IDEAS home Printed from https://ideas.repec.org/p/cqe/wpaper/8019.html
   My bibliography  Save this paper

Measurement Errors in Index Trader Positions Data: Is the Price Pressure Hypothesis Still Invalid?

Author

Listed:
  • Martin T. Bohl
  • Nicole Branger
  • Mark Trede

Abstract

In this paper, we examine whether the repeated rejection of Masters' price pressure hypothesis is robust with respect to measurement errors in index trader position data. We allow for autocorrelated errors and a potential impact of index trader positions on the level and volatility of commodity returns. The resulting state-space model is estimated via particle MCMC. The empirical investigation relies on weekly data for eleven commodities contained in the SCoT reports. Our empirical findings show that the rejection of the price pressure hypothesis is robust concerning the inclusion of measurement errors in index trader positions data.

Suggested Citation

  • Martin T. Bohl & Nicole Branger & Mark Trede, 2019. "Measurement Errors in Index Trader Positions Data: Is the Price Pressure Hypothesis Still Invalid?," CQE Working Papers 8019, Center for Quantitative Economics (CQE), University of Muenster.
  • Handle: RePEc:cqe:wpaper:8019
    as

    Download full text from publisher

    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/cqe_wp_80_2019.pdf
    File Function: Version of March 2019
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christopher L. Gilbert, 2010. "Speculative Influences On Commodity Futures Prices 2006-2008," UNCTAD Discussion Papers 197, United Nations Conference on Trade and Development.
    2. 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.
    3. 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.
    4. Flury, Thomas & Shephard, Neil, 2011. "Bayesian Inference Based Only On Simulated Likelihood: Particle Filter Analysis Of Dynamic Economic Models," Econometric Theory, Cambridge University Press, vol. 27(5), pages 933-956, October.
    5. Sanders, Dwight R. & Boris, Keith & Manfredo, Mark, 2004. "Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports," Energy Economics, Elsevier, vol. 26(3), pages 425-445, May.
    6. Susanne M. Schennach, 2016. "Recent Advances in the Measurement Error Literature," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 341-377, October.
    7. Dwight R. Sanders & Scott H. Irwin, 2011. "New Evidence on the Impact of Index Funds in U.S. Grain Futures Markets," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 59(4), pages 519-532, December.
    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. Sania Wadud & Robert D. Durand & Marc Gronwald, 2021. "Connectedness between the Crude Oil Futures and Equity Markets during the Pre- and Post-Financialisation Eras," CESifo Working Paper Series 9202, CESifo.

    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. Martin T. Bohl & Nicole Branger & Mark Trede, 2022. "Measurement errors in index trader positions data: Is the price pressure hypothesis still invalid?," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(3), pages 1534-1553, September.
    2. Dwight R. Sanders and Scott H. Irwin, 2013. "Measuring Index Investment in Commodity Futures Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    3. Awan, Obaid A., 2019. "Price discovery or noise: The role of arbitrage and speculation in explaining crude oil price behaviour," Journal of Commodity Markets, Elsevier, vol. 16(C).
    4. Georg Lehecka, 2015. "Do hedging and speculative pressures drive commodity prices, or the other way round?," Empirical Economics, Springer, vol. 49(2), pages 575-603, September.
    5. 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.
    6. Shanker, Latha, 2017. "New indices of adequate and excess speculation and their relationship with volatility in the crude oil futures market," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 18-35.
    7. 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).
    8. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
    9. 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.
    10. Miffre, Joëlle & Brooks, Chris, 2013. "Do long-short speculators destabilize commodity futures markets?," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 230-240.
    11. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 371-396, August.
    12. Manera, Matteo & Nicolini, Marcella & Vignati, Ilaria, 2016. "Modelling futures price volatility in energy markets: Is there a role for financial speculation?," Energy Economics, Elsevier, vol. 53(C), pages 220-229.
    13. Matteo Manera & Marcella Nicolini & Ilaria Vignati, 2013. "Futures price volatility in commodities markets: The role of short term vs long term speculation," DEM Working Papers Series 042, University of Pavia, Department of Economics and Management.
    14. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    15. Nicole M. Moran & Scott H. Irwin & Philip Garcia, 2020. "Who Wins and Who Loses? Trader Returns and Risk Premiums in Agricultural Futures Markets," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(4), pages 611-652, December.
    16. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joelle, 2021. "The risk premia of energy futures," Energy Economics, Elsevier, vol. 102(C).
    17. Algieri, Bernardina, 2012. "Price Volatility, Speculation and Excessive Speculation in Commodity Markets: sheep or shepherd behaviour?," Discussion Papers 124390, University of Bonn, Center for Development Research (ZEF).
    18. Zhang, Yue-Jun, 2013. "Speculative trading and WTI crude oil futures price movement: An empirical analysis," Applied Energy, Elsevier, vol. 107(C), pages 394-402.
    19. Will, Matthias Georg & Prehn, Sören & Pies, Ingo & Glauben, Thomas, 2012. "Schadet oder nützt die Finanzspekulation mit Agrarrohstoffen? Ein Literaturüberblick zum aktuellen Stand der empirischen Forschung," Discussion Papers 2012-26, Martin Luther University of Halle-Wittenberg, Chair of Economic Ethics.
    20. Bosch, David & Smimou, K., 2022. "Traders’ motivation and hedging pressure in commodity futures markets," Research in International Business and Finance, Elsevier, vol. 59(C).

    More about this item

    Keywords

    Masters' Price Pressure Hypothesis; Measurement Errors; Commodity Futures Markets; Index Traders; CFTC Data;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

    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:cqe:wpaper:8019. 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: Susanne Deckwitz (email available below). General contact details of provider: https://edirc.repec.org/data/cqmuede.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.