What is market seasonality?

Market seasonality is the historical pattern of returns across calendar buckets — months, days of the month, weeks of the month, days of the week, or trading days of the year. It answers "where in the calendar are we, historically?" by averaging the period's return across the years that fall inside a chosen window. It is descriptive of the past, not predictive of the future.

How do you compute average return for a seasonality cell?

For each (unit, period_bucket, window) row, we take the unit's realized return for that period in each year that falls inside the window and average them arithmetically. A "January for ^GSPC over the last 20 years" cell averages the 20 individual January full-month returns. Daily returns are adjusted-close-based; period returns are compounded from daily returns inside the bucket.

What does win_rate mean in a seasonality table?

win_rate is the fraction of contributing years whose period return was strictly greater than zero. A win_rate of 0.70 over 20 years means 14 of the 20 years were positive in that period and 6 were not. Years that closed exactly flat do not count as wins.

Does TickerStance seasonality account for survivorship bias?

Indexes (^GSPC, ^NDX, ^RUT, ^DJI) and sector SPDR ETFs are single-ticker series and carry no survivorship bias. Fama-French 49 industries and individual tickers are survivorship-biased: the universe contains only tickers still listed and still in Massive's coverage today, so failed-and-delisted companies are absent and aggregates lean optimistic — especially in windows that included the 2000–2002 dot-com bust, 2008–2009 GFC, and 2020-03 COVID shock.

How far back does the data go?

Indexes and sector ETFs reach roughly 25 to 30 years from the yfinance one-shot seed. Fama-French 49 industries and individual tickers reach roughly 10 years from Massive, with a planned upgrade to 20 years. The 30-year window toggle is therefore meaningful for indexes and ETFs only until the Massive history upgrade lands.

Can I use seasonality as a trading signal?

No. TickerStance reports historical patterns, not forecasts. A positive average return in a calendar bucket says only that the period has tended to be positive across the available history — the dispersion across years is wide, market structure changes between cycles, and the survivorship caveat on stock-level layers tilts averages upward. Pair seasonality context with the regime read (Stance) and your own risk plan; do not use it as a standalone trigger.

How often is the seasonality data recomputed?

Monthly, on the first of each month after US market close, via a dedicated systemd timer on the VPS. Daily recompute would only shift averages by parts per million and is not worth the work. On-demand recompute is available via pnpm seasonality:recompute when a backfill changes the underlying daily_bars history.

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Home/Seasonality

Where in the calendar are we?

Historical returns by month, day, and weekday — across indexes, sectors, industries, and individual tickers. Seasonality is a backdrop, not a signal.

TodayMon, Jun 15, 2026Trading day 115 of 252Week 24 · DoW Mon close

UNIT

index, sector, industry, or ticker

HISTORY WINDOW

10y · 20y · 30y · ALL

GRANULARITY

year-by-year or aggregate

Per yearAggregate

AS OF TODAY · June 15, 2026

We're entering June — historically a strong month for Real Estate.

Over 10 years, June has averaged +1.08% with a 80% win rate.

+1.08%

June avg · 10y

LAYER A · CALENDAR HEATMAP

Monthly returns, year by year.

Where in the calendar are we, historically? Index, sector, industry, and ticker views over the chosen window.

