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A Dynamical Analysis of Moving Average Rules

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Author Info
Cars Hommes
Carl Chiarella
Xue-Zhong He

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Abstract

The methods of various moving average rules remain popular with financial market practitioners. These rules have recently become the focus of empirical studies. However there seem to have been very few studies on the analysis of the type of financial market dynamics resulting from the fact that some agents engage in such strategies. In this paper we seek to fill this gap in the literature by proposing a market of financial market dynamics in which demand for traded assets has both a fundamentalist and a chartist component. The chartist demand is governed by the difference between a long run and a short run moving average. Both types of traders are bounded rational in the sense that, based on a certain fitness measure, traders switch from strategy with low fitness to the one with high fitness. We characterise first the stability and bifurcation properties of the underlying deterministic model via the reaction coefficient of the fundamentalists, the extrapolation rate of the chartists and the lengths used for the moving averages. By increasing the switching intensity, we then examine various rational routes to randomness for different, but fixed, long run moving average. The price dynamics of moving average is also examined and it is found that an increase of the window length of the long moving average can destabilize an otherwise stable system, leading to more complicated, even chaotic behaviour

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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 238.

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Date of creation: 11 Aug 2004
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Handle: RePEc:sce:scecf4:238

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Related research
Keywords: Moving average; fundamentalists; trend followers; bifurcation;

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Find related papers by JEL classification:
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August. [Downloadable!] (restricted)
  2. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  3. Boswijk, H.P., Griffioen, G.A.W., Hommes, C.H., 2001. "Succes and Failure of Technical Trading Strategies in the Cocoa Futures Market," Computing in Economics and Finance 2001 120, Society for Computational Economics.
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  4. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December. [Downloadable!] (restricted)
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  5. M. Hashem Pesaran & Allan Timmermann, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," University of California at San Diego, Economics Working Paper Series 95-19, Department of Economics, UC San Diego.
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  6. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer, vol. 19(1), pages 95-132, February. [Downloadable!]
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  7. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, School of Finance and Economics, University of Technology, Sydney. [Downloadable!]
  8. Chiarella, Carl & He, Xue-Zhong, 2003. "Dynamics of beliefs and learning under aL-processes -- the heterogeneous case," Journal of Economic Dynamics and Control, Elsevier, vol. 27(3), pages 503-531, January. [Downloadable!] (restricted)
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  9. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," NBER Working Papers 7613, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  10. Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October. [Downloadable!] (restricted)
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  11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May. [Downloadable!] (restricted)
  12. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December. [Downloadable!]
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  13. Pesaran, M.H. & Timmermann, A., 1992. "Forecasting Stock Returns," Cambridge Working Papers in Economics 9216, Faculty of Economics, University of Cambridge.
  14. Tesfatsion, Leigh S. & Judd, Kenneth L., 2003. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers 10368, Iowa State University, Department of Economics. [Downloadable!]
  15. Allen, Helen & Taylor, Mark P, 1990. "Charts, Noise and Fundamentals in the London Foreign Exchange Market," Economic Journal, Royal Economic Society, vol. 100(400), pages 49-59, Supplemen. [Downloadable!] (restricted)
  16. 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. [Downloadable!] (restricted)
  17. Frankel, Jeffrey A & Froot, Kenneth A, 1986. "Understanding the U.S. Dollar in the Eighties: The Expectations of Chartists and Fundamentalists," The Economic Record, The Economic Society of Australia, vol. 0(0), pages 24-38, Supplemen.
  18. Gencay, Ramazan, 1998. "Optimization of technical trading strategies and the profitability in security markets," Economics Letters, Elsevier, vol. 59(2), pages 249-254, May. [Downloadable!] (restricted)
  19. Christopher J. Neely, 1997. "Technical analysis in the foreign exchange market: a layman's guide," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 23-38. [Downloadable!]
  20. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-81, March. [Downloadable!] (restricted)
  21. Carl Chiarella & Xue-Zhong He, 2000. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model with a Market Maker," Research Paper Series 35, Quantitative Finance Research Centre, University of Technology, Sydney. [Downloadable!]
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  22. Cars H. Hommes, 2005. "Heterogeneous Agent Models in Economics and Finance," Tinbergen Institute Discussion Papers 05-056/1, Tinbergen Institute. [Downloadable!]
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  23. repec:att:wimass:199530r is not listed on IDEAS
  24. Carl Chiarella & Xue-Zhong He, 1999. "The Dynamics of the Cobweb when Producers are Risk Averse Learners," Working Paper Series 90, School of Finance and Economics, University of Technology, Sydney. [Downloadable!]
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Bask, Mikael, 2007. "Long swings and chaos in the exchange rate in a DSGE model with a Taylor rule," Research Discussion Papers 19/2007, Bank of Finland. [Downloadable!]
  2. Stephan Schulmeister, 2007. "The Interaction Between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics," WIFO Working Papers 290, WIFO. [Downloadable!]
  3. Zwart, G.J. de & Markwat, T.D. & Swinkels, L. & Dijk, D.J.C. van, 2007. "The Economic Value of Fundamental and Technical Information in Emerging Currency Markets," Research Paper ERS-2007-096-F&A Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
    Other versions:
  4. Verbic, Miroslav, 2006. "Memory and Asset Pricing Models with Heterogeneous Beliefs," MPRA Paper 1261, University Library of Munich, Germany. [Downloadable!]
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