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SPY annualized Sharpe ratio, year by year, fixed 4.25% assumed rate

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 2026-08-06, from What Is the Sharpe Ratio? Formula and Math.

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SPY annualized Sharpe ratio, year by year, fixed 4.25% assumed rate — 10 rows by 3 columns, computed from US exchange, SIP and OPRA data.
yearsharpe_ratioann_volatility_pct
20160.4413.08
20172.076.64
2018-0.5417.09
20191.7412.47
20200.4834.23
20211.5813.01
2022-0.9524.16
20231.4113.14
20241.3912.57
20250.6818.62
Rows × columns
10 × 3
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for SPY annualized Sharpe ratio, year by year, fixed 4.25% assumed rate, derived from the stored result.
ColumnTypeRangeNotes
year text 10 distinct values (2016, 2017, 2018…)
sharpe_ratio number -0.95 to 2.07 ratio or rate
ann_volatility_pct number 6.64 to 34.23 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.

the exact SQL behind every number
WITH
    daily AS
    (
        SELECT
            toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
            argMax(toFloat64(close), window_start)               AS close_px
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= toDateTime('2015-12-24 00:00:00')
          AND window_start <  toDateTime('2026-01-01 05:00:00')
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
             + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
             + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
        GROUP BY session_date
    ),
    stepped AS
    (
        SELECT
            session_date,
            close_px,
            lagInFrame(close_px, 1) OVER (ORDER BY session_date
                                          ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_px
        FROM daily
    ),
    rets AS
    (
        SELECT
            session_date,
            close_px / prev_px - 1                AS raw_ret,
            close_px / prev_px - 1 - 0.0425 / 252 AS ex_ret
        FROM stepped
        WHERE prev_px > 0
          AND session_date >= toDate('2016-01-01')
    )
SELECT
    toString(toYear(session_date))                         AS year,
    round(avg(ex_ret) / stddevSamp(ex_ret) * sqrt(252), 2) AS sharpe_ratio,
    round(stddevSamp(raw_ret) * sqrt(252) * 100, 2)        AS ann_volatility_pct
FROM rets
GROUP BY year
ORDER BY year

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