Introducing Time Series Momentum for after-work quants

Takeaway. Time-series momentum (TSMOM) is trend-following on each instrument’s own past return: go long if recent performance was positive, short if negative—classic futures/CTA logic in research form.

Time Series Momentum (Tobias Moskowitz, Yao Hua Ooi, Lasse Heje Pedersen, 2012) is the after-work companion to cross-sectional Jegadeesh–Titman momentum.

Fit for learners: Trend-following on each asset’s own past returns—simple futures CTA logic in code.

This Hub note is a plain-language intro. Not investment advice. Pair with Jegadeesh–Titman and value & momentum everywhere.

The problem

Cross-sectional momentum ranks winners vs losers relative to peers. Many futures/CTA stories instead care whether this contract is trending up or down on its own clock. Mixing the two confuses notebooks.

The idea / core intuition

• For each asset, look at its own past return over a formation window.
• Position with the sign of that past return (details/vol scaling in the paper).
• Document TSMOM across asset classes in the study’s sample.
• Distinct from—but related to—cross-sectional momentum; both can appear in the same markets.

Research pattern—not a managed-futures product recommendation.

Why after-work Python learners care

TSMOM is almost the simplest multi-asset strategy skeleton: sign(past_return) → position → plot. Ideal first futures-style notebook after you can align dates.

Tiny evening exercise: on 3 toy futures return series, compute 12-month past return each month; set position = sign; print hit-rate of sign(past) vs next-month return sign—learning only.

One-evening reading checklist

1. Contrast TSMOM vs cross-sectional momentum in one line each.
2. Note why volatility scaling often appears in CTA-style recipes.
3. Name asset classes the paper emphasises.
4. List one crash/whipsaw risk trend systems face.

Download PDF

Download PDF

Landing / DOI: JFE / ScienceDirect

Important disclaimer

Not investment advice. This Hub note is educational only. TSMOM is academic research—not advice to trade futures or CTAs.

What this is not

• Not CEF / subsidy framing
• Not Quant or Macro course CTA
• Not a CTA fund advertisement

Next step

Single course CTA: SoloQuant Academy’s Introduction to Python Programming—date indexes and plots first; then TSMOM skeletons stop feeling mysterious.