By Market Recap: July 1, 2026, The Day in Numbers
The second half opened quiet at the index and violent underneath: the memory complex broke, META jumped, and most S&P sectors still closed green.
Wednesday, July 1, 2026, the second half's first session, put one of the month's quietest index days on top of its most violent tape. SPY closed -0.08% and QQQ -1.44%, yet the memory complex that carried the second quarter lost a tenth of its value, META jumped 8.88%, and 7 of 11 S&P sector funds still closed green. Prior session: June 30.
The scoreboard
Changes compare July 1's last regular-session bar with Tuesday June 30's.
The exact SQL behind every number
WITH prior AS (
SELECT ticker, argMax(close, window_start) AS prior_close
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
AND window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00'
GROUP BY ticker
),
sess AS (
SELECT ticker,
argMin(open, window_start) AS day_open,
argMax(close, window_start) AS day_close,
max(high) AS day_high,
min(low) AS day_low,
round(toFloat64(sum(volume)) / 1e6, 1) AS shares_traded_m
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
AND window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'
GROUP BY ticker
)
SELECT
s.ticker AS ticker,
round(toFloat64(p.prior_close), 2) AS prior_close,
round(toFloat64(s.day_open), 2) AS day_open,
round(toFloat64(s.day_close), 2) AS day_close,
round((toFloat64(s.day_close) / toFloat64(p.prior_close) - 1) * 100, 2) AS pct_change,
round(toFloat64(s.day_high), 2) AS day_high,
round(toFloat64(s.day_low), 2) AS day_low,
s.shares_traded_m AS shares_traded_m
FROM sess s
JOIN prior p ON s.ticker = p.ticker
ORDER BY s.tickerThe split is the story: DIA at 0.02% and SPY at -0.08% held flat against QQQ's -1.44% and IWM's -0.37%, a growth selloff the broad market barely registered.
One of the quietest index days of the trailing month
The exact SQL behind every number
SELECT round(anyIf(oc_pct, d = toDate('2026-07-01')), 2) AS day_move_pct,
arrayCount(x -> x > abs(anyIf(oc_pct, d = toDate('2026-07-01'))), groupArrayIf(abs(oc_pct), d != toDate('2026-07-01'))) + 1 AS abs_move_rank,
count() AS sessions_compared,
toString(min(d)) AS first_session
FROM (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
(argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS oc_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime('2026-06-01 00:00:00')
AND window_start < toDateTime('2026-07-02 00:00:00')
AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
GROUP BY d
)Open-to-close inside the session, a different lens from the close-over-close scoreboard, SPY moved 0.09%: rank 20 of 22 trailing sessions by absolute size, only two moving less. The volatility complex agreed. This warehouse carries no spot VIX index, so the check runs on listed VIX-futures funds, the closest tradeable read on the price of protection:
The exact SQL behind every number
WITH per_name AS (
SELECT
ticker,
toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'SVXY', 'UVXY', 'VIXY', 'VXX')
AND ((window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'))
GROUP BY ticker
)
SELECT
ticker,
round(prior_close, 2) AS prior_close,
round(day_close, 2) AS day_close,
round((day_close / prior_close - 1) * 100, 2) AS pct_chg,
round((day_high / day_low - 1) * 100, 2) AS range_pct
FROM per_name
ORDER BY tickerVXX, the largest front-month VIX futures fund, rose 0.72%; VIXY 0.8%; the leveraged UVXY 1.13% across a 3.68% range; the inverse SVXY -0.42%. Rounding errors beside what single stocks did.
