Trend following (momentum)
Rank winners versus losers on a lookback window; works until crowding, reversals, or a regime shift punishes trend followers.
Overview
Trend following (momentum) sits in the Futures chapter of the systematic catalog. On QUSXFI we treat it as a testable hypothesis: specify entries, exits, sizing, and costs—then ask whether edge survives out-of-sample scrutiny.
Discretionary traders often arrive at similar ideas intuitively; the quantitative version forces you to write the rule before you see the next bar. That discipline is what makes results reproducible—or exposes them as luck.
Based on the research catalog 151 Trading Strategies (Kakushadze & Serur, 2018), section 10.4. Educational summary—not a replication of the full formal definition.
Signal and Portfolio Construction
Trend following (momentum) ranks past winners and losers over a declared lookback, then tilts the book toward persistence. The catalog frames it this way: this strategy is equivalent to the optimization strategy (see Subsection 3. Your implementation must preserve that economic intent while making every parameter explicit.
Before backtesting Trend following (momentum), write the economic hypothesis in one sentence a risk manager would accept or reject.
Implementation and Research Process
Include at least one documented momentum crash month in Trend following (momentum) evaluation—not optional stress, core diligence.
Walk-forward Trend following (momentum) lookbacks; a single in-sample winner is an accident until confirmed out-of-sample.
For §10.4 Trend following (momentum), write the rule set so another researcher could replicate without you in the room.
Risk: What Breaks This Strategy
Momentum crashes—sharp reversals after crowded trends—are the signature tail risk of Trend following (momentum). Factor crowding and ETF flows accelerate the unwind.
Turnover and transaction costs scale with rebalance frequency; what worked gross of fees dies net.
Regime shifts (policy shocks, bear markets) can flip sign on the same lookback parameter that looked brilliant in the prior decade.
Common Mistakes to Avoid
- Stacking Trend following (momentum) with correlated sidebar strategies without netting exposures.
- Changing Trend following (momentum) parameters after each losing week—implicit discretion destroys reproducibility.
- Erasing losing Trend following (momentum) months instead of documenting regime breaks—that is how research firms stop learning.
- Optimizing Trend following (momentum) lookback on the same sample you report as final.
How to Study This Strategy
- Codify Trend following (momentum) signal, lag, rebalance, and vol-scaling rules without discretionary overrides.
- Identify the worst momentum crash month for Trend following (momentum) in-sample and replay it out-of-sample.
- Simulate Trend following (momentum) at two participation rates; note where capacity binds.
- Write Trend following (momentum) failure triggers: drawdown, turnover spike, sign flip on the signal.
- Run Trend following (momentum) walk-forward on a liquid universe; export turnover and sector exposures.
Key Takeaways
- Trend following (momentum) ranks past winners and losers—edge is conditional on trend persistence, not guaranteed by the lookback.
- Rebalance frequency and universe for Trend following (momentum) drive turnover; gross returns without fees mislead.
- Momentum crashes cluster after crowded trends—include crash months in evaluation, not just CAGR.
- Regime shifts can flip sign on the same parameter that worked in the prior decade.
- Walk-forward Trend following (momentum); a single in-sample lookback winner is a research accident until confirmed out-of-sample.
Learning Tip
Change one Trend following (momentum) parameter at a time; simultaneous tweaks are how researchers lie to themselves.
Explore related strategies in the sidebar or return to the full catalog.