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Re-evaluating Short- and Long-Term Trend Factors in CTA Replication: A Bayesian Graphical Approach

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  • Eric Benhamou
  • Jean-Jacques Ohana
  • Alban Etienne
  • B'eatrice Guez
  • Ethan Setrouk
  • Thomas Jacquot

Abstract

Commodity Trading Advisors (CTAs) have historically relied on trend-following rules that operate on vastly different horizons from long-term breakouts that capture major directional moves to short-term momentum signals that thrive in fast-moving markets. Despite a large body of work on trend following, the relative merits and interactions of short-versus long-term trend systems remain controversial. This paper adds to the debate by (i) dynamically decomposing CTA returns into short-term trend, long-term trend and market beta factors using a Bayesian graphical model, and (ii) showing how the blend of horizons shapes the strategy's risk-adjusted performance.

Suggested Citation

  • Eric Benhamou & Jean-Jacques Ohana & Alban Etienne & B'eatrice Guez & Ethan Setrouk & Thomas Jacquot, 2025. "Re-evaluating Short- and Long-Term Trend Factors in CTA Replication: A Bayesian Graphical Approach," Papers 2507.15876, arXiv.org.
    • Handle: RePEc:arx:papers:2507.15876
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    File URL: http://arxiv.org/pdf/2507.15876
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