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See every pattern that fits.

Set your own requirements, like win rate, average gain, risk, window length and entry month. The scanner returns only the patterns that meet them, across the stocks, ETFs and futures we track.

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Recurring Trade Seasonal Scanner showing 33 filtered seasonal patterns graded A+, with average gain, win rate, correlation and alpha for each

Filter for a pattern. Test it. Build around it.

Seasonal Scanner skip the ticker-by-ticker search

Patterns across the tracked universe are ranked and graded, so you filter for A+ instead of scrolling a chart library. Every row shows the average gain, win rate, worst historical trade, structural correlation across eras and alpha, not just a return number.

Filter by grade, filter set, or Core versus Technical signal type
Hover any grade to see exactly why it scored the way it did
Select any row and monitor it, or send it straight to backtesting

Example: The view above applies 8 filters (alpha score, convergence, win rate, average gain, grade and more) and returns 33 patterns: 2 active windows and 31 upcoming.

How a grade is built

One A+ to F grade, compressed from six checks.

Return quality: Average gain, win rate and consistency of the window.
Risk-adjustment: Sortino ratio, so downside counts more than upside.
Structural correlation: Whether 5-year, 15-year and full-history eras agree.
Statistical significance: A p-value on the pattern, so noise doesn't pass as edge.
Walk-forward validation: 3-window out-of-sample tests on data the pattern never saw.
Tail-risk caps: A worst historical trade of -12% or worse keeps a pattern from earning A+, and deeper losses cap the grade lower still.

One-Click Backtesting don't take the grade's word for it

Select any pattern and get a full backtest: total return, CAGR, active alpha versus a benchmark, Sharpe ratio, max drawdown and a hypothetical $10,000 growth curve, plus a Monte Carlo stress test to see how the strategy holds up outside the exact historical path.

Performance: total return, CAGR, active alpha, win rate and profit factor
Risk: max drawdown, active exposure, worst year and Sharpe ratio
Robustness: a 1,000-simulation test and a Monte Carlo stress test on the same pattern

Example: A backtest of ALAB's seasonal pattern over the past 3 years returned a 66.7% win rate and a 16.56% CAGR, against 1.67% for SPY. ALAB has only a short history, so the same screen also flags a noisy p-value. Hypothetical results, net of an estimated 15 bps round-trip cost.

Backtest analysis with performance and risk metrics, a hypothetical growth curve and a Monte Carlo stress test

Correlation Screener build a basket that's actually diversified

Once you have patterns you like, scan for the assets that move least in step with your benchmark, and assemble an uncorrelated basket step by step.

Explore the Correlation Screener

Examples are illustrative. Backtest results are hypothetical, simulated on historical data, net of an estimated 15 bps round-trip cost, and exclude taxes and dividends. Past performance and historical win rates don't guarantee future results.

About the Seasonal Scanner

How often does the scanner update?

Patterns are recomputed every weekday evening from each asset's full price history, and the live status and returns of every window refresh every 15 minutes during market hours. A window that grades B today can move to A+, or drop off entirely, as new price data comes in.

What's the difference between the backtest and the grade?

The grade is a compressed score. The backtest is the full detail behind it: the trade-by-trade equity curve, drawdown and a Monte Carlo stress test on top, so you can see how a strategy would have behaved instead of trusting a single letter.

Does the scanner find short trades?

No. The engine only discovers long windows: entry at a seasonal trough, exit at a peak. A window whose history averaged negative is a weak long, not a tradeable short.

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Set your rules. See every pattern that fits.