IDEAS home Printed from https://ideas.repec.org/p/ind/igiwpp/2012-016.html
   My bibliography  Save this paper

Regulations and price discovery: oil spot and futures markets

Author

Listed:
  • Ashima Goyal

    (Indira Gandhi Institute of Development Research)

  • Shruti Tripathi

    (Indira Gandhi Institute of Development Research)

Abstract

In a period of great oil price volatility, the paper assesses the role of expected net demand compared to liquidity and leverage driven expansion in net long positions. We apply time series tests for mutual and across exchange causality, and lead-lag relationships, between crude oil spot and futures prices on two international and one Indian commodity exchange. We also search for short duration bubbles, and how they differ across exchanges. The results show expectations mediated through financial markets did not lead to persistent deviations from fundamentals. There is mutual Granger causality between spot and futures, and in the error correction model for mature exchanges, spot leads futures. Mature market exchanges lead in price discovery. Futures in these markets lead Indian (daily) futures-markets are integrated. But there is stronger evidence of short-term or collapsing bubbles in mature market futures compared to Indian, although mature markets have a higher share of hedging. Indian regulations such as position limits may have mitigated short duration bubbles. It follows leverage due to lax regulation may be responsible for excess volatility. Well-designed regulations can improve market functioning.

Suggested Citation

  • Ashima Goyal & Shruti Tripathi, 2012. "Regulations and price discovery: oil spot and futures markets," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-016, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Handle: RePEc:ind:igiwpp:2012-016
    as

    Download full text from publisher

    File URL: http://www.igidr.ac.in/pdf/publication/WP-2012-016.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    2. Dufour, Alfonso & Engle, Robert F, 1999. "Time and the Price Impact of a Trade," University of California at San Diego, Economics Working Paper Series qt62c0h04j, Department of Economics, UC San Diego.
    3. Williams,Jeffrey C. & Wright,Brian D., 2005. "Storage and Commodity Markets," Cambridge Books, Cambridge University Press, number 9780521023399, September.
    4. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    5. Elif Arbatli, 2008. "Futures Markets, Oil Prices and the Intertemporal Approach to the Current Account," Staff Working Papers 08-48, Bank of Canada.
    6. Bessembinder, Hendrik & Seguin, Paul J., 1993. "Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 21-39, March.
    7. Serena Ng & Francisco J. Ruge-Murcia, 2000. "Explaining the Persistence of Commodity Prices," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 149-171, October.
    8. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    9. Fleming, Jeff & Ostdiek, Barbara, 1999. "The impact of energy derivatives on the crude oil market," Energy Economics, Elsevier, vol. 21(2), pages 135-167, April.
    10. Menzie D. Chinn & Michael LeBlanc & Olivier Coibion, 2005. "The Predictive Content of Energy Futures: An Update on Petroleum, Natural Gas, Heating Oil and Gasoline," NBER Working Papers 11033, National Bureau of Economic Research, Inc.
    11. Scott H. Irwin & Dwight R. Sanders, 2010. "The Impact of Index and Swap Funds on Commodity Futures Markets: Preliminary Results," OECD Food, Agriculture and Fisheries Papers 27, OECD Publishing.
    12. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    13. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
    14. José A. Scheinkman & Jack Schechtman, 1983. "A Simple Competitive Model with Production and Storage," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(3), pages 427-441.
    15. Pagan, Adrian R. & Schwert, G. William, 1990. "Testing for covariance stationarity in stock market data," Economics Letters, Elsevier, vol. 33(2), pages 165-170, June.
    16. Menzie D. Chinn & Olivier Coibion, 2014. "The Predictive Content of Commodity Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 607-636, July.
    17. Plourde, André & Watkins, G. C., 1998. "Crude oil prices between 1985 and 1994: how volatile in relation to other commodities?," Resource and Energy Economics, Elsevier, vol. 20(3), pages 245-262, September.
    18. Manmohan S. Kumar, 1992. "The Forecasting Accuracy of Crude Oil Futures Prices," IMF Staff Papers, Palgrave Macmillan, vol. 39(2), pages 432-461, June.
    19. Nicholas Kaldor, 1939. "Speculation and Economic Stability," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 7(1), pages 1-27.
    20. Spargoli, Fabrizio & Zagaglia, Paolo, 2007. "The Comovements between Futures Markets for Crude Oil: Evidence from a Structural GARCH Model," Research Papers in Economics 2007:15, Stockholm University, Department of Economics.
    21. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, September.
    22. Andrew H. McCallum & Tao Wu, 2005. "Do oil futures prices help predict future oil prices?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue dec30.
    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. Ashima Goyal & Rupayan Pal, 2022. "Global shocks and international policy coordination," Global Policy, London School of Economics and Political Science, vol. 13(4), pages 458-468, September.
    2. Ashima Goyal, 2015. "Understanding High Inflation Trend in India," South Asian Journal of Macroeconomics and Public Finance, , vol. 4(1), pages 1-42, June.
    3. Ashima Goyal, 2013. "Assessing Changes in the Global Financial Architecture from an Emerging Market Perspective," Foreign Trade Review, , vol. 48(4), pages 461-480, November.
    4. Ashima Goyal, 2015. "Financial stability: Underlining context," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-014, Indira Gandhi Institute of Development Research, Mumbai, India.
    5. Muneesh Kumar & Tarunika Jain Agrawal & Srishti Sehgal, 2017. "Domestic and International Information Linkages for Indian Commodities Market in the Pre- and Post-CTT Periods," Metamorphosis: A Journal of Management Research, , vol. 16(2), pages 75-91, December.

