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Technical analysis: An asset allocation perspective on the use of moving averages

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Author Info

  • Zhu, Yingzi
  • Zhou, Guofu

Abstract

In this paper, we analyze the usefulness of technical analysis, specifically the widely employed moving average trading rule from an asset allocation perspective. We show that, when stock returns are predictable, technical analysis adds value to commonly used allocation rules that invest fixed proportions of wealth in stocks. When uncertainty exists about predictability, which is likely in practice, the fixed allocation rules combined with technical analysis can outperform the prior-dependent optimal learning rule when the prior is not too informative. Moreover, the technical trading rules are robust to model specification, and they tend to substantially outperform the model-based optimal trading strategies when the model governing the stock price is uncertain.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Financial Economics.

Volume (Year): 92 (2009)
Issue (Month): 3 (June)
Pages: 519-544

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Handle: RePEc:eee:jfinec:v:92:y:2009:i:3:p:519-544

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Web page: http://www.elsevier.com/locate/inca/505576

Related research

Keywords: Technical analysis Trading rules Asset allocation Predictability Learning;

References

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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.:
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  1. Yacine Ait-Sahalia & Michael W. Brandt, 2001. "Variable Selection for Portfolio Choice," NBER Working Papers 8127, National Bureau of Economic Research, Inc.
  2. Lubos Pastor & Robert F. Stambaugh, . "Comparing Asset Pricing Models: An Investment Perspective," Rodney L. White Center for Financial Research Working Papers 16-99, Wharton School Rodney L. White Center for Financial Research.
  3. LeBaron, B., 1996. "Technical Trading Rule Profitability and Foreing Exchange Intervention," Working papers 9445r, Wisconsin Madison - Social Systems.
  4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
  5. John Y. Campbell & Luis M. Viceira, 1996. "Consumption and Portfolio Decisions When Expected Returns are Time Varying," NBER Working Papers 5857, National Bureau of Economic Research, Inc.
  6. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
  7. Wachter, Jessica A., 2002. "Portfolio and Consumption Decisions under Mean-Reverting Returns: An Exact Solution for Complete Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(01), pages 63-91, March.
  8. Gennotte, Gerard, 1986. " Optimal Portfolio Choice under Incomplete Information," Journal of Finance, American Finance Association, vol. 41(3), pages 733-46, July.
  9. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
  10. 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.
  11. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
  12. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
  13. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, 02.
  14. G. William Schwert, 2002. "Anomalies and Market Efficiency," NBER Working Papers 9277, National Bureau of Economic Research, Inc.
  15. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-67.
  16. Amit Goyal & Ivo Welch, 2002. "Predicting the Equity Premium With Dividend Ratios," NBER Working Papers 8788, National Bureau of Economic Research, Inc.
  17. Thomas Gehrig & Lukas Menkhoff, 2006. "Extended evidence on the use of technical analysis in foreign exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 327-338.
  18. 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.
  19. 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.
  20. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
  21. Jun Liu, 2007. "Portfolio Selection in Stochastic Environments," Review of Financial Studies, Society for Financial Studies, vol. 20(1), pages 1-39, January.
  22. 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.
  23. Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, 02.
  24. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
  25. Lixin Huang & Hong Liu, 2007. "Rational Inattention and Portfolio Selection," Journal of Finance, American Finance Association, vol. 62(4), pages 1999-2040, 08.
  26. Campbell, John, 1987. "Stock Returns and the Term Structure," Scholarly Articles 3207699, Harvard University Department of Economics.
  27. Neely, Christopher J., 2002. "The temporal pattern of trading rule returns and exchange rate intervention: intervention does not generate technical trading profits," Journal of International Economics, Elsevier, vol. 58(1), pages 211-232, October.
  28. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
  29. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-82, May.
  30. Michael W. Brandt & Pedro Santa-Clara, 2006. "Dynamic Portfolio Selection by Augmentingthe Asset Space," Journal of Finance, American Finance Association, vol. 61(5), pages 2187-2217, October.
  31. Grundy, Bruce D. & Kim, Youngsoo, 2002. "Stock Market Volatility in a Heterogeneous Information Economy," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(01), pages 1-27, March.
  32. Kim, Tong Suk & Omberg, Edward, 1996. "Dynamic Nonmyopic Portfolio Behavior," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 141-61.
  33. Yihong Xia, 2001. "Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," Journal of Finance, American Finance Association, vol. 56(1), pages 205-246, 02.
  34. Shleifer, Andrei, 2000. "Inefficient Markets: An Introduction to Behavioral Finance," OUP Catalogue, Oxford University Press, number 9780198292272.
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Citations

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Cited by:
  1. Scholz, Peter, 2012. "Size matters! How position sizing determines risk and return of technical timing strategies," CPQF Working Paper Series 31, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
  2. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
  3. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
  4. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
  5. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  6. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
  7. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
  8. Dai, Min & Li, Peifan & Zhang, Jin E., 2010. "A lattice algorithm for pricing moving average barrier options," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 542-554, March.
  9. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2011. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Working Papers CoFie-02-2011, Sim Kee Boon Institute for Financial Economics.
  10. Xue-Zhong He & Kai Li, 2014. "Time Series Momentum and Market Stability," Research Paper Series 341, Quantitative Finance Research Centre, University of Technology, Sydney.
  11. Ko, Kuan-Cheng & Lin, Shinn-Juh & Su, Hsiang-Ju & Chang, Hsing-Hua, 2014. "Value investing and technical analysis in Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 14-36.
  12. Carl Chiarella & Xue-Zhong He & Remco C.J. Zwinkels, 2014. "Heterogeneous Expectations in Asset Pricing:Empirical Evidence from the S&P500," Research Paper Series 344, Quantitative Finance Research Centre, University of Technology, Sydney.

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