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t-Statistic Trend Strength
rank by how *reliable* the trend is, not how big the return is
Ranking assets by the t-statistic of an OLS log-price slope (trend consistency) instead of raw return favors steady trends over lucky spikes; recent work on a century of industry trends reports t-stat-based trend estimation cut portfolio turnover ~66% while preserving edge, directly attacking the transaction-cost failure mode. Distinct from residual momentum (regression *residual return*) — here the signal is the *slope significance* of the asset's own price.
Universe
12 liquid multi-asset ETFs (SPY, QQQ, IWM, EFA, EEM, TLT, IEF, GLD, DBC, VNQ, HYG, LQD).
How it works
each month regress log price on time over 126 days, rank by slope t-stat, long the top positive-and-significant names equal-weight, hold monthly (low turnover from the smoothed signal).
Expected performance
Research-derived Sharpe estimate: 0.6–1.0.
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 Rank 12 multi-asset ETFs by t-statistic of 126-day log-price trend slope, hold top positive-trend names, monthly rebalance
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Research & sources
- arxiv.org — arxiv.org
- alphaarchitect.com — alphaarchitect.com
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Not financial advice. This page describes a research idea, not a recommendation. Any performance figures are hypothetical, research-derived estimates and are not indicative of future results. SignalChain is a research and educational tool; you are solely responsible for any decisions you make.