    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. Markos Farag, Stephen Snudden, Greg Upton, 2024. "Can Futures Prices Predict the Real Price of Primary Commodities?," LCERPA Working Papers jc0145, Laurier Centre for Economic Research and Policy Analysis, revised 2024.
    2. Martin T. Bohl & Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2018. "Information Transmission under Increasing Political Tension – Evidence for the Berlin Produce Exchange 1887-1896," CQE Working Papers 7618, Center for Quantitative Economics (CQE), University of Muenster.
    3. Pieroni, Luca & Ricciarelli, Matteo, 2008. "Modelling dynamic storage function in commodity markets: Theory and evidence," Economic Modelling, Elsevier, vol. 25(5), pages 1080-1092, September.
    4. Eyal Dvir & Ken Rogoff, 2009. "The Three Epochs of Oil," Boston College Working Papers in Economics 706, Boston College Department of Economics.
    5. Martin T. Bohl & Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2021. "Information transmission under increasing political tensions—Evidence from the Berlin Produce Exchange 1887–1896," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 226-244, February.
    6. Tore S. Kleppe & Atle Oglend, 2019. "Can limits‐to‐arbitrage from bounded storage improve commodity term‐structure modeling?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 865-889, July.
    7. Robert Socha & Piotr Wdowiński, 2018. "Crude oil price and speculative activity: a cointegration analysis," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 263-304, September.
    8. Menzie D. Chinn & Olivier Coibion, 2014. "The Predictive Content of Commodity Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 607-636, July.
    9. Christophe Gouel, 2012. "Agricultural Price Instability: A Survey Of Competing Explanations And Remedies," Journal of Economic Surveys, Wiley Blackwell, vol. 26(1), pages 129-156, February.
    10. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    11. Algieri, Bernardina, 2013. "A Roller Coaster Ride: an empirical investigation of the main drivers of wheat price," Discussion Papers 145556, University of Bonn, Center for Development Research (ZEF).
    12. Mr. Tao Wu & Mr. Michele Cavallo, 2012. "Measuring Oil-Price Shocks Using Market-Based Information," IMF Working Papers 2012/019, International Monetary Fund.
    13. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    14. Jeffrey R. Black & Pankaj K. Jain & Wei Sun, 2023. "Trade-time clustering," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1209-1242, April.
    15. Kyritsis, Evangelos & Serletis, Apostolos, 2018. "The zero lower bound and market spillovers: Evidence from the G7 and Norway," Research in International Business and Finance, Elsevier, vol. 44(C), pages 100-123.
    16. Ping-Hung Chou & Pei-Shan Wu & Teng-Tsai Tu, 2014. "The Impact of Trader Behavior on Options Price Volatility," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(4), pages 503-516, April.
    17. Cerqueira, Vinícius Dos Santos & Ribeiro, Márcio Bruno & Martinez, Thiago Sevilhano, 2014. "Propagação Assimétrica de Choques Monetários na Economia Brasileira: Evidências com base em um modelo vetorial não-linear de transição suave," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(1), April.
    18. Deren Unalmis & Ibrahim Unalmis & Ms. Filiz D Unsal, 2012. "On the Sources and Consequences of Oil Price Shocks: The Role of Storage," IMF Working Papers 2012/270, International Monetary Fund.
    19. Nicolas Legrand, 2019. "The Empirical Merit Of Structural Explanations Of Commodity Price Volatility: Review And Perspectives," Journal of Economic Surveys, Wiley Blackwell, vol. 33(2), pages 639-664, April.
    20. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.

    More about this item

    Keywords

    crude oil spot; futures; commodity exchanges; short duration bubbles; position limits;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ind:igiwpp:2012-016. 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: Shamprasad M. Pujar (email available below). General contact details of provider: https://edirc.repec.org/data/igidrin.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.