Breadth: more fell than rose, and more made new highs than new lows
The exact SQL behind every number
WITH per_ticker AS (
SELECT
ticker,
toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
maxIf(toFloat64(high), window_start < '2026-07-01 00:00:00') AS quarter_high,
minIf(toFloat64(low), window_start < '2026-07-01 00:00:00') AS quarter_low,
maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low,
sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 00:00:00') AS day_dollar_volume,
countIf(window_start < '2026-07-01 00:00:00') AS quarter_bars
FROM global_markets.delayed_stocks_minute_aggs
WHERE ((window_start >= '2026-04-01 13:30:00' AND window_start < '2026-06-30 20:00:00')
OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'))
AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
GROUP BY ticker
)
SELECT
countIf(day_close > prior_close AND day_dollar_volume >= 1000000) AS advancers,
countIf(day_close < prior_close AND day_dollar_volume >= 1000000) AS decliners,
countIf(day_close = prior_close AND day_dollar_volume >= 1000000) AS unchanged,
round(100.0 * countIf(day_close > prior_close AND day_dollar_volume >= 1000000)
/ countIf(day_dollar_volume >= 1000000), 1) AS advancer_pct,
countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_high > quarter_high) AS new_quarter_highs,
countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_low < quarter_low) AS new_quarter_lows,
round(countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_high > quarter_high)
/ countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_low < quarter_low), 1) AS highs_per_low,
countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000) AS names_with_a_full_quarter,
countIf(day_dollar_volume >= 1000000) AS liquid_tickers,
count() AS tickers_traded_both_sessions,
count() - countIf(day_dollar_volume >= 1000000) AS dropped_by_liquidity_filter,
countIf(day_dollar_volume >= 1000000 AND quarter_bars < 1000) AS dropped_short_quarter_history
FROM per_ticker
WHERE prior_close > 0 AND day_close > 02928 advancers, 3465 decliners, 82 unchanged, 45.2% of the liquid tape rose. But scope is not severity: against the second quarter's regular-hours range, 836 of the 6217 names with a complete quarter of trading printed a new quarterly high on this red day, against 246 printing a new low, 3.4 new highs per new low. Most slipped; few broke their range. Drops: 5435 of 11910 dual-session tickers under the $1 million filter, 258 liquid names without a full quarter of bars.
The sector board: the damage was one sector deep
The eleven SPDR sector funds are the cheapest whole-market cross-section, the same basket every session.
The exact SQL behind every number
WITH per_name AS (
SELECT
ticker,
toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 00:00:00') / 1e9, 2) AS day_dollar_bn
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('XLB', 'XLC', 'XLE', 'XLF', 'XLI', 'XLK', 'XLP', 'XLRE', 'XLU', 'XLV', 'XLY')
AND ((window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'))
GROUP BY ticker
)
SELECT
ticker,
round(prior_close, 2) AS prior_close,
round(day_close, 2) AS day_close,
round((day_close / prior_close - 1) * 100, 2) AS pct_chg,
round((day_close / prior_close - 1) * 100 - min((day_close / prior_close - 1) * 100) OVER (), 2) AS pct_above_worst_sector,
sum(if(day_close > prior_close, 1, 0)) OVER (ORDER BY (day_close / prior_close) DESC ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS green_so_far,
day_dollar_bn
FROM per_name
ORDER BY pct_chg DESCCommunication services (XLC), the sector fund that holds META, led at 2.41%, financials (XLF) behind at 2.2%. Technology (XLK) sat alone at the bottom, -2.56% and 4.97 percentage points below the leader. In all, 7 of 11 funds closed green, discretionary 0.68%, health care 0.57%, against utilities (-1.28%), industrials (-0.98%) and energy (-0.6%) in red. That is "the index barely moved" from underneath.
The day's highlight: memory broke, META went the other way
Eight names carried the dispersion: the four memory-and-storage stocks that led the second quarter, and four chip and platform names around them. Co-movement, magnitude and timing are reported; the data does not say why.
