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Technical analysis, spread trading, and data snooping control

Author

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  • Psaradellis, Ioannis
  • Laws, Jason
  • Pantelous, Athanasios A.
  • Sermpinis, Georgios

Abstract

This paper utilizes a large universe of 18,410 technical trading rules (TTRs) and adopts a technique that controls for false discoveries to evaluate the performance of frequently traded spreads using daily data over 1990–2016. For the first time, the paper applies an excessive out-of-sample analysis in different subperiods across all TTRs examined. For commodity spreads, the evidence of significant predictability appears much stronger compared to equity and currency spreads. Out-of-sample performance of portfolios of significant rules typically exceeds transaction cost estimates and generates a Sharpe ratio of 3.67 in 2016. In general, we reject previous studies’ evidence of a uniformly monotonic downward trend in the selection of predictive TTRs over 1990–2016.

Suggested Citation

  • Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    • Handle: RePEc:eee:intfor:v:39:y:2023:i:1:p:178-191
    DOI: 10.1016/j.ijforecast.2021.10.002
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