IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v10y2018icp29-46.html
   My bibliography  Save this article

Guilty speculators? Range-based conditional volatility in a cross-section of wheat futures

Author

Listed:
  • Haase, Marco
  • Huss, Matthias

Abstract

In response to the unusually high levels of price volatility during the world food price crisis of 2007/2008, US and EU regulators have introduced position limits that aim to protect commodity markets from exposure to excess speculation. Such regulatory initiatives presuppose that excess speculation is indeed responsible for excess volatility. Our results debunk this presupposition and show the opposite effect: speculative activity reduces price volatility, particularly during times of distress. Our findings are based on a cross-section of wheat futures contracts, traded at five different commodity exchanges with various degrees of speculative activity. Volatility is estimated based on a Conditional Autoregressive Range Model (CARR), which is further augmented with exogenous excess-speculation shocks (CARRX). These models capture herding, feedback and noise trading, and a threshold version (TCARRX) identifies regimes in which the anatomy of the volatility process changes according to the level of excess speculation. Our findings support Working’s hypothesis that a certain level of excess speculation is essential for a well-functioning market.

Suggested Citation

  • Haase, Marco & Huss, Matthias, 2018. "Guilty speculators? Range-based conditional volatility in a cross-section of wheat futures," Journal of Commodity Markets, Elsevier, vol. 10(C), pages 29-46.
  • Handle: RePEc:eee:jocoma:v:10:y:2018:i:c:p:29-46
    DOI: 10.1016/j.jcomm.2017.10.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851316301532
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcomm.2017.10.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    2. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    3. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    4. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    5. repec:dau:papers:123456789/14980 is not listed on IDEAS
    6. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    7. Easterbrook, Frank H, 1986. "Monopoly, Manipulation, and the Regulation of Futures Markets," The Journal of Business, University of Chicago Press, vol. 59(2), pages 103-127, April.
    8. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    9. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    10. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
    11. Louis Ederington & Jae Ha Lee, 2002. "Who Trades Futures and How: Evidence from the Heating Oil Futures Market," The Journal of Business, University of Chicago Press, vol. 75(2), pages 353-374, April.
    12. Jennifer Clapp, 2009. "Food Price Volatility and Vulnerability in the Global South: considering the global economic context," Third World Quarterly, Taylor & Francis Journals, vol. 30(6), pages 1183-1196.
    13. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2012. "Commodity Liquidity Measurement and Transaction Costs," Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 599-638.
    14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    15. Marc F. Bellemare & Christopher B. Barrett & David R. Just, 2013. "The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(4), pages 877-899.
    16. Dwight R. Sanders & Scott H. Irwin & Robert P. Merrin, 2010. "The Adequacy of Speculation in Agricultural Futures Markets: Too Much of a Good Thing?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 32(1), pages 77-94.
    17. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    18. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    19. Luo, Guo Ying, 1998. "Market Efficiency and Natural Selection in a Commodity Futures Market," Review of Financial Studies, Society for Financial Studies, vol. 11(3), pages 647-674.
    20. Hernandez, Manuel & Torero, Maximo, 2010. "Examining the dynamic relationship between spot and future prices of agricultural commodities," IFPRI discussion papers 988, International Food Policy Research Institute (IFPRI).
    21. Haase, Marco & Seiler Zimmermann, Yvonne & Zimmermann, Heinz, 2016. "The impact of speculation on commodity futures markets – A review of the findings of 100 empirical studies," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 1-15.
    22. Nicole M. Aulerich & Scott H. Irwin & Philip Garcia, 2014. "Bubbles, Food Prices, and Speculation: Evidence from the CFTC's Daily Large Trader Data Files," NBER Chapters, in: The Economics of Food Price Volatility, pages 211-253, National Bureau of Economic Research, Inc.
    23. Stephanie-Carolin Grosche, 2014. "What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 279-302, June.
    24. Bohl, Martin T. & Stephan, Patrick M., 2013. "Does Futures Speculation Destabilize Spot Prices? New Evidence for Commodity Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 45(4), pages 595-616, November.
    25. Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-582, June.
    26. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    27. ap Gwilym, Rhys & Ebrahim, M. Shahid, 2013. "Can position limits restrain ‘rogue’ trading?," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 824-836.
    28. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    29. Christopher Gilbert & Wyn Morgan, 2010. "Has food price volatility risen?," Department of Economics Working Papers 1002, Department of Economics, University of Trento, Italia.
    30. Zeileis, Achim & Kleiber, Christian & Kramer, Walter & Hornik, Kurt, 2003. "Testing and dating of structural changes in practice," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 109-123, October.
    31. Dwight R. Sanders & Scott H. Irwin, 2010. "A speculative bubble in commodity futures prices? Cross‐sectional evidence," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 25-32, January.
    32. Brian J. Henderson & Neil D. Pearson & Li Wang, 2015. "Editor's Choice New Evidence on the Financialization of Commodity Markets," Review of Financial Studies, Society for Financial Studies, vol. 28(5), pages 1285-1311.
    33. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    34. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
    35. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    36. Eugenio Bobenrieth & Brian Wright & Di Zeng, 2013. "Stocks-to-use ratios and prices as indicators of vulnerability to spikes in global cereal markets," Agricultural Economics, International Association of Agricultural Economists, vol. 44(s1), pages 43-52, November.
    37. Mr. Shaun K. Roache, 2010. "What Explains the Rise in Food Price Volatility?," IMF Working Papers 2010/129, International Monetary Fund.
    38. Brandt, Michael W. & Jones, Christopher S., 2006. "Volatility Forecasting With Range-Based EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 470-486, October.
    39. Working, Holbrook, 1960. "Speculation on Hedging Markets," Food Research Institute Studies, Stanford University, Food Research Institute, vol. 1(2), pages 1-36.
    40. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    41. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    42. Bohl, Martin T. & Stephan, Patrick M., 2013. "Does Futures Speculation Destabilize Spot Prices? New Evidence for Commodity Markets," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(4), pages 1-21, November.
    43. Abby Kim, 2015. "Does Futures Speculation Destabilize Commodity Markets?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(8), pages 696-714, August.
    44. Christopher L. Gilbert & Simone Pfuderer, 2014. "The Role of Index Trading in Price Formation in the Grains and Oilseeds Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 303-322, June.
    45. Gilbert, Christopher L., 2012. "Speculative impacts on grains price volatility," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122540, European Association of Agricultural Economists.
    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. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security," Agriculture, MDPI, vol. 12(11), pages 1-27, November.
    2. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic," Agriculture, MDPI, vol. 12(5), pages 1-26, April.

