ah_extreme_survival
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 2026-10-03, from most-active-stocks-after-hours.
| ticker | evenings | pct_high_above_next_session | pct_low_below_next_session |
|---|---|---|---|
| GOOGL | 138 | 31.9 | 25.4 |
| MSFT | 138 | 30.4 | 31.2 |
| INTC | 138 | 27.5 | 31.2 |
| AMZN | 138 | 26.8 | 31.2 |
| SPY | 138 | 26.1 | 36.2 |
| QQQ | 138 | 26.1 | 38.4 |
| F | 138 | 25.4 | 21.7 |
| META | 138 | 22.5 | 29.7 |
| KO | 138 | 22.5 | 26.1 |
| AMD | 138 | 21.7 | 36.2 |
| TSLA | 138 | 21 | 26.8 |
| NVDA | 138 | 20.3 | 35.5 |
| AAPL | 138 | 16.7 | 30.4 |
- Rows × columns
- 13 × 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 |
|---|---|---|---|
ticker |
text | 13 distinct values (AAPL, AMD, AMZN…) | |
evenings |
number | every row is 138 | |
pct_high_above_next_session |
number | 16.7 to 31.9 | percent |
pct_low_below_next_session |
number | 21.7 to 38.4 | percent |
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.
SELECT
ticker,
count() AS evenings,
round(100 * countIf(ah_high > next_high) / count(), 1) AS pct_high_above_next_session,
round(100 * countIf(ah_low < next_low) / count(), 1) AS pct_low_below_next_session
FROM
(
SELECT
e.ticker AS ticker,
e.session AS session,
e.ah_high AS ah_high,
e.ah_low AS ah_low,
argMin(n.reg_high, n.session) AS next_high,
argMin(n.reg_low, n.session) AS next_low
FROM
(
SELECT
ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS session,
max(high) AS ah_high,
min(low) AS ah_low
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('AAPL','MSFT','NVDA','AMZN','TSLA','META','GOOGL','AMD','INTC','F','KO','SPY','QQQ')
AND window_start >= today() - 200
AND window_start < today() - 1
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) >= 960
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) < 1200
GROUP BY ticker, session
HAVING sum(volume) >= 10000
) AS e
INNER JOIN
(
SELECT
ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS session,
max(high) AS reg_high,
min(low) AS reg_low
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('AAPL','MSFT','NVDA','AMZN','TSLA','META','GOOGL','AMD','INTC','F','KO','SPY','QQQ')
AND window_start >= today() - 200
AND window_start < today()
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 ticker, session
) AS n ON n.ticker = e.ticker
WHERE n.session > e.session
AND n.session <= e.session + 5
GROUP BY e.ticker, e.session, e.ah_high, e.ah_low
)
GROUP BY ticker
ORDER BY pct_high_above_next_session DESC
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.