STRASMORE/EXPLORE 3,293 QUERIES

The 2020 peak, low, death cross and golden cross, dated from the same bars

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 2026-11-01, from Can a Death Cross Be Bullish? The SPY Record.

as of scalar 1×16read in context →
peak day
Feb 19, 2020
peak close
338.34
low day
Mar 23, 2020
low close
222.95
cross day
Mar 30, 2020
cross close
261.65
golden day
Jul 9, 2020
golden close
314.38
peak to low drop pct
34.1
sessions peak to low
23
sessions low to cross
5
low to cross gain pct
17.4
cross off peak pct
22.7
sessions cross to golden
70
cross to golden gain pct
20.2
fwd 12m pct
50.9
Rows × columns
1 × 16
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for The 2020 peak, low, death cross and golden cross, dated from the same bars, derived from the stored result.
ColumnTypeRangeNotes
peak_day text 1 distinct value (Feb 19, 2020)
peak_close number every row is 338.34 US dollars
low_day text 1 distinct value (Mar 23, 2020)
low_close number every row is 222.95 US dollars
cross_day text 1 distinct value (Mar 30, 2020)
cross_close number every row is 261.65 US dollars
golden_day text 1 distinct value (Jul 9, 2020)
golden_close number every row is 314.38 US dollars
peak_to_low_drop_pct number every row is 34.1 percent
sessions_peak_to_low number every row is 23 US dollars
sessions_low_to_cross number every row is 5 US dollars
low_to_cross_gain_pct number every row is 17.4 percent
cross_off_peak_pct number every row is 22.7 percent
sessions_cross_to_golden number every row is 70
cross_to_golden_gain_pct number every row is 20.2 percent
fwd_12m_pct number every row is 50.9 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.

WITH
bars AS
(
    SELECT
        date,
        toFloat64(argMax(close, _ingest_time)) AS px
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'SPY'
    GROUP BY date
),
smas AS
(
    SELECT
        date,
        px,
        row_number() OVER (ORDER BY date) AS rn,
        avg(px) OVER (ORDER BY date ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS avg_50,
        avg(px) OVER (ORDER BY date ROWS BETWEEN 199 PRECEDING AND CURRENT ROW) AS avg_200,
        max(px) OVER (ORDER BY date ROWS BETWEEN 251 PRECEDING AND CURRENT ROW) AS high_1y,
        leadInFrame(px, 21) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS px_1m,
        leadInFrame(px, 63) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS px_3m,
        leadInFrame(px, 126) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS px_6m,
        leadInFrame(px, 252) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS px_12m
    FROM bars
),
states AS
(
    SELECT
        *,
        (avg_50 < avg_200) AS below,
        lagInFrame((avg_50 < avg_200), 1) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS prev_below
    FROM smas
),
flags AS
(
    SELECT
        *,
        (rn >= 201 AND below = 1 AND prev_below = 0) AS is_death,
        (rn >= 201 AND below = 0 AND prev_below = 1) AS is_golden
    FROM states
),
cross_row AS
(
    SELECT date AS cross_date, px AS cross_px, rn AS cross_rn, px_12m AS cross_px_12m
    FROM flags
    WHERE is_death
      AND date BETWEEN toDate('2020-02-01') AND toDate('2020-05-31')
    ORDER BY date
    LIMIT 1
),
golden_row AS
(
    SELECT date AS golden_date, px AS golden_px, rn AS golden_rn
    FROM flags
    WHERE is_golden
      AND date BETWEEN toDate('2020-04-01') AND toDate('2020-12-31')
    ORDER BY date
    LIMIT 1
),
peak_row AS
(
    SELECT date AS peak_date, px AS peak_px, rn AS peak_rn
    FROM flags
    WHERE date BETWEEN toDate('2020-01-01') AND toDate('2020-03-31')
    ORDER BY px DESC
    LIMIT 1
),
low_row AS
(
    SELECT date AS low_date, px AS low_px, rn AS low_rn
    FROM flags
    WHERE date BETWEEN toDate('2020-02-01') AND toDate('2020-06-30')
    ORDER BY px ASC
    LIMIT 1
)
SELECT
    concat(formatDateTime(peak_date, '%b'), ' ', toString(toDayOfMonth(peak_date)), ', ', toString(toYear(peak_date)))       AS peak_day,
    round(peak_px, 2)                                  AS peak_close,
    concat(formatDateTime(low_date, '%b'), ' ', toString(toDayOfMonth(low_date)), ', ', toString(toYear(low_date)))           AS low_day,
    round(low_px, 2)                                   AS low_close,
    concat(formatDateTime(cross_date, '%b'), ' ', toString(toDayOfMonth(cross_date)), ', ', toString(toYear(cross_date)))     AS cross_day,
    round(cross_px, 2)                                 AS cross_close,
    concat(formatDateTime(golden_date, '%b'), ' ', toString(toDayOfMonth(golden_date)), ', ', toString(toYear(golden_date))) AS golden_day,
    round(golden_px, 2)                                AS golden_close,
    round((1 - low_px / peak_px) * 100, 1)             AS peak_to_low_drop_pct,
    toInt64(low_rn) - toInt64(peak_rn)                 AS sessions_peak_to_low,
    toInt64(cross_rn) - toInt64(low_rn)                AS sessions_low_to_cross,
    round((cross_px / low_px - 1) * 100, 1)            AS low_to_cross_gain_pct,
    round((1 - cross_px / peak_px) * 100, 1)           AS cross_off_peak_pct,
    toInt64(golden_rn) - toInt64(cross_rn)             AS sessions_cross_to_golden,
    round((golden_px / cross_px - 1) * 100, 1)         AS cross_to_golden_gain_pct,
    round((cross_px_12m / cross_px - 1) * 100, 1)      AS fwd_12m_pct
FROM cross_row, peak_row, low_row, golden_row
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