11Y of history

XLREReal EstateMonthly returns by year · 2015–2026

11y of history

Year

2026

+2.7%

+5.8%

-6.9%

+8.7%

-0.9%

+3.1%

—

2025

+1.8%

+4.2%

-3.0%

-1.3%

+1.0%

-0.7%

-0.0%

+2.2%

-0.4%

-2.9%

+1.9%

-3.2%

2024

-4.8%

+2.6%

+1.1%

-8.4%

+5.1%

+0.9%

+7.2%

+5.7%

+2.6%

-3.3%

+4.2%

-9.6%

2023

+9.9%

-5.9%

-2.2%

+1.0%

-4.5%

+4.6%

+1.3%

-3.1%

-8.0%

-2.8%

+12.5%

+7.6%

2022

-8.6%

-4.8%

+7.2%

-3.6%

-5.1%

-7.6%

+8.5%

-5.6%

-14.0%

+2.0%

+6.8%

-5.9%

2021

+0.5%

+1.6%

+5.8%

+8.3%

+1.1%

+2.5%

+4.6%

+2.8%

-6.8%

+7.6%

-0.9%

+9.3%

2020

+1.4%

-6.2%

-15.7%

+9.4%

+2.2%

+0.5%

+4.2%

-0.0%

-2.7%

-3.2%

+6.9%

+0.2%

2019

+10.7%

+1.1%

+4.4%

-0.5%

+1.2%

+0.8%

+1.7%

+4.8%

+0.3%

-0.0%

-1.7%

+0.1%

2018

-1.9%

-6.8%

+3.2%

-0.6%

+2.2%

+3.6%

+1.0%

+2.4%

-3.7%

-1.6%

+5.5%

-8.4%

2017

-0.1%

+4.7%

-1.7%

+0.2%

+0.7%

+1.1%

+1.2%

+1.0%

-2.1%

+0.8%

+2.9%

-1.5%

2016

-6.4%

+0.5%

+9.6%

-2.4%

+1.7%

+5.2%

+3.2%

-3.7%

-1.8%

-5.6%

-3.0%

+2.5%

2015

—

+2.4%

-0.6%

+1.4%

Avg

+0.5

-0.3

+0.2

+1.0

+0.4

+1.1

+3.3

+0.7

-3.6

-0.6

+3.1

-0.7

seasonality by year
Year	Jan	Feb	Mar	Apr	May	Jun (current)	Jul	Aug	Sep	Oct	Nov	Dec
2026	Jan 2026 avg: 2.68% n: 20	Feb 2026 avg: 5.82% n: 19	Mar 2026 avg: -6.87% n: 22	Apr 2026 avg: 8.74% n: 21	May 2026 avg: -0.92% n: 20	Jun 2026 avg: 3.11% n: 10 (current)	Jul 2026 no data n: 0	Aug 2026 no data n: 0	Sep 2026 no data n: 0	Oct 2026 no data n: 0	Nov 2026 no data n: 0	Dec 2026 no data n: 0
2025	Jan 2025 avg: 1.84% n: 20	Feb 2025 avg: 4.18% n: 19	Mar 2025 avg: -3.01% n: 21	Apr 2025 avg: -1.31% n: 21	May 2025 avg: 1.04% n: 21	Jun 2025 avg: -0.74% n: 20	Jul 2025 avg: -0.02% n: 22	Aug 2025 avg: 2.17% n: 21	Sep 2025 avg: -0.43% n: 21	Oct 2025 avg: -2.92% n: 23	Nov 2025 avg: 1.88% n: 19	Dec 2025 avg: -3.17% n: 22
2024	Jan 2024 avg: -4.82% n: 21	Feb 2024 avg: 2.57% n: 20	Mar 2024 avg: 1.07% n: 20	Apr 2024 avg: -8.45% n: 22	May 2024 avg: 5.14% n: 22	Jun 2024 avg: 0.95% n: 19	Jul 2024 avg: 7.24% n: 22	Aug 2024 avg: 5.73% n: 22	Sep 2024 avg: 2.57% n: 20	Oct 2024 avg: -3.29% n: 23	Nov 2024 avg: 4.17% n: 20	Dec 2024 avg: -9.62% n: 21
2023	Jan 2023 avg: 9.91% n: 20	Feb 2023 avg: -5.86% n: 19	Mar 2023 avg: -2.17% n: 23	Apr 2023 avg: 0.99% n: 19	May 2023 avg: -4.53% n: 22	Jun 2023 avg: 4.58% n: 21	Jul 2023 avg: 1.33% n: 20	Aug 2023 avg: -3.06% n: 23	Sep 2023 avg: -7.97% n: 20	Oct 2023 avg: -2.85% n: 22	Nov 2023 avg: 12.48% n: 21	Dec 2023 avg: 7.60% n: 20
2022	Jan 2022 avg: -8.63% n: 20	Feb 2022 avg: -4.80% n: 19	Mar 2022 avg: 7.21% n: 23	Apr 2022 avg: -3.56% n: 20	May 2022 avg: -5.11% n: 21	Jun 2022 avg: -7.60% n: 21	Jul 2022 avg: 8.52% n: 20	Aug 2022 avg: -5.62% n: 23	Sep 2022 avg: -13.95% n: 21	Oct 2022 avg: 2.00% n: 21	Nov 2022 avg: 6.83% n: 21	Dec 2022 avg: -5.89% n: 21
