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Regulations and price discovery: oil spot and futures markets

Author

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  • 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
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    File URL: http://www.igidr.ac.in/pdf/publication/WP-2012-016.pdf
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    References listed on IDEAS

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    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. 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.
    3. Williams,Jeffrey C. & Wright,Brian D., 2005. "Storage and Commodity Markets," Cambridge Books, Cambridge University Press, number 9780521023399, May.
    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. 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(01), pages 21-39, March.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. José A. Scheinkman & Jack Schechtman, 1983. "A Simple Competitive Model with Production and Storage," Review of Economic Studies, Oxford University Press, vol. 50(3), pages 427-441.
    11. 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.
    12. 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.
    13. 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.
    14. Manmohan S. Kumar, 1992. "The Forecasting Accuracy of Crude Oil Futures Prices," IMF Staff Papers, Palgrave Macmillan, vol. 39(2), pages 432-461, June.
    15. 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.
    16. Tao Wu & Andrew H. McCallum, 2005. "Do oil futures prices help predict future oil prices?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue dec30.
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    Cited by:

    1. 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.

    More about this item

    Keywords

    crude oil spot; futures; commodity exchanges; short duration bubbles; position limits;

    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

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