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Technical Trading Rules and the Size of the Risk Premium in Security Returns

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Author Info

  • Gencay, R
  • Stengos, T

Abstract

Among analysts, technical trading rules are widely used for forecasting security returns. Recent literature provides edivende that these rules may provide positive profits after accounting for transaction costs. This would be contrary to the theory of the efficient market hypothesis which states that security prices cannot be forecasted from their past values or other past variables.

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Bibliographic Info

Paper provided by University of Guelph, Department of Economics in its series Working Papers with number 1996-11.

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Length: 23 pages
Date of creation: 1996
Date of revision:
Handle: RePEc:gue:guelph:1996-11

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Web page: http://www.economics.uoguelph.ca/index.htm
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Keywords: FINANCIAL MARKET; RISK; TRADE;

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Cited by:
  1. Cheol-Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, 09.
  2. Neely, Christopher J., 2003. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 69-87.
  3. Fernando Fernández-Rodríguez & Christian González-Martel* & Simón Sosvilla-Rivero, . "On the profitability of technical trading rules based on arifitial neural networks : evidence from the Madrid stock market," Working Papers 99-07, FEDEA.
  4. Mariano Matilla-Garcia & Carlos Arguello, 2005. "A hybrid approach based on neural networks and genetic algorithms to the study of profitability in the Spanish Stock Market," Applied Economics Letters, Taylor and Francis Journals, vol. 12(5), pages 303-308.
  5. Bokhari, Jawaad & Cai, Charlie & Hudson, Robert & Keasey, Kevin, 2005. "The predictive ability and profitability of technical trading rules: does company size matter?," Economics Letters, Elsevier, vol. 86(1), pages 21-27, January.
  6. Nam, Kiseok & Washer, Kenneth M. & Chu, Quentin C., 2005. "Asymmetric return dynamics and technical trading strategies," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 391-418, February.
  7. 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.
  8. Bill Cai & Charlie Cai & Kevin Keasey, 2005. "Market Efficiency and Returns to Simple Technical Trading Rules: Further Evidence from U.S., U.K., Asian and Chinese Stock Markets," Asia-Pacific Financial Markets, Springer, vol. 12(1), pages 45-60, March.
  9. Nowman, K. Ben & Saltoglu, Burak, 2003. "Continuous time and nonparametric modelling of U.S. interest rate models," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 25-34.
  10. Kwang-il Choe & Joshua Krausz & Kiseok Nam, 2011. "Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 36(3), pages 323-353, April.
  11. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
  12. Yochanan Shachmurove & Uri BenZion & Paul Klein & Joseph Yagil, 2001. "A Moving Average Comparison of the Tel-Aviv 25 and S&P 500 Stock Indices," Penn CARESS Working Papers 4731f3394c43bebf4d3191c81, Penn Economics Department.

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