2021	Jan 2021 avg: 0.55% n: 19	Feb 2021 avg: 1.58% n: 19	Mar 2021 avg: 5.76% n: 23	Apr 2021 avg: 8.31% n: 21	May 2021 avg: 1.15% n: 20	Jun 2021 avg: 2.47% n: 22	Jul 2021 avg: 4.62% n: 21	Aug 2021 avg: 2.80% n: 22	Sep 2021 avg: -6.77% n: 21	Oct 2021 avg: 7.58% n: 21	Nov 2021 avg: -0.90% n: 21	Dec 2021 avg: 9.33% n: 22
2020	Jan 2020 avg: 1.45% n: 21	Feb 2020 avg: -6.22% n: 19	Mar 2020 avg: -15.74% n: 22	Apr 2020 avg: 9.42% n: 21	May 2020 avg: 2.15% n: 20	Jun 2020 avg: 0.46% n: 22	Jul 2020 avg: 4.17% n: 22	Aug 2020 avg: -0.03% n: 21	Sep 2020 avg: -2.70% n: 21	Oct 2020 avg: -3.18% n: 22	Nov 2020 avg: 6.88% n: 20	Dec 2020 avg: 0.16% n: 22
2019	Jan 2019 avg: 10.74% n: 21	Feb 2019 avg: 1.11% n: 19	Mar 2019 avg: 4.35% n: 21	Apr 2019 avg: -0.52% n: 21	May 2019 avg: 1.22% n: 22	Jun 2019 avg: 0.82% n: 20	Jul 2019 avg: 1.74% n: 22	Aug 2019 avg: 4.81% n: 22	Sep 2019 avg: 0.33% n: 20	Oct 2019 avg: -0.03% n: 23	Nov 2019 avg: -1.73% n: 20	Dec 2019 avg: 0.05% n: 21
2018	Jan 2018 avg: -1.91% n: 21	Feb 2018 avg: -6.81% n: 19	Mar 2018 avg: 3.22% n: 21	Apr 2018 avg: -0.61% n: 21	May 2018 avg: 2.23% n: 22	Jun 2018 avg: 3.58% n: 21	Jul 2018 avg: 1.04% n: 21	Aug 2018 avg: 2.42% n: 23	Sep 2018 avg: -3.66% n: 19	Oct 2018 avg: -1.59% n: 23	Nov 2018 avg: 5.48% n: 21	Dec 2018 avg: -8.42% n: 19
2017	Jan 2017 avg: -0.13% n: 20	Feb 2017 avg: 4.66% n: 19	Mar 2017 avg: -1.68% n: 23	Apr 2017 avg: 0.16% n: 19	May 2017 avg: 0.66% n: 22	Jun 2017 avg: 1.07% n: 22	Jul 2017 avg: 1.21% n: 20	Aug 2017 avg: 1.01% n: 23	Sep 2017 avg: -2.07% n: 20	Oct 2017 avg: 0.81% n: 22	Nov 2017 avg: 2.92% n: 21	Dec 2017 avg: -1.52% n: 20
2016	Jan 2016 avg: -6.39% n: 19	Feb 2016 avg: 0.48% n: 20	Mar 2016 avg: 9.65% n: 22	Apr 2016 avg: -2.43% n: 21	May 2016 avg: 1.72% n: 21	Jun 2016 avg: 5.23% n: 22	Jul 2016 avg: 3.24% n: 20	Aug 2016 avg: -3.74% n: 23	Sep 2016 avg: -1.83% n: 21	Oct 2016 avg: -5.55% n: 21	Nov 2016 avg: -3.04% n: 21	Dec 2016 avg: 2.47% n: 21
2015	Jan 2015 no data n: 0	Feb 2015 no data n: 0	Mar 2015 no data n: 0	Apr 2015 no data n: 0	May 2015 no data n: 0	Jun 2015 no data n: 0	Jul 2015 no data n: 0	Aug 2015 no data n: 0	Sep 2015 no data n: 0	Oct 2015 avg: 2.45% n: 16	Nov 2015 avg: -0.65% n: 20	Dec 2015 avg: 1.41% n: 22

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−5%+5%Cell label = monthly return for that year-month. Bottom row = across-years average per month.

LAYER B · SCREENER

Entering historically bullish windows.

Markets entering a historically bullish window over the next 20 trading days.

20-day forward · since 2015

Markets entering a historically bullish window over the next 20 trading days.

Nothing is entering a historically bullish window today — no unit clears the bar (forward avg ≥ 1%, up-day rate ≥ 65%, ≥ 10 sessions of history).

Loading screener…

METHODOLOGY

Daily returns are adjusted-close-based.
FF49 buckets use Fama-French 49-industry SIC ranges (Kenneth French data library).
Sectors use SPDR ETF series, not synthetic constituent baskets.
Seasonality is contextual, not predictive. We report conditions, never recommend trades.

How we compute this →