The window decides the answer: SPY calendar-year price return and intra-year high-to-low range, 2016-2025
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-07-31, from Multi-Agent AI Trading Systems: What Is Real.
| year | sessions | price_return_pct | high_low_range_pct |
|---|---|---|---|
| 2016 | 252 | 11.2 | 24.4 |
| 2017 | 251 | 18.5 | 19.1 |
| 2018 | 251 | -6.9 | 25.3 |
| 2019 | 252 | 28.6 | 32.3 |
| 2020 | 253 | 15.1 | 68 |
| 2021 | 252 | 28.7 | 29.4 |
| 2022 | 251 | -20 | 34 |
| 2023 | 250 | 24.8 | 25.6 |
| 2024 | 252 | 24 | 30.1 |
| 2025 | 250 | 16.6 | 39 |
- Rows × columns
- 10 × 4
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
year |
number | 2,016 to 2,025 | |
sessions |
number | 250 to 253 | |
price_return_pct |
number | -20 to 28.7 | percent |
high_low_range_pct |
number | 19.1 to 68 | percent |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
WITH daily AS (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
argMax(close, window_start) AS close_px
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2016-01-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2025-12-31')
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY d
),
yr AS (
SELECT toYear(d) AS year,
argMin(close_px, d) AS first_close,
argMax(close_px, d) AS last_close,
max(close_px) AS high_close,
min(close_px) AS low_close,
count() AS sessions
FROM daily
GROUP BY year
)
SELECT year,
sessions,
round(100 * (toFloat64(last_close) / toFloat64(first_close) - 1), 1) AS price_return_pct,
round(100 * (toFloat64(high_close) / toFloat64(low_close) - 1), 1) AS high_low_range_pct
FROM yr
ORDER BY year
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