The exact SQL behind every number
WITH per_name AS (
SELECT
ticker,
toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low,
argMinIf(window_start, (toFloat64(low), toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-01 00:00:00') AS low_bar,
argMaxIf(window_start, (toFloat64(high), -toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-01 00:00:00') AS high_bar,
round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 00:00:00') / 1e9, 2) AS day_dollar_bn
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('AMD', 'META', 'MRVL', 'MU', 'NVDA', 'SNDK', 'STX', 'WDC')
AND ((window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'))
GROUP BY ticker
)
SELECT
ticker,
round(prior_close, 2) AS prior_close,
round(day_close, 2) AS day_close,
round((day_close / prior_close - 1) * 100, 2) AS pct_chg,
formatDateTime(toTimeZone(high_bar, 'America/New_York'), '%H:%i') AS day_high_et,
formatDateTime(toTimeZone(low_bar, 'America/New_York'), '%H:%i') AS day_low_et,
toHour(toTimeZone(low_bar, 'America/New_York')) * 60 + toMinute(toTimeZone(low_bar, 'America/New_York')) AS low_minute_et,
round((day_high / day_low - 1) * 100, 2) AS range_pct,
day_dollar_bn
FROM per_name
ORDER BY tickerSanDisk (-10.45%) and Micron (-10.23%) each shed more than a tenth of their value; Marvell -8.68%, AMD -6.87%, Western Digital -6.3%, Seagate -5.11%. MU turned over $42.94 billion, more than SPY traded all day, and MU, AMD and Marvell each printed session lows in the closing minutes (15:59, 15:57, 15:58 ET), sold into the closing auction, not a morning air pocket that healed (the MU deep-dive has the quarter behind it).
META is the mirror image: 8.88% on $22.72 billion traded, its low at 09:30 ET, the opening bar, and never revisited. NVDA went nowhere at -1.09% (NVDA's June).
What was said
This page never assigns causes. But our licensed news feed is a table like any other, what it carried that day:
The exact SQL behind every number
SELECT published_et, publisher, names_tagged, headline
FROM (
SELECT
published_utc,
formatDateTime(toTimeZone(published_utc, 'America/New_York'), '%H:%i') AS published_et,
JSONExtractString(publisher, 'name') AS publisher,
arrayStringConcat(arrayFilter(x -> x IN ('MU', 'SNDK', 'STX', 'WDC', 'META'), tickers), ' ') AS names_tagged,
substring(title, 1, 72) AS headline
FROM global_markets.stocks_news
WHERE published_utc >= '2026-07-01 04:00:00' AND published_utc < '2026-07-02 04:00:00'
AND hasAny(tickers, ['MU', 'SNDK', 'STX', 'WDC', 'META'])
AND NOT has(tickers, 'SPCX')
AND position(title, 'SPCX') = 0
ORDER BY published_utc DESC
LIMIT 12
)
ORDER BY published_utc ASCThe Motley Fool's mid-afternoon piece on Micron (14:11 ET) ran under the headline "Why Micron Stock Is Plummeting Today". Its evening wrap (17:12 ET) and the follow-up four minutes later (17:16 ET) both put META's jump beside a reported plan to sell excess AI compute as a cloud business. That is the outlet's framing, not a finding in the tape, and 12 articles from two publishers is one feed's attention, not the market's.
Where the money traded
The exact SQL behind every number
SELECT ticker, leaderboard, dollar_volume_bn, if(dollar_volume_bn < 1, dollar_volume_m, NULL) AS dollar_value_m, shares_m,
round(100 * if(leaderboard = 'by dollars traded', dollar_volume_bn, shares_m)
/ max(if(leaderboard = 'by dollars traded', dollar_volume_bn, shares_m)) OVER (PARTITION BY leaderboard), 1) AS pct_of_board_leader
FROM (
SELECT
'by dollars traded' AS leaderboard,
ticker,
round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 2) AS dollar_volume_bn,
round(sum(toFloat64(close) * toFloat64(volume)) / 1e6, 0) AS dollar_volume_m,
round(sum(toFloat64(volume)) / 1e6, 1) AS shares_m
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'
AND ticker NOT IN ('SPCX')
GROUP BY ticker
ORDER BY dollar_volume_bn DESC
LIMIT 6
UNION ALL
SELECT
'by shares traded' AS leaderboard,
ticker,
round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 2) AS dollar_volume_bn,
round(sum(toFloat64(close) * toFloat64(volume)) / 1e6, 0) AS dollar_volume_m,
round(sum(toFloat64(volume)) / 1e6, 1) AS shares_m
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'
AND ticker NOT IN ('SPCX')
GROUP BY ticker
ORDER BY shares_m DESC
LIMIT 4
)
ORDER BY leaderboard ASC, if(leaderboard = 'by dollars traded', dollar_volume_bn, shares_m) DESCMU's $42.94 billion led the tape, SPY second at $27.76 billion, META fourth at $22.72 billion, a falling stock out-trading the index fund by half again. The extremes of the move were the loudest names on it. The share board is the usual funhouse mirror: SOXS, the 3x-inverse semiconductor ETF, led at 553.1 million shares, busiest on the day chips broke, while a low-priced name rounds it out at 189.8 million shares worth $319 million (relative volume flags exactly this). Basis: July 1 regular hours, one reused-symbol listing excluded (receipts).
