Screen U.S. stocks for recurring historical opportunities
A U.S. stock screener can help reduce a very large market into a manageable watchlist. For seasonal research, the goal is to identify recurring historical windows and then inspect whether those patterns were stable across different market regimes.
Why the U.S. market is well suited to screening
The U.S. market offers a deep universe of liquid stocks across sectors, industries and market-cap ranges. That makes screening useful—but it also increases the risk of finding attractive historical patterns simply because you tested many symbols.
What to filter first
- Minimum historical sample size
- Reasonable trading history
- Win rate and average return together
- Calendar-window length
- Direction of the historical pattern
What to verify afterward
- Best and worst individual years
- 10-, 20- and 25-year stability
- Whether recent years still resemble the long-term result
- Whether one outlier dominates the average
| Research question | Why it matters |
|---|---|
| Is the stock old enough? | Short histories provide fewer observations and can make patterns look stronger than they are. |
| Is the pattern broad or narrow? | A two-week window and a six-month window answer very different questions. |
| Does the pattern survive multiple lookbacks? | Robust behavior should not depend completely on one chosen sample. |
| Does the stock behave differently from the index? | Stock-specific seasonality can diverge from broader market seasonality. |
A practical U.S. screening workflow
Choose a broad universe
Start with U.S.-listed stocks rather than cherry-picking names you already expect to work.
Set objective thresholds
Decide your minimum sample and win-rate criteria before reviewing the results.
Validate the shortlist
Open each candidate in the historical dashboard and inspect every year.
Screen U.S. stocks for free
Use the screener to find candidates and the dashboard to validate each historical pattern.
Can I use this for U.S. stocks only?
The screening workflow is particularly relevant to U.S. stocks, but market coverage depends on the symbols supported by the product.
Is more data always better?
More history gives more observations, but market structures change. That is why comparing multiple lookback periods is important.