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Time series momentum trading strategy and autocorrelation amplification

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  • K. J. Hong
  • S. Satchell

Abstract

This paper investigates why general Moving Average (MA) trading rules are widely used by technical analysts and others. We assume general stationary processes for prices and we derive the autocorrelation function for an MA trading rule. Based on our results, we conjecture that autocorrelation amplification is one of the reasons why such trading rules are popular. Using simulated results, we show that the MA rule may be popular because it can identify price momentum and is a simple way of assessing and exploiting the price autocorrelation structure without necessarily knowing its precise structure. This paper then, provides empirical evidence of autocorrelation amplification using 15-year daily price data for 11 major international stock indices.

Suggested Citation

  • K. J. Hong & S. Satchell, 2015. "Time series momentum trading strategy and autocorrelation amplification," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1471-1487, September.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:9:p:1471-1487
    DOI: 10.1080/14697688.2014.1000951
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    8. Mahsa Ghorbani & Edwin K P Chong, 2020. "Stock price prediction using principal components," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
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