    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. Haase, Marco & Seiler Zimmermann, Yvonne & Zimmermann, Heinz, 2016. "The impact of speculation on commodity futures markets – A review of the findings of 100 empirical studies," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 1-15.
    2. Bohl, Martin T. & Sulewski, Christoph, 2019. "The impact of long-short speculators on the volatility of agricultural commodity futures prices," Journal of Commodity Markets, Elsevier, vol. 16(C).
    3. Ana I. Sanjuán-López & Philip J. Dawson, 2017. "Volatility Effects of Index Trading and Spillovers on US Agricultural Futures Markets: A Multivariate GARCH Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 822-838, September.
    4. Martin T. Bohl & Pierre L. Siklos & Claudia Wellenreuther, 2018. "Speculative activity and returns volatility of Chinese major agricultural commodity futures," CAMA Working Papers 2018-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Bohl, Martin T. & Siklos, Pierre L. & Wellenreuther, Claudia, 2018. "Speculative activity and returns volatility of Chinese agricultural commodity futures," Journal of Asian Economics, Elsevier, vol. 54(C), pages 69-91.
    6. Boyd, Naomi E. & Harris, Jeffrey H. & Li, Bingxin, 2018. "An update on speculation and financialization in commodity markets," Journal of Commodity Markets, Elsevier, vol. 10(C), pages 91-104.
    7. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    8. Dwight R. Sanders & Scott H. Irwin, 2017. "Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 345-365, June.
    9. Algieri, Bernardina & Kalkuhl, Matthias & Koch, Nicolas, 2017. "A tale of two tails: Explaining extreme events in financialized agricultural markets," Food Policy, Elsevier, vol. 69(C), pages 256-269.
    10. Martin T. Bohl & Christoph Sulewski, 2018. "The Impact of Long-Short Speculators on the Volatility of Agricultural Commodity Futures Prices," CQE Working Papers 7718, Center for Quantitative Economics (CQE), University of Muenster.
    11. Bernhard Brümmer & Olaf Korn & Kristina Schlüßler & Tinoush Jamali Jaghdani, 2016. "Volatility in Oilseeds and Vegetable Oils Markets: Drivers and Spillovers," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 685-705, September.
    12. Mayer, Herbert & Rathgeber, Andreas & Wanner, Markus, 2017. "Financialization of metal markets: Does futures trading influence spot prices and volatility?," Resources Policy, Elsevier, vol. 53(C), pages 300-316.
    13. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    14. Emiliano Magrini & Ayca Donmez, 2013. "Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach," JRC Research Reports JRC84138, Joint Research Centre.
    15. Tröster, Bernhard & Gunter, Ulrich, 2022. "Trading for speculators: The role of physical actors in the financialization of coffee, cocoa and cotton value chains," Working Papers 68, Austrian Foundation for Development Research (ÖFSE).
    16. Yan, Lei & Irwin, Scott H. & Sanders, Dwight R., 2018. "Mapping algorithms, agricultural futures, and the relationship between commodity investment flows and crude oil futures prices," Energy Economics, Elsevier, vol. 72(C), pages 486-504.
    17. Yan, Lei & Irwin, Scott H. & Sanders, Dwight R., 2017. "Identifying the Impact of Financialization in Commodity Futures Prices from Index Rebalancing," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258504, Agricultural and Applied Economics Association.
    18. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    19. Huchet, Nicolas & Fam, Papa Gueye, 2016. "The role of speculation in international futures markets on commodity prices," Research in International Business and Finance, Elsevier, vol. 37(C), pages 49-65.
    20. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.

    More about this item

    Keywords

    Range based volatility; Wheat futures; Speculation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

    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:eee:jocoma:v:10:y:2018:i:c:p:29-46. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcomm .

    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.