The options tape
The exact SQL behind every number
WITH
(
SELECT (any(underlying_symbol), any(toFloat64(strike_price)), any(option_type),
sum(size), round(avg(toFloat64(price)), 3),
any(if(substring(ticker, length(ticker) - 14, 6) = '260701', 1, 0)))
FROM global_markets.options_trades
WHERE sip_timestamp >= '2026-07-01 00:00:00' AND sip_timestamp < '2026-07-02 00:00:00'
GROUP BY ticker
ORDER BY sum(size) DESC, ticker ASC
LIMIT 1
) AS top_contract,
(
SELECT round(toFloat64(argMax(close, window_start)), 2)
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'
) AS spy_regular_close
SELECT
round(count() / 1e6, 2) AS option_prints_m,
round(toFloat64(sum(size)) / 1e6, 2) AS contracts_m,
round(100.0 * sumIf(size, option_type = 'C') / sum(size), 1) AS call_pct_of_volume,
round(sumIf(toFloat64(size), option_type = 'P') / sumIf(toFloat64(size), option_type = 'C'), 2) AS put_call_ratio,
round(100.0 * sumIf(size, substring(ticker, length(ticker) - 14, 6) = '260701') / sum(size), 1) AS same_day_expiry_pct,
round(toFloat64(sumIf(size, substring(ticker, length(ticker) - 14, 6) = '260702')) / 1e6, 2) AS thu_jul2_expiry_contracts_m,
countIf(substring(ticker, length(ticker) - 14, 6) = '260703') AS fri_jul3_expiry_prints,
round(toFloat64(sumIf(size, underlying_symbol = 'SPY' AND option_type = 'P')) / 1e6, 2) AS spy_put_contracts_m,
round(100.0 * sumIf(size, underlying_symbol = 'SPY' AND option_type = 'P' AND toFloat64(strike_price) < spy_regular_close * 0.98)
/ sumIf(size, underlying_symbol = 'SPY' AND option_type = 'P'), 1) AS spy_puts_2pct_below_pct,
round(100.0 * sumIf(size, underlying_symbol = 'SPY' AND option_type = 'C' AND toFloat64(strike_price) > spy_regular_close * 1.02)
/ sumIf(size, underlying_symbol = 'SPY' AND option_type = 'C'), 1) AS spy_calls_2pct_above_pct,
round(sumIf(toFloat64(size), underlying_symbol = 'MU' AND option_type = 'P')
/ sumIf(toFloat64(size), underlying_symbol = 'MU' AND option_type = 'C'), 2) AS mu_put_call_ratio,
round(sumIf(toFloat64(size), underlying_symbol = 'META' AND option_type = 'P')
/ sumIf(toFloat64(size), underlying_symbol = 'META' AND option_type = 'C'), 2) AS meta_put_call_ratio,
top_contract.1 AS top_contract_underlying,
top_contract.2 AS top_contract_strike,
top_contract.3 AS top_contract_type,
top_contract.4 AS top_contract_volume,
reverse(arrayStringConcat(extractAll(reverse(toString(assumeNotNull(top_contract.4))), '\\d{1,3}'), ',')) AS top_contract_volume_fmt,
round(top_contract.5, 3) AS top_contract_avg_price,
top_contract.6 AS top_contract_is_same_day,
round(top_contract.2 - spy_regular_close, 2) AS top_strike_minus_spy_close,
spy_regular_close AS spy_close
FROM global_markets.options_trades
WHERE sip_timestamp >= '2026-07-01 00:00:00' AND sip_timestamp < '2026-07-02 00:00:00'Options traded 68.46 million contracts across 11.22 million prints, calls 58.6% of volume, same-day expiries 33.5%. Nobody was hedging the index: 0.71 puts per call market-wide, and of SPY's 5.76 million puts only 11.6% were struck more than two percent below its 745.69 close, the far-downside strikes that pay in a crash. The skew sat in single names: Micron's puts outnumbered its calls (1.11 per call) while META's calls beat its puts better than two to one (0.39). The busiest contract was the same-day SPY $748 call, 878,947 contracts at $0.707 average, expiring 2.31 dollars out of the money, as Tuesday's did. No July 3 expiry printed all day (0 prints, that Friday is closed); the Thursday weekly took 14.43 million.
