifty Energy Index," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 141-145, July.

    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. David McMillan & Mark Wohar, 2011. "Structural breaks in volatility: the case of UK sector returns," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1079-1093.
    2. Hillebrand, Eric & Schnabl, Gunther & Ulu, Yasemin, 2009. "Japanese foreign exchange intervention and the yen-to-dollar exchange rate: A simultaneous equations approach using realized volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 490-505, July.
    3. Ewing, Bradley T. & Malik, Farooq, 2016. "Volatility spillovers between oil prices and the stock market under structural breaks," Global Finance Journal, Elsevier, vol. 29(C), pages 12-23.
    4. Josep Lluís Carrion-i-Silvestre & Andreu Sansó, 2023. ""Generalized Extreme Value Approximation to the CUMSUMQ Test for Constant Unconditional Variance in Heavy-Tailed Time Series"," IREA Working Papers 202309, University of Barcelona, Research Institute of Applied Economics, revised Jul 2023.
    5. Alaa Abi Morshed & Elena Andreou & Otilia Boldea, 2018. "Structural Break Tests Robust to Regression Misspecification," Econometrics, MDPI, vol. 6(2), pages 1-39, May.
    6. Omotosho, Babatunde S., 2012. "Endogenous Structural Breaks and Real Exchange Rate Determination in Nigeria since Interbank Foreign Exchange Market (IFEM)," MPRA Paper 98306, University Library of Munich, Germany.
    7. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    8. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    9. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    10. Adnen Ben Nasr & Ahdi Noomen Ajmi & Rangan Gupta, 2014. "Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model," Applied Financial Economics, Taylor & Francis Journals, vol. 24(14), pages 993-1004, July.
    11. Mansour Khalili Araghi & Majid Mirzaee Ghazani, 2015. "Abrupt Changes in Volatility: Evidence from TEPIX Index in Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(3), pages 377-393, Autumn.
    12. Andreu Sansó & Vicent Aragó & Josep Lluís Carrion, 2003. "Testing for Changes in the Unconditional Variance of Financial Time Series," DEA Working Papers 5, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    13. Arago-Manzana, Vicent & Fernandez-Izquierdo, Maria Angeles, 2007. "Influence of structural changes in transmission of information between stock markets: A European empirical study," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 112-124, April.
    14. Helena Veiga, 2007. "Are Feedback Factors Important in Modeling Financial Data?," International Review of Finance, International Review of Finance Ltd., vol. 7(3‐4), pages 105-118, September.
    15. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "Crude oil price behaviour before and after military conflicts and geopolitical events," Energy, Elsevier, vol. 120(C), pages 79-91.
    16. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    17. Kim, Moosup & Lee, Taewook & Noh, Jungsik & Baek, Changryong, 2014. "Quasi-maximum likelihood estimation for multiple volatility shifts," Statistics & Probability Letters, Elsevier, vol. 86(C), pages 50-60.
    18. Broto, Carmen, 2011. "Inflation targeting in Latin America: Empirical analysis using GARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1424-1434, May.
    19. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research.
    20. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.

    More about this item

    Keywords

    Stock Futures; Volatility modelling; ICSS test; AR (1)-GARCH (1; 1); Structural Breaks; Futures trading; Energy Sector;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:eco:journ2:2021-04-29. 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: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    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.