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Back to the future: an empirical investigation into the validity of stock index models over time

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  • Barbara Summers
  • Evan Griffiths
  • Robert Hudson

Abstract

The use of technical analysis to predict security price movements from past price series has been supported by a number of academic research studies. These studies are broadly based on the premise that a technical trading rule should have constant validity over time. This premise is in accord with the practitioner rational for technical analysis, which is that, in the securities markets, history tends to repeat itself due to the relative constancy of human behaviour. The primary purpose of this paper is to investigate the extent to which technical trading rules have constant validity over time by determining the extent to which rules derived entirely from a particular time period can have validity over a variety of different time periods. It is found that rules derived from the data from the early period can be predictive at a later date and, rather unexpectedly, can even exceed the predictive power of rules derived from more contemporary data. It is hypothesized that this may be due to a decreasing signal to noise ratio in the data as the volatility of the index increases over time. The findings tend to support the assertion that, with respect to share trading, 'history repeats itself' with the caveat that there are factors that confound modelling in later periods.

Suggested Citation

  • Barbara Summers & Evan Griffiths & Robert Hudson, 2004. "Back to the future: an empirical investigation into the validity of stock index models over time," Applied Financial Economics, Taylor & Francis Journals, vol. 14(3), pages 209-214.
    • Handle: RePEc:taf:apfiec:v:14:y:2004:i:3:p:209-214
    DOI: 10.1080/0960310042000187351
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    References listed on IDEAS

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    1. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
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