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BREAKING INTO THE BLACKBOX: Trend Following, Stop Losses, and the Frequency of Trading: the case of the S&P500

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  • Andrew Clare
  • James Seaton
  • Peter N Smith
  • Stephen Thomas

Abstract

In this paper we compare a variety of technical trading rules in the context of investing in the S&P500 index. These rules are increasingly popular both among retail investors and CTAs and similar investment funds. We find that a range of fairly simple rules, including the popular 200-day moving average trading rule, dominate the long only, passive investment in the index. In particular, using the latter rule we find that popular stop loss rules do not add value and that monthly end of month investment decision rules are superior to those which trade more frequently: this adds to the growing view that trading can damage your wealth. Finally we compare the MA rule with a variety of simple fundamental metrics and find the latter far inferior to the technical rules over the last 60 years of investing.

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Bibliographic Info

Paper provided by Department of Economics, University of York in its series Discussion Papers with number 12/11.

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Date of creation: Apr 2012
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Handle: RePEc:yor:yorken:12/11

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Keywords: trend following; S&P500; stop losses; trading frequency; fundamental investment metrics.;

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  1. Szakmary, Andrew C. & Shen, Qian & Sharma, Subhash C., 2010. "Trend-following trading strategies in commodity futures: A re-examination," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 409-426, February.
  2. Park, Cheol-Ho & Irwin, Scott H., 2005. "The Profitability of Technical Trading Rules in US Futures Markets: A Data Snooping Free Test," AgMAS Project Research Reports 14771, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
  3. Philip H. Dybvig, 1988. "Inefficient Dynamic Portfolio Strategies or How to Throw Away a Million Dollars in the Stock Market," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 67-88.
  4. 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.
  5. Robert A. Korajczyk & Ronnie Sadka, 2004. "Are Momentum Profits Robust to Trading Costs?," Journal of Finance, American Finance Association, vol. 59(3), pages 1039-1082, 06.
  6. Gollier, Christian, 1997. "On the Inefficiency of Bang-Bang and Stop-Loss Portfolio Strategies," Journal of Risk and Uncertainty, Springer, vol. 14(2), pages 143-54, March.
  7. Annaert, Jan & Osselaer, Sofieke Van & Verstraete, Bert, 2009. "Performance evaluation of portfolio insurance strategies using stochastic dominance criteria," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 272-280, February.
  8. Clare, A D & Thomas, S H & Wickens, M R, 1994. "Is the Gilt-Equity Yield Ratio Useful for Predicting UK Stock Returns?," Economic Journal, Royal Economic Society, vol. 104(423), pages 303-15, March.
  9. Miffre, Joelle & Rallis, Georgios, 2007. "Momentum strategies in commodity futures markets," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1863-1886, June.
  10. Lesmond, David A. & Schill, Michael J. & Zhou, Chunsheng, 2004. "The illusory nature of momentum profits," Journal of Financial Economics, Elsevier, vol. 71(2), pages 349-380, February.
  11. Kaminski, Kathryn & Lo, Andrew W., 2008. "When Do Stop-Loss Rules Stop Losses?," SIFR Research Report Series 63, Institute for Financial Research.
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