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The Impact of Technical Analysis on Asset Price Dynamics

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  • J.-H. Steffi Yang
  • Satchell, S.E.

Abstract

We study the impact of technical analysis in a context of heterogeneous, utility-maximising agents. A framework is provided to capture observed diversity in forecast estimates as a result of interaction between prior beliefs and asymmetric information. Using investment decisions of fundamentalists as a benchmark, agents’ optimal demand difference, which reflects expectation heterogeneity and the use of technical analysis, offers insights into the endogenous uncertainly in asset pricing behaviour. Technical analysis results in price feedback. We define a new family of feedback rules over cumulative distribution functions. Using bifurcation analysis, we show how prices asymptotically approach equilibrium and how significant feedback effects drive them off the equilibrium path. Both trend chasing strategy and contrarian strategy among technical trades are described in the model: the latter leads prices to overshoot the fundamental value with a high frequency; whereas in the former case, prices exhibit prolonged cyclic behaviour.

Suggested Citation

  • J.-H. Steffi Yang & Satchell, S.E., 2002. "The Impact of Technical Analysis on Asset Price Dynamics," Cambridge Working Papers in Economics 0219, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:0219
    Note: EM (updated August 2003)
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    1. Sentana, Enrique & Wadhwani, Sushil B, 1992. "Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data," Economic Journal, Royal Economic Society, vol. 102(411), pages 415-425, March.
    2. Marco Pagano, 1989. "Endogenous Market Thinness and Stock Price Volatility," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(2), pages 269-287.
    3. C. Chiarella & X-Z. He, 2001. "Asset price and wealth dynamics under heterogeneous expectations," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 509-526.
    4. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    5. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
    6. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    7. 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 181-185, May.
    8. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    9. M. A. H. dempster & C. M. Jones, 2001. "A real-time adaptive trading system using genetic programming," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 397-413.
    10. Hommes, C.H., 2001. "Modeling the stylized facts in finance through simple nonlinear adaptive systems," CeNDEF Working Papers 01-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    11. 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.
    12. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    13. Levy, Moshe & Levy, Haim & Solomon, Sorin, 1994. "A microscopic model of the stock market : Cycles, booms, and crashes," Economics Letters, Elsevier, vol. 45(1), pages 103-111, May.
    14. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
    15. 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.
    16. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    17. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    18. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    19. 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.
    20. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    21. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    22. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
    23. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    24. 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.
    25. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    26. Gaunersdorfer, Andrea, 2000. "Endogenous fluctuations in a simple asset pricing model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 799-831, June.
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    Cited by:

    1. Stefanescu, Razvan & Dumitriu, Ramona, 2016. "Particularitǎţi ale evoluţiei variabilelor financiare [Some particularities of the financial variables evolution]," MPRA Paper 73481, University Library of Munich, Germany, revised 02 Sep 2016.
    2. J-H Steffi Yang, 2004. "The Markovian Dynamics of "Smart Money"," Econometric Society 2004 Far Eastern Meetings 797, Econometric Society.
    3. Yang, J-H.S. & Satchell, S.E., 2003. "Endogenous Correlation," Cambridge Working Papers in Economics 0321, Faculty of Economics, University of Cambridge.

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    More about this item

    Keywords

    price dynamics; heterogeneity; bifurcation; feedback trading;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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