STRASMORE/EXPLORE 3,256 QUERIES 22Y EQUITIES · 12Y OPTIONS

3,256 answered market questions

every one with its exact SQL, its result and the date it was computed · free, no signup

The Low-Volatility Anomaly
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weeklyseries · 2026-10-04 · 114×4Preview: a 16-point series, ending higher. Annualized volatility vs total return, 25 large caps, calmest to wildest (~2 years)ranking · 2026-10-04 · 25×3Preview: 16 ranked values, smallest first. Volatility thirds: median return, and the range from worst to best name in eachtable · 2026-10-04 · 3×6
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly

Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly

most recentas of series 114×4read in context →
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly — 114 rows by 4 columns, computed from US exchange, SIP and OPRA data.
weekko_calmspy_marketnvda_wild
2024-07-29103.497.994.9
2024-08-05102.497.992.6
2024-08-12103.2101.8110.2
2024-08-19104.1103.3114.3
2024-08-26108.1103.5105.6
2024-09-02106.199.390.9
2024-09-09106.5103.2105.3
2024-09-16106.8104.4102.7
2024-09-23107.1105107.4
2024-09-30104.6105.2110.5
2024-10-07103.7106.5119.2
2024-10-14105107.4122
2024-10-2199.8106.4125.1
2024-10-2896.9104.9119.8
2024-11-0495.4109.9130.5
2024-11-1192.1107.6125.6
2024-11-1895.3109.4125.5
2024-11-2595.6110.7122.3
2024-12-0293.2111.7126
2024-12-0994.2111118.7
2024-12-1693.4108.5119.4
2024-12-2393.2109.3121.3
2024-12-3092.1108.7127.9
2025-01-0691.1106.6120.2
2025-01-1393.5109.8121.8
2025-01-2092.3111.7126.1
2025-01-2794.6110.5106.1
2025-02-0395.2110.4114.9
2025-02-10102.7112122.8
2025-02-17106.5110.2118.8
2025-02-24106.2109.1110.6
2025-03-03106.5105.899.7
2025-03-10103.1103.4107.4
2025-03-17102.4103.6104
2025-03-24105102.197
2025-03-31104.392.983.4
2025-04-07106.498.197.9
2025-04-14108.896.789.7
2025-04-21107.3101.198.1
2025-04-28106.9104.1101.2
2025-05-05105.2103.7103.1
2025-05-12107.4109.2119.7
2025-05-19107.1106.4116.1
2025-05-26107.5108.3119.3
2025-06-02106.4110125.3
2025-06-09105.9109.7125.6
2025-06-16102.7109.2127.2
2025-06-23104.9112.9139.5
2025-06-30106.4114.9140.9
2025-07-07104.2114.6145.8
2025-07-14104.2115.3152.5
2025-07-21103.2117153.4
2025-07-28102.7114.2153.5
2025-08-04104.9117161.6
2025-08-11104.3118.2159.6
2025-08-18104.6118.5157.5
2025-08-25102.9118.5154.1
2025-09-01101.4118.9147.7
2025-09-0899.9120.8157.3
2025-09-1599.1121.9156.1
2025-09-2297.9121.6157.6
2025-09-2999.4122.9165.9
2025-10-06100120162
2025-10-13102.1122162.1
2025-10-20104124.4164.8
2025-10-27102.8125.3179
2025-11-03105.2123.2166.5
2025-11-10106.1123.4168.3
2025-11-17108.8121.1158.3
2025-11-24109.1125.5156.5
2025-12-01104.4126161.3
2025-12-08105.2125.2154.8
2025-12-15104.5125160.1
2025-12-22104.2126.8168.5
2025-12-29103.1125.5167
2026-01-05105.2127.5163.5
2026-01-12105127164.7
2026-01-19108.7126.6166
2026-01-26111.6127.1169.2
2026-02-02117.9126.9164
2026-02-09117.3125.2161.7
2026-02-16119.1126.6167.9
2026-02-23121.6126.1156.7
2026-03-02114.9123.5157.2
2026-03-09115.3121.7159.4
2026-03-16111.5119.1153
2026-03-23112.8116.5148.1
2026-03-30114.4120.5156.9
2026-04-06115.5124.8166.8
2026-04-13113130.4178.4
2026-04-20114.3131.2184.1
2026-04-27117.2132.4175.5
2026-05-04117135.5190.3
2026-05-11120.5135.8199.3
2026-05-18121.5137190.4
2026-05-25117.8138.9186.8
2026-06-01118.6135.5181.4
2026-06-08123.2136.2181.4
2026-06-15118.4137.1185.9
2026-06-22123.2133.9169.6
2026-06-29125.2136.8172
2026-07-06124.5138.7186.6
2026-07-13121.6136.5179.2
2026-07-20122.7135.7183.1
2026-07-27130.6137.2177.6
2026-08-03129.8142198
2026-08-10130.8142.6199.1
2026-08-17135.9140.7190
2026-08-24133.7141.3192.4
2026-08-31131.3141.5203.7
2026-09-07131.6140.4193
2026-09-14131.4139.9196.4
2026-09-21131141.7199.1
2026-09-28127.9141.4207.2
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
$