Profitable technical trading rules as a source of price instability
This model incorporates technical trading rules (TTRs) that extract information from the price, allowing the users to benefit from the information. Sustainable profits are possible as long as the price movements reflect changes in the security's intrinsic value. The choice to use the TTR rather than fundamental information is endogenous to the model. Increases in the popularity of the TTR can produce price bubbles and diminish the TTR's ability to extract a reliable signal. Large fluctuations in the TTR's popularity lead to unsustainable periods of positive profits coupled with long-term losses.
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Volume (Year): 3 (2003)
Issue (Month): 3 ()
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- 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.
- 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 1731-64, December.
- Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
- Sciubba, E., 1999.
"Asymmetric Information and Survival in Financial Markets,"
Cambridge Working Papers in Economics
9908, Faculty of Economics, University of Cambridge.
- Emanuela Sciubba, 2005. "Asymmetric information and survival in financial markets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 25(2), pages 353-379, 02.
- Chiarella, Carl & He, Xue-Zhong, 2003.
"Heterogeneous Beliefs, Risk, And Learning In A Simple Asset-Pricing Model With A Market Maker,"
Cambridge University Press, vol. 7(04), pages 503-536, September.
- 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.
- Bray, Margaret, 1982. "Learning, estimation, and the stability of rational expectations," Journal of Economic Theory, Elsevier, vol. 26(2), pages 318-339, April.
- Abreu, Dilip & Brunnermeier, Markus K., 2002. "Synchronization risk and delayed arbitrage," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 341-360.
- David Goldbaum, 2004.
"Market Efficiency and Learning in an Endogenously Unstable Environment,"
Working Papers Rutgers University, Newark
2004-002, Department of Economics, Rutgers University, Newark.
- Goldbaum, David, 2005. "Market efficiency and learning in an endogenously unstable environment," Journal of Economic Dynamics and Control, Elsevier, vol. 29(5), pages 953-978, May.
- David Goldbaum, 2001. "Market Efficiency and Learning in an Endogenously Unstable Environment," Computing in Economics and Finance 2001 105, Society for Computational Economics.
- 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.
- Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, 08.
- Andrew Lo & Harry Mamaysky & Jiang Wang, 1999. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Computing in Economics and Finance 1999 402, Society for Computational Economics.
- Goldbaum, David, 1999. "A nonparametric examination of market information: application to technical trading rules," Journal of Empirical Finance, Elsevier, vol. 6(1), pages 59-85, January.
- Rendleman, Richard Jr. & Jones, Charles P. & Latane, Henry A., 1982. "Empirical anomalies based on unexpected earnings and the importance of risk adjustments," Journal of Financial Economics, Elsevier, vol. 10(3), pages 269-287, November.
- 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.
- 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.
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