STRASMORE/EXPLORE 2,170 QUERIES

Same SPY 2025 returns, six assumed risk-free rates

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.

as of ranking 6×4read in context →
Same SPY 2025 returns, six assumed risk-free rates — 6 rows by 4 columns, computed from US exchange, SIP and OPRA data.
assumed_risk_freeann_excess_return_pctann_volatility_pctsharpe_ratio
0.00%16.9918.620.91
1.00%15.9918.620.86
2.00%14.9918.620.8
3.00%13.9918.620.75
4.00%12.9918.620.7
5.00%11.9918.620.64
Rows × columns
6 × 4
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 Same SPY 2025 returns, six assumed risk-free rates, derived from the stored result.
ColumnTypeRangeNotes
assumed_risk_free text 6 distinct values (0.00%, 1.00%, 2.00%…)
ann_excess_return_pct number 11.99 to 16.99 percent
ann_volatility_pct number every row is 18.62 percent
sharpe_ratio number 0.64 to 0.91 ratio or rate

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('2024-12-24 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 close_px / prev_px - 1 AS raw_ret
        FROM stepped
        WHERE prev_px > 0
          AND session_date >= toDate('2025-01-01')
    ),
    rates AS
    (
        SELECT
            arrayJoin([(0.00, '0.00%'), (0.01, '1.00%'), (0.02, '2.00%'),
                       (0.03, '3.00%'), (0.04, '4.00%'), (0.05, '5.00%')]) AS pair,
            pair.1                                                         AS rf_annual,
            pair.2                                                         AS assumed_risk_free
    )
SELECT
    assumed_risk_free,
    round(avg(raw_ret - rf_annual / 252) * 252 * 100, 2)              AS ann_excess_return_pct,
    round(stddevSamp(raw_ret - rf_annual / 252) * sqrt(252) * 100, 2) AS ann_volatility_pct,
    round(avg(raw_ret - rf_annual / 252)
          / stddevSamp(raw_ret - rf_annual / 252) * sqrt(252), 2)     AS sharpe_ratio
FROM rets
CROSS JOIN rates
GROUP BY rf_annual, assumed_risk_free
ORDER BY rf_annual

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