S&P 500 tracker by calendar year: price return vs the points added by reinvested dividends
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 2026-08-03, from Price Return vs Total Return: The Real Gap.
| year | price_return_pct | dividend_points_pct |
|---|---|---|
| 2007 | 3.5 | 1.9 |
| 2008 | -37.6 | 1.49 |
| 2009 | 19.9 | 2.79 |
| 2010 | 11 | 2.18 |
| 2011 | -1.1 | 2.07 |
| 2012 | 11.7 | 2.48 |
| 2013 | 26.3 | 2.55 |
| 2014 | 12.3 | 2.19 |
| 2015 | -0.7 | 2.07 |
| 2016 | 11.2 | 2.39 |
| 2017 | 18.5 | 2.3 |
| 2018 | -6.9 | 1.78 |
| 2019 | 28.6 | 2.43 |
| 2020 | 15.1 | 2.19 |
| 2021 | 28.7 | 1.73 |
| 2022 | -20 | 1.3 |
| 2023 | 24.8 | 1.91 |
| 2024 | 24 | 1.59 |
| 2025 | 16.6 | 1.37 |
| 2026 | 9.3 | 0.58 |
- Rows × columns
- 20 × 3
- 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 | 2,007 to 2,026 | |
price_return_pct |
number | -37.6 to 28.7 | percent |
dividend_points_pct |
number | 0.58 to 2.79 | 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(toFloat64(close), window_start) AS close
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2006-01-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY d
),
yearly AS (
SELECT toYear(d) AS year,
argMin(close, d) AS first_px,
argMax(close, d) AS last_px
FROM daily
GROUP BY year
),
divs AS (
SELECT toYear(dv.ex_dividend_date) AS year,
exp(sum(log(1 + toFloat64(dv.cash_amount) / dl.close))) AS factor
FROM global_markets.stocks_dividends AS dv
INNER JOIN daily AS dl ON dl.d = dv.ex_dividend_date
WHERE dv.ticker = 'SPY'
AND dv.cash_amount > 0
GROUP BY year
)
SELECT y.year AS year,
round(100 * (y.last_px / y.first_px - 1), 1) AS price_return_pct,
round(100 * (y.last_px / y.first_px) * (d.factor - 1), 2) AS dividend_points_pct
FROM yearly AS y
INNER JOIN divs AS d ON y.year = d.year
ORDER BY year
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.