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The loss pile by root: contracts down 90%+ from first print, share of the pile, and each root's ten-baggers

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 2026-07-26, from The Best and Worst Thousand Dollars of June 2026.

as of table 6×6read in context →
The loss pile by root: contracts down 90%+ from first print, share of the pile, and each root's ten-baggers — 6 rows by 6 columns, computed from US exchange, SIP and OPRA data.
rootcontractsdown_90_pct_pluspct_of_root_wipedshare_of_all_down_90_pctup_10x_plus
QQQ8199292335.731.19
SPY7460231931.124.70
MU5652166029.417.72
TSLA4527136830.214.61
NVDA307867121.87.11
AAPL203544421.84.71
Rows × columns
6 × 6
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 loss pile by root: contracts down 90%+ from first print, share of the pile, and each root's ten-baggers, derived from the stored result.
ColumnTypeRangeNotes
root text 6 distinct values (AAPL, MU, NVDA…)
contracts number 2,035 to 8,199 count
down_90_pct_plus number 444 to 2,923 percent
pct_of_root_wiped number 21.8 to 35.7 percent
share_of_all_down_90_pct number 4.7 to 31.1 percent
up_10x_plus number 0 to 9

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
SELECT
    multiIf(startsWith(ticker, 'O:NVDA'), 'NVDA', startsWith(ticker, 'O:TSLA'), 'TSLA', startsWith(ticker, 'O:AAPL'), 'AAPL', startsWith(ticker, 'O:SPY'), 'SPY', startsWith(ticker, 'O:QQQ'), 'QQQ', 'MU') AS root,
    count() AS contracts,
    countIf(last_px / first_px <= 0.1) AS down_90_pct_plus,
    round(100.0 * countIf(last_px / first_px <= 0.1) / count(), 1) AS pct_of_root_wiped,
    round(100.0 * countIf(last_px / first_px <= 0.1) / sum(countIf(last_px / first_px <= 0.1)) OVER (), 1) AS share_of_all_down_90_pct,
    countIf(last_px / first_px >= 10) AS up_10x_plus
FROM (
    SELECT ticker,
        toFloat64(argMin(price, (sip_timestamp, price))) AS first_px,
        toFloat64(argMax(price, (sip_timestamp, price))) AS last_px,
        count() AS trades
    FROM global_markets.options_trades
    WHERE ((startsWith(ticker, 'O:MU') AND length(ticker) = 19) OR (startsWith(ticker, 'O:NVDA') AND length(ticker) = 21) OR (startsWith(ticker, 'O:TSLA') AND length(ticker) = 21) OR (startsWith(ticker, 'O:SPY') AND length(ticker) = 20) OR (startsWith(ticker, 'O:QQQ') AND length(ticker) = 20) OR (startsWith(ticker, 'O:AAPL') AND length(ticker) = 21))
      AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
    GROUP BY ticker
    HAVING count() >= 50 AND argMin(price, (sip_timestamp, price)) > 0
)
GROUP BY root
ORDER BY down_90_pct_plus DESC, root ASC

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More from this analysisThe Best and Worst Thousand Dollars of June 2026
Calibration: every month of 2026 computed identically, SPY and NVDA, open-to-close and range table 6×6 The five biggest first-print-to-last-print multiples of June, priced from both chairs (six liquid roots, 50+ trades) table 5×9 The ride, session by session: daily turnover, last price, and the thousand-dollar position's mark series 10×6 The most expensive ticket to zero: the priciest contract that ended at two cents or less scalar 1×5 The entry receipt: the winner's first print, its second, and every penny print of its June life (one row) scalar 1×11 The full distribution: for every jackpot, thousands of near-total losses (put/call split included) scalar 1×10 See all 2,170 queries →