Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly
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 2026-08-22, from The Low-Volatility Anomaly.
| week | ko_calm | spy_market | nvda_wild |
|---|---|---|---|
| 2024-06-10 | 99.4 | 100.1 | 102 |
| 2024-06-17 | 99.7 | 100.3 | 98.2 |
| 2024-06-24 | 101.1 | 100.3 | 95.4 |
| 2024-07-01 | 101.2 | 102.3 | 97.2 |
| 2024-07-08 | 101.2 | 103.2 | 99.8 |
| 2024-07-15 | 103.7 | 101.2 | 91.2 |
| 2024-07-22 | 106.5 | 100.4 | 87.4 |
| 2024-07-29 | 110.1 | 98.3 | 82.9 |
| 2024-08-05 | 109.1 | 98.3 | 80.9 |
| 2024-08-12 | 109.9 | 102.2 | 96.3 |
| 2024-08-19 | 110.8 | 103.6 | 99.9 |
| 2024-08-26 | 115.1 | 103.9 | 92.3 |
| 2024-09-02 | 113 | 99.6 | 79.5 |
| 2024-09-09 | 113.4 | 103.6 | 92 |
| 2024-09-16 | 113.8 | 104.7 | 89.7 |
| 2024-09-23 | 114 | 105.3 | 93.8 |
| 2024-09-30 | 111.4 | 105.6 | 96.5 |
| 2024-10-07 | 110.5 | 106.8 | 104.2 |
| 2024-10-14 | 111.8 | 107.8 | 106.7 |
| 2024-10-21 | 106.3 | 106.8 | 109.4 |
| 2024-10-28 | 103.2 | 105.3 | 104.7 |
| 2024-11-04 | 101.5 | 110.3 | 114 |
| 2024-11-11 | 98 | 108 | 109.7 |
| 2024-11-18 | 101.5 | 109.8 | 109.7 |
| 2024-11-25 | 101.8 | 111.1 | 106.9 |
| 2024-12-02 | 99.3 | 112.1 | 110.1 |
| 2024-12-09 | 100.3 | 111.4 | 103.7 |
| 2024-12-16 | 99.4 | 108.9 | 104.3 |
| 2024-12-23 | 99.2 | 109.7 | 106 |
| 2024-12-30 | 98 | 109.1 | 111.8 |
| 2025-01-06 | 97 | 107 | 105 |
| 2025-01-13 | 99.6 | 110.2 | 106.5 |
| 2025-01-20 | 98.3 | 112.1 | 110.2 |
| 2025-01-27 | 100.8 | 111 | 92.8 |
| 2025-02-03 | 101.4 | 110.8 | 100.4 |
| 2025-02-10 | 109.4 | 112.4 | 107.3 |
| 2025-02-17 | 113.4 | 110.6 | 103.8 |
| 2025-02-24 | 113.1 | 109.5 | 96.7 |
| 2025-03-03 | 113.4 | 106.2 | 87.1 |
| 2025-03-10 | 109.8 | 103.8 | 93.9 |
| 2025-03-17 | 109 | 104 | 90.9 |
| 2025-03-24 | 111.8 | 102.5 | 84.7 |
| 2025-03-31 | 111.1 | 93.2 | 72.9 |
| 2025-04-07 | 113.3 | 98.4 | 85.6 |
| 2025-04-14 | 115.9 | 97 | 78.4 |
| 2025-04-21 | 114.2 | 101.5 | 85.8 |
| 2025-04-28 | 113.8 | 104.5 | 88.4 |
| 2025-05-05 | 112 | 104 | 90.1 |
| 2025-05-12 | 114.4 | 109.6 | 104.6 |
| 2025-05-19 | 114 | 106.8 | 101.5 |
| 2025-05-26 | 114.5 | 108.7 | 104.2 |
| 2025-06-02 | 113.3 | 110.4 | 109.5 |
| 2025-06-09 | 112.8 | 110.1 | 109.7 |
| 2025-06-16 | 109.3 | 109.6 | 111.1 |
| 2025-06-23 | 111.7 | 113.4 | 121.9 |
| 2025-06-30 | 113.3 | 115.3 | 123.1 |
| 2025-07-07 | 111 | 115 | 127.4 |
| 2025-07-14 | 110.9 | 115.7 | 133.2 |
| 2025-07-21 | 109.8 | 117.4 | 134.1 |
| 2025-07-28 | 109.3 | 114.6 | 134.2 |
| 2025-08-04 | 111.7 | 117.5 | 141.3 |
| 2025-08-11 | 111.1 | 118.6 | 139.5 |
| 2025-08-18 | 111.4 | 119 | 137.6 |
| 2025-08-25 | 109.6 | 118.9 | 134.7 |
| 2025-09-01 | 107.9 | 119.3 | 129.1 |
| 2025-09-08 | 106.4 | 121.2 | 137.4 |
| 2025-09-15 | 105.5 | 122.4 | 136.4 |
| 2025-09-22 | 104.2 | 122 | 137.7 |
| 2025-09-29 | 105.8 | 123.4 | 145 |
| 2025-10-06 | 106.5 | 120.4 | 141.5 |
| 2025-10-13 | 108.7 | 122.5 | 141.6 |
| 2025-10-20 | 110.7 | 124.8 | 144 |
