Strasmore Research
市场回顾 Matt Connor作者: Matt Connor · 更新于 2026-08-08

2026年6月29日股市收盘数据复盘

2026年6月29日市场数据:成长股领涨、行业分化约四个百分点,存储芯片冲高回落,0DTE、报价与利率表现如何?查看完整盘面分析。

2026年6月29日(星期一)是由成长股领涨的上涨日,但领涨范围较窄:QQQ上涨 2.57%,SPY上涨 1.62%3968只股票上涨,对比2327只股票下跌;不过,近一半的行业篮子收跌。所有数字均来自存储的查询;展开任一面板即可查看 SQL。同期的逐笔交易层面分析:6月29日微观结构深度分析

盘面概览

每项变动均比较6月29日常规交易时段最后一分钟K线与6月26日星期五的对应数据。

查询SPY / QQQ / DIA / IWM:6月29日较6月26日收盘,常规交易时段
股票代码6月26日收盘价6月29日开盘价6月29日收盘价涨跌幅(%)占最佳涨跌幅(%)日内最高价日内最低价成交股数(百万)
DIA517.5520.63521.680.8131.5522.975519.45.5
IWM297.61298.11298.950.4517.5299.16294.6821.7
QQQ705.84713.99723.952.57100724.58705.17238.5
SPY729.09736.525740.881.6263741.56732.0946
每个数字背后的完整 SQL
WITH friday AS (
    SELECT ticker, argMax(close, window_start) AS friday_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
      AND window_start >= '2026-06-26 13:30:00' AND window_start < '2026-06-26 20:00:00'
    GROUP BY ticker
),
monday AS (
    SELECT ticker,
           argMin(open, window_start) AS monday_open,
           argMax(close, window_start) AS monday_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 >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'
    GROUP BY ticker
)
SELECT
    m.ticker AS ticker,
    toFloat64(f.friday_close) AS jun26_close,
    toFloat64(m.monday_open) AS jun29_open,
    toFloat64(m.monday_close) AS jun29_close,
    round((toFloat64(m.monday_close) / toFloat64(f.friday_close) - 1) * 100, 2) AS pct_change,
    round(100 * (toFloat64(m.monday_close) / toFloat64(f.friday_close) - 1) / max(toFloat64(m.monday_close) / toFloat64(f.friday_close) - 1) OVER (), 1) AS pct_of_best_change,
    toFloat64(m.day_high) AS day_high,
    toFloat64(m.day_low) AS day_low,
    m.shares_traded_m AS shares_traded_m
FROM monday m
JOIN friday f ON m.ticker = f.ticker
ORDER BY m.ticker
自己运行这个查询

SPY开盘报$736.525,而星期五收盘价为$729.09,最终收于$740.88,低于盘中高点$741.56。QQQ上涨2.57%,DIA上涨0.81%,显示当天市场由成长股和科技股领涨;小盘股ETF IWM上涨0.45%。

这一天是否异常?