Rates: drifting up, front end down
Yields are daily closes against June 30.
The exact SQL behind every number
SELECT
t.1 AS curve_point,
round(t.2, 2) AS jul1_yield_pct,
round((t.2 - t.3) * 100) AS one_day_change_bp
FROM (
SELECT arrayJoin([
('1 month', toFloat64(d.yield_1_month), toFloat64(p.yield_1_month)),
('3 month', toFloat64(d.yield_3_month), toFloat64(p.yield_3_month)),
('1 year', toFloat64(d.yield_1_year), toFloat64(p.yield_1_year)),
('2 year', toFloat64(d.yield_2_year), toFloat64(p.yield_2_year)),
('5 year', toFloat64(d.yield_5_year), toFloat64(p.yield_5_year)),
('10 year', toFloat64(d.yield_10_year), toFloat64(p.yield_10_year)),
('30 year', toFloat64(d.yield_30_year), toFloat64(p.yield_30_year)),
('2s10s spread', toFloat64(d.yield_10_year - d.yield_2_year), toFloat64(p.yield_10_year - p.yield_2_year))
]) AS t
FROM (SELECT * FROM global_markets.treasury_yields WHERE date = '2026-07-01') AS d,
(SELECT * FROM global_markets.treasury_yields WHERE date = '2026-06-30') AS p
)The 10-year added 4 bp to 4.48% and the 30-year 6 bp, while the 1-month bill moved -3 bp, belly and long end up, front end down. The 2s10s spread closed at 0.31 percentage points: nothing here matched the equity dispersion.
The calendar behind the day
The exact SQL behind every number
WITH
(
SELECT (count(), uniqExact(publisher))
FROM global_markets.stocks_news
WHERE toDate(toTimeZone(published_utc, 'America/New_York')) = '2026-07-01'
) AS news,
(
SELECT (argMax(t, n), max(n))
FROM (
SELECT t, count() AS n
FROM (
SELECT arrayJoin(tickers) AS t
FROM global_markets.stocks_news
WHERE toDate(toTimeZone(published_utc, 'America/New_York')) = '2026-07-01'
)
WHERE t != 'SPCX'
GROUP BY t
)
) AS top_news
SELECT
(SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS ex_dividend_records,
(SELECT countIf(frequency = 12) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS monthly_payers,
(SELECT countIf(frequency = 4) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS quarterly_payers,
(SELECT round(100.0 * countIf(frequency = 12) / count(), 1) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS monthly_payer_pct,
(SELECT count() FROM global_markets.stocks_splits WHERE execution_date = '2026-07-01') AS splits_executed,
(SELECT count() FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-01') AS ipos_listed,
(SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS sec_filings,
(SELECT uniqExactIf(accession_number, form_type = '4') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS insider_form4_filings,
(SELECT uniqExactIf(accession_number, form_type = '8-K') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS filings_8k,
(SELECT arrayStringConcat(groupArray(concat(ticker, ' — ', issuer_name)), '; ') FROM (
SELECT ticker, issuer_name FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-01' ORDER BY ticker
)) AS ipo_names,
news.1 AS news_articles,
news.2 AS news_publishers,
top_news.1 AS most_covered_ticker,
top_news.2 AS most_covered_articlesThe quarter turn crested here: 746 dividend records went ex-dividend, the wave the June recap watched building, alongside 9 splits and 3 listings (BSP — Bending Spoons S.p.A.; ITG — ITG Inc.; LIME — Neutron Holdings Inc.). The filing feed revived: 4283 filings, 1072 of them Form 4s and 248 8-Ks, after June 30's near-empty index day (the month-end gap note). Our feed carried 201 articles, most-covered MSFT at 16.