| 2025-10-27 | 109.4 | 125.7 | 156.5 |
| 2025-11-03 | 112 | 123.7 | 145.5 |
| 2025-11-10 | 113 | 123.9 | 147.1 |
| 2025-11-17 | 115.9 | 121.5 | 138.3 |
| 2025-11-24 | 116.1 | 126 | 136.8 |
| 2025-12-01 | 111.1 | 126.4 | 141 |
| 2025-12-08 | 112 | 125.7 | 135.3 |
| 2025-12-15 | 111.3 | 125.5 | 139.9 |
| 2025-12-22 | 111 | 127.3 | 147.3 |
| 2025-12-29 | 109.8 | 126 | 145.9 |
| 2026-01-05 | 112 | 127.9 | 142.9 |
| 2026-01-12 | 111.8 | 127.5 | 143.9 |
| 2026-01-19 | 115.7 | 127.1 | 145.1 |
| 2026-01-26 | 118.9 | 127.6 | 147.9 |
| 2026-02-02 | 125.5 | 127.3 | 143.3 |
| 2026-02-09 | 124.9 | 125.7 | 141.3 |
| 2026-02-16 | 126.8 | 127.1 | 146.7 |
| 2026-02-23 | 129.5 | 126.5 | 136.9 |
| 2026-03-02 | 122.4 | 124 | 137.4 |
| 2026-03-09 | 122.8 | 122.1 | 139.3 |
| 2026-03-16 | 118.7 | 119.6 | 133.7 |
| 2026-03-23 | 120.2 | 116.9 | 129.4 |
| 2026-03-30 | 121.8 | 120.9 | 137.1 |
| 2026-04-06 | 123 | 125.2 | 145.8 |
| 2026-04-13 | 120.3 | 130.9 | 155.9 |
| 2026-04-20 | 121.7 | 131.6 | 160.9 |
| 2026-04-27 | 124.8 | 132.9 | 153.4 |
| 2026-05-04 | 124.5 | 136 | 166.3 |
| 2026-05-11 | 128.4 | 136.3 | 174.2 |
| 2026-05-18 | 129.4 | 137.5 | 166.4 |
| 2026-05-25 | 125.5 | 139.5 | 163.2 |
| 2026-06-01 | 126.3 | 136 | 158.5 |
| 2026-06-08 | 131.2 | 136.7 | 158.6 |
| 2026-06-15 | 126.1 | 137.6 | 162.5 |
| 2026-06-22 | 131.2 | 134.4 | 148.2 |
| 2026-06-29 | 133.4 | 137.3 | 150.4 |
| 2026-07-06 | 132.6 | 139.2 | 163.1 |
| 2026-07-13 | 129.5 | 137 | 156.6 |
| 2026-07-20 | 130.6 | 136.2 | 160 |
| 2026-07-27 | 139.1 | 137.7 | 155.2 |
| 2026-08-03 | 138.2 | 142.6 | 173.1 |
| 2026-08-10 | 139.3 | 143.1 | 174 |
| 2026-08-17 | 144.6 | 141.4 | 166.5 |
- Rows × columns
- 115 × 4
- Period covered
- to
- 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 |
|---|---|---|---|
week |
date | 2024-06-10 to 2026-08-17 | |
ko_calm |
number | 97 to 144.6 | |
spy_market |
number | 93.2 to 143.1 | |
nvda_wild |
number | 72.9 to 174.2 |
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 d AS (
SELECT ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
argMax(toFloat64(close), toTimeZone(window_start, 'America/New_York')) AS c
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('KO','SPY','NVDA')
AND window_start >= now() - INTERVAL 800 DAY
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY ticker, dt
),
r AS (
SELECT ticker, dt,
c / lagInFrame(c) OVER (PARTITION BY ticker ORDER BY dt) - 1 AS ret
FROM d
),
f AS (
SELECT ticker, dt, ret FROM r WHERE ret IS NOT NULL AND ret > -0.5 AND ret < 0.5
),
cum AS (
SELECT ticker, dt,
100 * exp(sum(log(1 + ret)) OVER (PARTITION BY ticker ORDER BY dt)) AS idx
FROM f
),
wk AS (
SELECT ticker, toMonday(dt) AS week, argMax(idx, dt) AS wv
FROM cum GROUP BY ticker, week
)
SELECT week,
round(maxIf(wv, ticker = 'KO'), 1) AS ko_calm,
round(maxIf(wv, ticker = 'SPY'), 1) AS spy_market,
round(maxIf(wv, ticker = 'NVDA'), 1) AS nvda_wild
FROM wk
GROUP BY week
ORDER BY week
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