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Price dynamics and financialization effects in corn futures markets with heterogeneous traders

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  • Grosche, Stephanie
  • Heckelei, Thomas

Abstract

Presumed portfolio benefits of commodities and the availability of index fund-type investment products increase attractiveness of commodity markets for financial traders. But resulting “index trading” strategies are suspected to inflate commodity prices above their fundamental value. We use a Heterogeneous Agent Model for the corn futures market, which can depict price dynamics from the interaction of fundamentalist commercial traders and chartist speculators, and estimate its parameters with the Method of Simulated Moments. In a scenario-based approach, we introduce index funds and simulate price effects from their inclusion in financial portfolio strategies. Results show that the additional long-only trading volume on the market does not inflate price levels but increases return volatility.

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Bibliographic Info

Paper provided by University of Bonn, Institute for Food and Resource Economics in its series Discussion Papers with number 172077.

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Date of creation: 07 Jun 2014
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Handle: RePEc:ags:ubfred:172077

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Web page: http://www.ilr1.uni-bonn.de/
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Related research

Keywords: Heterogeneous agents; Agent-based modeling; Commodity index treading; Financialization of commodity markets; Agricultural and Food Policy; Agricultural Finance; Financial Economics; Research Methods/ Statistical Methods; D84; G15; G17; Q02;

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  1. Manzan, S. & Westerhoff, F., 2002. "Representativeness of News and Exchange Rate Dynamics," CeNDEF Working Papers 02-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  2. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
  3. Anufriev, M. & Tuinstra, J., 2013. "The impact of short-selling constraints on financial market stability in a heterogeneous agents model," CeNDEF Working Papers 13-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  4. Zeeman, E. C., 1974. "On the unstable behaviour of stock exchanges," Journal of Mathematical Economics, Elsevier, vol. 1(1), pages 39-49, March.
  5. He, Xue-Zhong & Westerhoff, Frank H., 2005. "Commodity markets, price limiters and speculative price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 29(9), pages 1577-1596, September.
  6. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2014. "Bubbles in food commodity markets: Four decades of evidence," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 129-155.
  7. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
  8. Frankel, Jeffrey A & Froot, Kenneth A, 1990. "Chartists, Fundamentalists, and Trading in the Foreign Exchange Market," American Economic Review, American Economic Association, vol. 80(2), pages 181-85, May.
  9. 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.
  10. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
  11. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425.
  12. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Society for Computational Economics, vol. 26(1), pages 19-49, August.
  13. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2005. "Heterogeneous Expectations and Speculative Behaviour in a Dynamic Multi-Asset Framework," Research Paper Series 166, Quantitative Finance Research Centre, University of Technology, Sydney.
  14. Franke, Reiner, 2009. "Applying the method of simulated moments to estimate a small agent-based asset pricing model," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 804-815, December.
  15. Christian Bauer & Paul De Grauwe & Stefan Reitz, 2007. "Exchange Rates Dynamics in a Target Zone – A Heterogeneous Expectations Approach," CESifo Working Paper Series 2080, CESifo Group Munich.
  16. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
  17. Franke, Reiner & Westerhoff, Frank, 2011. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," BERG Working Paper Series 78, Bamberg University, Bamberg Economic Research Group.
  18. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
  19. Westerhoff, Frank & Reitz, Stefan, 2005. "Commodity price dynamics and the nonlinear market impact of technical traders: empirical evidence for the US corn market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 641-648.
  20. Grosche, Stephanie & Heckelei, Thomas, 2014. "Directional Volatility Spillovers between Agricultural, Crude Oil, Real Estate and other Financial Markets," Discussion Papers 166079, University of Bonn, Institute for Food and Resource Economics.
  21. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
  22. Lin Gao & Lu Liu, 2014. "The Volatility Behavior and Dependence Structure of Commodity Futures and Stocks," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(1), pages 93-101, 01.
  23. Chiarella, Carl & Dieci, Roberto & Gardini, Laura, 2002. "Speculative behaviour and complex asset price dynamics: a global analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 173-197, October.
  24. Irwin, Scott H. & Sanders, Dwight R. & Merrin, Robert P., 2009. "Devil or Angel? The Role of Speculation in the Recent Commodity Price Boom (and Bust)," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(02), August.
  25. Lee, Bong-Soo & Ingram, Beth Fisher, 1991. "Simulation estimation of time-series models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 197-205, February.
  26. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  27. Robles, Miguel & Torero, Maximo & von Braun, Joachim, 2009. "When speculation matters:," Issue briefs 57, International Food Policy Research Institute (IFPRI).
  28. Ellen, Saskia ter & Zwinkels, Remco C.J., 2010. "Oil price dynamics: A behavioral finance approach with heterogeneous agents," Energy Economics, Elsevier, vol. 32(6), pages 1427-1434, November.
  29. Carl Chiarella & Roberto Dieci & Laura Gardini, 2005. "The Dynamic Interaction of Speculation and Diversification," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 17-52.
  30. Lux, Thomas, 1997. "Time variation of second moments from a noise trader/infection model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 1-38, November.
  31. Beja, Avraham & Goldman, M Barry, 1980. " On the Dynamic Behavior of Prices in Disequilibrium," Journal of Finance, American Finance Association, vol. 35(2), pages 235-48, May.
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