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.
| assumed_risk_free | ann_excess_return_pct | ann_volatility_pct | sharpe_ratio |
|---|---|---|---|
| 0.00% | 16.99 | 18.62 | 0.91 |
| 1.00% | 15.99 | 18.62 | 0.86 |
| 2.00% | 14.99 | 18.62 | 0.8 |
| 3.00% | 13.99 | 18.62 | 0.75 |
| 4.00% | 12.99 | 18.62 | 0.7 |
| 5.00% | 11.99 | 18.62 | 0.64 |
- Rows × columns
- 6 × 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 |
|---|---|---|---|
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.
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 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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