But a count says nothing about who was paying. Ranked by the money that traded in them, the board is not corporate at all:
The exact SQL behind every number
WITH divs AS (
SELECT ticker, max(toFloat64(cash_amount)) AS cash, max(frequency) AS freq
FROM global_markets.stocks_dividends
WHERE ex_dividend_date = '2026-07-01' AND distribution_type = 'recurring'
GROUP BY ticker
),
tape AS (
SELECT ticker,
sum(toFloat64(close) * toFloat64(volume)) AS dollar_volume,
toFloat64(argMax(close, (window_start, close))) AS day_close
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'
AND ticker NOT IN ('SPCX')
GROUP BY ticker
)
SELECT
d.ticker AS ticker,
round(d.cash, 4) AS cash_per_share,
d.freq AS payments_per_year,
round(t.day_close, 2) AS day_close,
round(100 * d.cash / t.day_close, 2) AS pct_of_price,
round(100 * d.cash * d.freq / t.day_close, 2) AS annualized_yield_pct,
round(t.dollar_volume / 1e9, 2) AS day_dollar_bn
FROM divs d JOIN tape t ON d.ticker = t.ticker
WHERE t.dollar_volume > 0 AND d.cash > 0
ORDER BY t.dollar_volume DESC
LIMIT 8Every one of the eight busiest ex-dividend tickers is a fund paying 12 times a year: SGOV, a Treasury-bill fund, went ex on $0.2958 a share (0.29% of price, 3.54% annualized) on $3.5 billion traded; HYG, a high-yield bond fund, on $0.3688. That is a first-of-month wave: 572 of the day's 746 records (76.7%) are monthly payers, funds distributing interest, against 123 quarterly payers. The ex-date drop is mechanical, not a loss.
Is the first day of a quarter ever an ordinary day?
The framing writes itself: new quarter, new money, fresh allocations. The database disagrees.
The exact SQL behind every number
SELECT
count() AS quarter_opens_measured,
round(quantileExact(0.5)(oc_pct), 2) AS median_quarter_open_pct,
countIf(oc_pct > 0) AS quarter_opens_green,
countIf(oc_pct <= 0) AS quarter_opens_red,
round(anyIf(oc_pct, first_day = toDate('2026-07-01')), 2) AS jul1_oc_pct,
arrayCount(x -> x < anyIf(oc_pct, first_day = toDate('2026-07-01')), groupArrayIf(oc_pct, first_day != toDate('2026-07-01'))) + 1 AS jul1_rank_worst_to_best,
round(min(oc_pct), 2) AS worst_quarter_open_pct,
round(max(oc_pct), 2) AS best_quarter_open_pct,
concat(monthName(min(first_day)), ' ', toString(toYear(min(first_day)))) AS first_measured
FROM (
SELECT f.first_day AS first_day, d.oc_pct AS oc_pct
FROM (
SELECT toStartOfQuarter(d) AS q, min(d) AS first_day
FROM (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime('2004-01-01 00:00:00')
AND window_start < toDateTime('2026-07-02 00:00:00')
AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
GROUP BY d
)
GROUP BY q
) f
INNER JOIN (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
(argMax(toFloat64(close), (window_start, close)) / argMin(toFloat64(open), (window_start, open)) - 1) * 100 AS oc_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime('2004-01-01 00:00:00')
AND window_start < toDateTime('2026-07-02 00:00:00')
AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
GROUP BY d
) d ON d.d = f.first_day
)Across 91 quarter-opening sessions since January 2004, SPY's median open-to-close move on a quarter's first day is 0.01%, 46 green against 45 red, spanning -2.28% to 3.18%: a coin flip with a rounding error attached. July 1 printed 0.09%, rank 50 of 91 worst to best, dead centre. Basis: SPY regular-hours open-to-close, every quarter's first session in the database.
