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Nonlinear expectations in speculative markets - Evidence from the ECB survey of professional forecasters

Author

Listed:
  • Reitz, Stefan

    (Institute for Quantitative Business and Economics Research)

  • Rülke, Jan-Christoph

    (Department of Economics)

  • Stadtmann, Georg

    (Department of Business and Economics)

Abstract

Chartist and fundamentalist models have proven to be capable of replicating stylized facts on speculative markets. In general, this is achieved by specifying nonlinear interactions of otherwise linear asset price expectations of the respective trader groups. This paper investigates whether or not regressive and extrapolative expectations themselves exhibit significant nonlinear dynamics. The empirical results are based on a new data set from the European Central Bank Survey of Professional Forecasters on oil price expectations. In particular, we find that forecasters form destabilizing expectations in the neighborhood of the fundamental value, whereas expectations tend to be stabilizing in the presence of substantial oil price misalignment.

Suggested Citation

  • Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets - Evidence from the ECB survey of professional forecasters," Discussion Papers on Economics 1/2012, University of Southern Denmark, Department of Economics.
  • Handle: RePEc:hhs:sdueko:2012_001
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    1. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    2. Stefan Reitz & Ulf Slopek, 2009. "Non‐Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?," German Economic Review, Verein für Socialpolitik, vol. 10(3), pages 270-283, August.
    3. Manzanares, Andrés & Garcí­a, Juan Angel, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 836, European Central Bank.
    4. Cars H. Hommes, 2009. "Bounded Rationality and Learning in Complex Markets," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 5, Edward Elgar Publishing.
    5. Christopher F Baum, 2006. "An Introduction to Modern Econometrics using Stata," Stata Press books, StataCorp LP, number imeus, March.
    6. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2007. "The ECB survey of professional forecasters (SPF) – A review after eight years’ experience," Occasional Paper Series 59, European Central Bank.
    7. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    8. González, Andrés & Teräsvirta, Timo & van Dijk, Dick & Yang, Yukai, 2005. "Panel Smooth Transition Regression Models," SSE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics, revised 11 Oct 2017.
    9. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    10. Thomas Lux, 2009. "Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey," Post-Print hal-00720175, HAL.
    11. Abosedra, Salah & Baghestani, Hamid, 2004. "On the predictive accuracy of crude oil futures prices," Energy Policy, Elsevier, vol. 32(12), pages 1389-1393, August.
    12. Elliott, Graham & Ito, Takatoshi, 1999. "Heterogeneous expectations and tests of efficiency in the yen/dollar forward exchange rate market," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 435-456, April.
    13. J. Barkley Rosser Jr. (ed.), 2009. "Handbook of Research on Complexity," Books, Edward Elgar Publishing, number 3625.
    14. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
    15. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    16. Paul De Grauwe & Marianna Grimaldi, 2014. "Exchange Rate Puzzles: A Tale of Switching Attractors," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 3, pages 71-117, World Scientific Publishing Co. Pte. Ltd..
    17. Frank H. Westerhoff, 2009. "Exchange Rate Dynamics: A Nonlinear Survey," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 11, Edward Elgar Publishing.
    18. Juan Angel Garcia, 2003. "An introduction to the ECB’s survey of professional forecasters," Occasional Paper Series 08, European Central Bank.
    19. Westerhoff, Frank H., 2003. "Expectations driven distortions in the foreign exchange market," Journal of Economic Behavior & Organization, Elsevier, vol. 51(3), pages 389-412, July.
    20. Robert B. Barsky & Lutz Kilian, 2004. "Oil and the Macroeconomy Since the 1970s," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 115-134, Fall.
    21. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    22. Bauer, Christian & De Grauwe, Paul & Reitz, Stefan, 2009. "Exchange rate dynamics in a target zone--A heterogeneous expectations approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 329-344, February.
    23. Richard Alm & Stephen P. A. Brown & Raghav Virmani, 2008. "Crude awakening: behind the surge in oil prices," Economic Letter, Federal Reserve Bank of Dallas, vol. 3(may).
    24. Hommes, C.H. & Wagener, F.O.O., 2008. "Complex evolutionary systems in behavioral finance," CeNDEF Working Papers 08-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    25. 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.
    26. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    27. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    28. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    29. James D. Hamilton, 2009. "Understanding Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 179-206.
    30. Thomas A. Knetsch, 2007. "Forecasting the price of crude oil via convenience yield predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 527-549.
    31. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    32. Ito, Takatoshi, 1990. "Foreign Exchange Rate Expectations: Micro Survey Data," American Economic Review, American Economic Association, vol. 80(3), pages 434-449, June.
    33. Menkhoff, Lukas & Rebitzky, Rafael R. & Schröder, Michael, 2009. "Heterogeneity in exchange rate expectations: Evidence on the chartist-fundamentalist approach," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 241-252, May.
    34. Menkhoff, Lukas, 1997. "Examining the Use of Technical Currency Analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(4), pages 307-318, October.
    35. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    36. Béreau, Sophie & Villavicencio, Antonia López & Mignon, Valérie, 2010. "Nonlinear adjustment of the real exchange rate towards its equilibrium value: A panel smooth transition error correction modelling," Economic Modelling, Elsevier, vol. 27(1), pages 404-416, January.
    37. Prat, Georges & Uctum, Remzi, 2011. "Modelling oil price expectations: Evidence from survey data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
    38. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    39. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    40. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    41. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    42. Johansen, Soren & Juselius, Katarina, 1994. "Identification of the long-run and the short-run structure an application to the ISLM model," Journal of Econometrics, Elsevier, vol. 63(1), pages 7-36, July.
    43. Stefan Reitz & Ulf Slopek, 2009. "Non‐Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?," German Economic Review, Verein für Socialpolitik, vol. 10(3), pages 270-283, August.
    44. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.
    45. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    46. Macdonald, Ronald & Marsh, Ian W., 1996. "Currency forecasters are heterogeneous: confirmation and consequences," Journal of International Money and Finance, Elsevier, vol. 15(5), pages 665-685, October.
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    Cited by:

    1. Atalla, Tarek & Joutz, Fred & Pierru, Axel, 2016. "Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1178-1192.
    2. Leppin, Julian Sebastian, 2014. "The relation between overreaction in forecasts and uncertainty: A nonlinear approachvon," HWWI Research Papers 158, Hamburg Institute of International Economics (HWWI).
    3. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
    4. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
    5. Zhenxi Chen & Stefan Reitz, 2020. "Dynamics of the European sovereign bonds and the identification of crisis periods," Empirical Economics, Springer, vol. 58(6), pages 2761-2781, June.
    6. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    7. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2014. "Heterogeneous forecasters and nonlinear expectation formation in the US stock market," Kiel Working Papers 1947, Kiel Institute for the World Economy (IfW Kiel).
    8. Goldbaum, David & Zwinkels, Remco C.J., 2014. "An empirical examination of heterogeneity and switching in foreign exchange markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 667-684.
    9. Dick, Christian D. & Menkhoff, Lukas, 2013. "Exchange rate expectations of chartists and fundamentalists," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1362-1383.
    10. Leppin, Julian Sebstian, 2014. "The Relation Between Overreaction in Forecasts and Uncertainty: A Nonlinear Approach," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100284, Verein für Socialpolitik / German Economic Association.
    11. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," EconomiX Working Papers 2015-17, University of Paris Nanterre, EconomiX.
    12. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," Working Papers hal-04141409, HAL.

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    More about this item

    Keywords

    Agent based models; nonlinear expectations; survey data;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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