Glossary
Plain-English definitions of the concepts and metrics you’ll see across SeasonalityX — so you can read every pattern with confidence.
Core concepts
Seasonal Pattern
A recurring tendency for a stock to move in a similar direction during the same calendar dates each year.
Example: Apple (AAPL) has risen between July 1 and July 11 in 9 of the last 10 years — that recurring behaviour is a seasonal pattern.
Seasonal Trend
The overall direction a seasonal pattern leans toward across the historical years. A pattern that was positive in most years has a bullish trend; one that was mostly negative has a bearish trend.
Example: If a stock fell during the same two weeks in 8 of 10 years, its seasonal trend for that window is bearish.
Bullish Pattern
A seasonal pattern that has historically tended to move up (a positive average return) during its date range.
Example: A window averaging +4% over the past 10 years is shown as Bullish.
Bearish Pattern
A seasonal pattern that has historically tended to move down (a negative average return) during its date range.
Example: A window averaging −3% over the past 10 years is shown as Bearish.
Historical Performance
How a pattern actually played out in each past year — the individual yearly returns behind the average — so you can judge whether an average is driven by steady results or a few outliers.
Example: Two patterns both average +4%, but one earned roughly +4% every year while the other had several flat years and one huge +20% year. Historical performance reveals that difference.
Metrics
Average Return
The typical return of a pattern over its time period, averaged across all the historical years analysed.
Example: If a 20-day window returned +5%, +3%, and +4% over three years, its average return is +4%.
Annualized Return (%/yr)
The pattern's average return scaled to a yearly rate, so windows of different lengths can be compared on equal footing. It assumes the same pace of return continued for a full year and does not mean you would actually earn that much.
Example: A 10-day window averaging +4% annualizes to a much higher %/yr than a 60-day window averaging +4%, because it achieves the move in far less time.
Win Rate (%)
The share of historical years in which the pattern was profitable. Higher means more consistent.
Example: A 90% win rate over 10 years means the pattern was positive in 9 of those 10 years.
Standard Deviation
A measure of how much the yearly returns varied around the average. A low number means the result was steady year to year; a high number means it swung widely. Lower is generally more dependable.
Example: Two patterns both average +4%, but the one with the lower standard deviation delivered that +4% more reliably.
Pattern Strength
An at-a-glance star rating that combines average return, win rate, and consistency (standard deviation) into one score, so you can compare patterns quickly without reading every number.
Example: A ★★★★★ pattern has a strong average return, a high win rate, and steady year-to-year results.
Current Year Return
How the pattern's date range has performed so far in the current year. It is shown as “—” when this year's window hasn't occurred yet.
Example: For a pattern that runs July 1–11, the current-year return appears only once those dates have passed this year.
Filters & inputs
Seasonal Time Period
How many trading days a pattern is measured over, starting from a recurring date — also called the holding window. On the Pattern Finder you can scan several at once.
Example: A 20-day period measures the return from a start date through the next 20 trading days. Entering “10,20,30” scans all three lengths.
Historical Years
How many past years of price data the analysis looks at. More years generally make a pattern more reliable, since it has repeated more often.
Example: Setting “10 years” checks how the same date range behaved in each of the last 10 years. (Free plan: up to 5 years; paid plans: up to 20.)
Min Average Return (%)
A filter that hides weaker patterns by showing only those whose average return across the historical years is at least the value you set.
Example: Set it to 3% to hide any pattern that historically averaged less than a 3% move.
Min Win Rate (%)
A filter that shows only patterns that were profitable in at least the chosen percentage of historical years.
Example: Set it to 70% to focus on patterns that worked in 7 out of every 10 years or better.
Features
Upcoming Opportunity
A seasonal pattern whose recurring start date is coming up soon — within the range you choose — so you can prepare before the window opens.
Example: On the Dashboard, “Next 7 days” surfaces patterns whose historical start date lands within the coming week.
Watchlist
Your personal list of stocks. The Dashboard uses it to surface upcoming seasonal opportunities tailored to the stocks you care about.
Example: Add AAPL, MSFT, and RELIANCE.NS to your watchlist to see only their upcoming windows. (Free: up to 2 stocks; Pro: 25; Premium: unlimited.)
Saved Patterns
Individual patterns you bookmark so you can revisit them later without re-running the analysis.
Example: Star a promising AAPL window and find it again on your Saved page.
Compare
A tool that puts two stocks side by side so you can see which has the stronger, more reliable seasonal edge for a given period.
Example: Compare AAPL vs MSFT to see which has the better-rated seasonal pattern. (Premium feature.)
Alerts
Notifications that let you know when a saved or watchlisted pattern's window is approaching, so you don't miss it.
Example: Get an alert a few days before one of your saved patterns is due to begin.
Ready to put these into practice?
Our step-by-step tutorials walk you through finding, reading, and acting on seasonal patterns.
Browse TutorialsThese definitions are for educational purposes only and are not financial advice. Past seasonal patterns do not guarantee future performance.