What the day leaves a reader with
The index moved 0.09%; the eight-name panel spans -10.45% to 8.88%; protection barely repriced. That is the ordinary arithmetic of a concentrated market, one sector's losses offset by gains in 7 of 11 others is what an index nets out. An index-level look sees nothing here; a position-level look sees a tenth of a holding gone in a day.
The session, verified
The exact SQL behind every number
SELECT
formatDateTime(min(toTimeZone(window_start, 'America/New_York')), '%H:%i') AS first_spy_bar_et,
formatDateTime(max(toTimeZone(window_start, 'America/New_York')), '%H:%i') AS last_spy_bar_et,
count() AS spy_minute_bars,
countIf(window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00') AS regular_session_bars,
uniqExactIf(toDate(toTimeZone(window_start, 'America/New_York')), window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00') AS day_sessions,
(SELECT count() FROM global_markets.stocks_market_holidays WHERE date = '2026-07-01') AS jul1_holiday_rows
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2026-07-01 00:00:00' AND window_start < '2026-07-02 00:00:00'SPY's bars run 04:00 to 19:59 New York time, with 390 regular-window bars and 0 holiday rows on the date, a complete session, verified from the tape.
FAQ
Did the stock market go up or down on July 1, 2026?
Depends where you look. SPY closed -0.08%, DIA 0.02%, QQQ -1.44%; 3465 liquid names fell against 2928 rising, yet 7 of 11 sector funds closed green, technology the outlier.
Why did Micron, SanDisk, Western Digital and Seagate all fall on July 1, 2026?
This data reports co-movement, not cause: the four fell between -5.11% and -10.45%. The Motley Fool's same-day piece on Micron (in the news panel on this page, 14:11 ET) ran under the headline "Why Micron Stock Is Plummeting Today". That is the outlet's framing, not a finding in the tape.
Why did META rise on July 1, 2026?
META closed 8.88% higher, its low on the opening bar. The Motley Fool's coverage attributed the move to reports the company planned to sell excess AI computing capacity as a cloud business: the outlet's attribution, not ours.
Is the first trading day of a quarter usually a strong day?
Not measurably. Across 91 quarter openings since January 2004, SPY's median open-to-close move was 0.01%: 46 green, 45 red, a coin flip; July 1 landed mid-pack.
Was the options market hedging the selloff on July 1, 2026?
Not at the index level: 0.71 puts per call market-wide, and only 11.6% of SPY's put volume struck more than two percent below the close.
Data notes
- Dollar volume is a per-minute proxy, close × volume summed per minute bar, regular hours. Displayed extremes were cross-checked against adjacent bars; ties take the earliest.
- No spot VIX index exists here. The volatility panel reads listed VIX-futures funds, which hold and roll futures, related to the index, never identical.
- New quarterly highs/lows compare July 1's regular-hours extremes with each name's April 1–June 30 range, for liquid names with a full quarter of bars; drops are in the panel.
- The sector board is a curated basket (eleven SPDR ETFs, not a vendor field); the news panel is one licensed feed (12 articles, two publishers); one reused-symbol listing is excluded from the leaderboards (its receipts).
Methodology
- One trading session (1 session, verified from observed bars and the holiday table, never assumed). Timestamps are stored in UTC, converted to New York time inside the queries; "close" is the last regular-session minute bar, day changes against June 30.
- Decimals are cast to 64-bit floats before ratio arithmetic; option expiries are re-parsed from the OCC ticker. Panels run once, at authoring time, through the gated read-only path. Warehouse state as of July 13, 2026; this edition adds the sector, volatility, news, dividend and quarter-history panels.
Every panel is a stored query result, chart, table and SQL are one object. Paste any into the Strasmore terminal. Next: July 2; the week: the holiday week.