Home / Ideas / Cross-asset time-series momentum (ETF trend)
Cross-asset time-series momentum (ETF trend)
go long/short each asset on its own 12-month trend, vol-scaled
Moskowitz, Ooi & Pedersen (2012, JFE) document robust time-series momentum across equity, bond, commodity and FX futures, with the effect strongest during extreme markets — i.e. it acts as a convex macro hedge. AQR's "Century of Evidence" (2017) confirms persistence across regimes. Highly relevant now given divergent 2026 central-bank paths (Fed easing debate, rangebound Treasuries, USD softening early-year).
Why it's relevant now
2026 outlooks flag a range-bound-but-transitioning rate regime and a potentially weakening then rebounding dollar — a fertile, directional cross-asset environment where per-asset trend signals diverge rather than move as one beta.
Universe
Cross-asset ETF sleeve — SPY (equity), TLT/IEF (rates), GLD (gold), DBC (commodities), UUP (USD), HYG (credit).
How it works
Each month, go long assets with positive trailing 12-month excess return and short those negative, sizing each position inversely to its trailing realized volatility (target ~10-15% portfolio vol), hold 1 month.
Expected performance
Research-derived Sharpe estimate: 0.5–0.9. Quantpedia reports 1.31 gross on the 58-instrument futures universe 1965-2009; discounted heavily for ETF-only proxies, monthly rebalance and costs).
Backtest this idea with SignalChain
This is a research lead — not a finished backtest. SignalChain takes an idea like this and runs the whole pipeline inside Claude Code: it researches the concept against academic and practitioner sources, sets benchmarks, writes and lints a VectorBT backtest, runs it, and grades the result PASS/FAIL. One command:
/signalchain Time-series momentum across SPY TLT IEF GLD DBC UUP HYG: monthly long positive / short negative 12-month trend, volatility-scaled sizing
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Research & sources
- quantpedia.com — quantpedia.com
- sciencedirect.com — sciencedirect.com
- blackrock.com — blackrock.com
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