Earnings-momentum
Rank winners versus losers on a lookback window; works until crowding, reversals, or a regime shift punishes trend followers.
Overview
Earnings-momentum sits in the Stocks 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 3.2. Educational summary—not a replication of the full formal definition.
Signal and Portfolio Construction
Earnings-momentum ranks past winners and losers over a declared lookback, then tilts the book toward persistence. The catalog frames it this way: This strategy amounts to buying winners and selling losers as in the price-momentum strategy, but the selection criterion is based on earnings. Your implementation must preserve that economic intent while making every parameter explicit.
Map every input Earnings-momentum needs in Stocks—prices, vol surfaces, fundamentals, or legal milestones—and verify point-in-time integrity.
Implementation and Research Process
Run Earnings-momentum with and without vol scaling; report turnover and capacity at 5% and 10% of ADV participation.
Walk-forward Earnings-momentum lookbacks; a single in-sample winner is an accident until confirmed out-of-sample.
Decompose Earnings-momentum into signal, portfolio construction, and execution modules—each must be path-independent given the same historical tape.
Risk: What Breaks This Strategy
Momentum crashes—sharp reversals after crowded trends—are the signature tail risk of Earnings-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
- Reporting Earnings-momentum backtests without fees, slippage, and realistic fill rules.
- Erasing losing Earnings-momentum months instead of documenting regime breaks—that is how research firms stop learning.
- Deploying Earnings-momentum live before paper trading through at least one adverse Stocks month.
- Confusing this educational Earnings-momentum summary with compliance-approved investment advice.
How to Study This Strategy
- Identify the worst momentum crash month for Earnings-momentum in-sample and replay it out-of-sample.
- Simulate Earnings-momentum at two participation rates; note where capacity binds.
- Codify Earnings-momentum signal, lag, rebalance, and vol-scaling rules without discretionary overrides.
- Write Earnings-momentum failure triggers: drawdown, turnover spike, sign flip on the signal.
- Run Earnings-momentum walk-forward on a liquid universe; export turnover and sector exposures.
Key Takeaways
- Earnings-momentum ranks past winners and losers—edge is conditional on trend persistence, not guaranteed by the lookback.
- Rebalance frequency and universe for Earnings-momentum drive turnover; gross returns without fees mislead.
- Sector neutrality changes whether you trade pure trend or a constrained factor portfolio.
- Regime shifts can flip sign on the same parameter that worked in the prior decade.
- Walk-forward Earnings-momentum; a single in-sample lookback winner is a research accident until confirmed out-of-sample.
Learning Tip
Change one Earnings-momentum parameter at a time; simultaneous tweaks are how researchers lie to themselves.
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