Kelly inputs from daily closes, 2016 through 2025: win rate, average gain, average loss, and the fraction the formula returns
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 Kelly Criterion Position Sizing, Measured.
| ticker | win_rate_pct | avg_gain_pct | avg_loss_pct | full_kelly_x |
|---|---|---|---|---|
| SPY | 55.3 | 0.71 | 0.76 | 10.1 |
| MSFT | 54.1 | 1.17 | 1.16 | 7.4 |
| JNJ | 51.8 | 0.79 | 0.77 | 5.8 |
| KO | 53 | 0.76 | 0.8 | 4.4 |
| NVDA | 54.6 | 2.28 | 2.3 | 3.8 |
| TSLA | 52 | 2.71 | 2.64 | 2 |
- Rows × columns
- 6 × 5
- 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 |
|---|---|---|---|
ticker |
text | 6 distinct values (JNJ, KO, MSFT…) | |
win_rate_pct |
number | 51.8 to 55.3 | percent |
avg_gain_pct |
number | 0.71 to 2.71 | percent |
avg_loss_pct |
number | 0.76 to 2.64 | percent |
full_kelly_x |
number | 2 to 10.1 |
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 ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
argMax(toFloat64(close), window_start) AS c
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'KO', 'JNJ', 'MSFT', 'NVDA', 'TSLA')
AND window_start >= '2016-01-01 00:00:00'
AND window_start < '2026-01-01 00:00:00'
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY ticker, dt
),
steps AS (
SELECT ticker, dt, c,
lagInFrame(c) OVER (PARTITION BY ticker ORDER BY dt
ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev
FROM daily
),
rets AS (
SELECT ticker, c / prev - 1 AS ret
FROM steps
WHERE prev > 0 AND c != prev
)
SELECT ticker,
round(100 * countIf(ret > 0) / count(), 1) AS win_rate_pct,
round(100 * avgIf(ret, ret > 0), 2) AS avg_gain_pct,
round(100 * abs(avgIf(ret, ret < 0)), 2) AS avg_loss_pct,
round(countIf(ret > 0) / count() / abs(avgIf(ret, ret < 0))
- countIf(ret < 0) / count() / avgIf(ret, ret > 0), 1) AS full_kelly_x
FROM rets
GROUP BY ticker
HAVING countIf(ret > 0) > 0 AND countIf(ret < 0) > 0
ORDER BY full_kelly_x DESC
Run your own version of this
The same 22 years of US equities and 12 years of options data are queryable in SQL or plain English. A free account runs 100 queries a day and takes no card.
More from this analysisKelly Criterion Position Sizing, Measured
The same Kelly calculation on the S&P 500 tracker, year by year, 2016 through 2025
table 10×5
→
One decade of S&P 500 daily returns compounded at eight fixed bet sizes: ending wealth and worst drawdown
ranking 8×3
→
S&P 500 tracker (SPY): down sessions by calendar year, 2016 to mid-2026
table 11×5
→
One-day move profile, seven household names, July 2025 to June 2026
table 7×6
→
SPY realised volatility by month against a 10% target
series 72×4
→
Weekly realised volatility and the weight it implied, Nov 2019 to Apr 2020
series 25×4
→
See all 2,170 queries →