如果没有参照标准,涨跌幅本身意义有限。本面板按收盘价对收盘价的绝对变动幅度,将6月29日与过去一个月进行比较排名。

查询QQQ和SPY:6月29日在过去一个月交易日中的排名(排名1 = 绝对变动最大)
QQQ收盘至收盘涨跌幅(%)QQQ绝对变动排名QQQ比较交易日数QQQ月内最大变动(%)QQQ上涨交易日数SPY收盘至收盘涨跌幅(%)SPY绝对变动排名SPY比较交易日数SPY开盘至收盘涨跌幅(%)首个交易日
2.575214.76101.624210.59May 29, 2026
每个数字背后的完整 SQL
SELECT
    round(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-06-29')), 2) AS qqq_close_over_close_pct,
    arrayCount(x -> x > abs(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-06-29'))), groupArrayIf(abs(cc_pct), ticker = 'QQQ' AND d != toDate('2026-06-29'))) + 1 AS qqq_abs_move_rank,
    countIf(ticker = 'QQQ') AS qqq_sessions_compared,
    round(max(if(ticker = 'QQQ', abs(cc_pct), 0)), 2) AS qqq_biggest_move_of_month_pct,
    countIf(ticker = 'QQQ' AND cc_pct > 0) AS qqq_up_sessions,
    round(anyIf(cc_pct, ticker = 'SPY' AND d = toDate('2026-06-29')), 2) AS spy_close_over_close_pct,
    arrayCount(x -> x > abs(anyIf(cc_pct, ticker = 'SPY' AND d = toDate('2026-06-29'))), groupArrayIf(abs(cc_pct), ticker = 'SPY' AND d != toDate('2026-06-29'))) + 1 AS spy_abs_move_rank,
    countIf(ticker = 'SPY') AS spy_sessions_compared,
    round(anyIf(oc_pct, ticker = 'SPY' AND d = toDate('2026-06-29')), 2) AS spy_open_to_close_pct,
    concat(monthName(min(d)), ' ', toString(toDayOfMonth(min(d))), ', ', toString(toYear(min(d)))) AS first_session
FROM (
    SELECT ticker, d,
           (close_px / lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY d) - 1) * 100 AS cc_pct,
           oc_pct
    FROM (
        SELECT ticker,
               toDate(toTimeZone(window_start, 'America/New_York')) AS d,
               argMax(toFloat64(close), window_start) AS close_px,
               (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS oc_pct
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN ('SPY', 'QQQ')
          AND window_start >= toDateTime('2026-05-28 00:00:00')
          AND window_start < toDateTime('2026-06-30 00:00:00')
          AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
        GROUP BY ticker, d
    )
)
WHERE isFinite(cc_pct)
自己运行这个查询

涨幅较大,但并非创纪录:QQQ的2.57%变动,在自May 29, 2026以来的21个交易日中排名第5。在这一个月中,单日最大变动为4.76%;SPY的1.62%变动在21个交易日中排名第4。变动来自哪里同样重要:SPY开盘至收盘的上涨仅为0.59%,因此大部分涨幅来自隔夜跳空,在常规交易时段首根K线成交前就已出现。QQQ在其中10个交易日收盘上涨,几乎是五五开。

市场广度:本轮上涨覆盖面有多广?

上涨股是指周一收盘价高于周五收盘价的股票,统计对象为成交额至少达到100万美元的股票。该筛选条件剔除了5,108的双日交易股票,占11,475

查询6月29日成交额至少为100万美元的股票中,上涨股与下跌股
上涨股票数下跌股票数平盘股票数高流动性股票代码两个交易日均交易的股票代码两个交易日均交易的股票代码标签因流动性筛选被剔除因流动性筛选被剔除标签上涨股票占比(%)
396823277263671147511,47551085,10862.3
每个数字背后的完整 SQL
WITH per_ticker AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-06-27 00:00:00')) AS friday_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-06-29 00:00:00')) AS monday_close,
        sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-06-29 00:00:00') AS monday_dollar_volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE (window_start >= '2026-06-26 13:30:00' AND window_start < '2026-06-26 20:00:00')
       OR (window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00')
    GROUP BY ticker
)
SELECT
    countIf(monday_close > friday_close AND monday_dollar_volume >= 1000000) AS advancers,
    countIf(monday_close < friday_close AND monday_dollar_volume >= 1000000) AS decliners,
    countIf(monday_close = friday_close AND monday_dollar_volume >= 1000000) AS unchanged,
    countIf(monday_dollar_volume >= 1000000) AS liquid_tickers,
    count() AS tickers_traded_both_sessions,
    reverse(arrayStringConcat(extractAll(reverse(toString(count())), '[0-9]{1,3}'), ',')) AS tickers_traded_both_sessions_label,
    count() - countIf(monday_dollar_volume >= 1000000) AS dropped_by_liquidity_filter,
    reverse(arrayStringConcat(extractAll(reverse(toString(count() - countIf(monday_dollar_volume >= 1000000))), '[0-9]{1,3}'), ',')) AS dropped_by_liquidity_filter_label,
    round(100.0 * countIf(monday_close > friday_close AND monday_dollar_volume >= 1000000)
        / countIf(monday_dollar_volume >= 1000000), 1) AS advancer_pct
FROM per_ticker
WHERE friday_close > 0 AND monday_close > 0
自己运行这个查询

上涨股3968只,下跌股2327只,持平股72只:按单只股票计,流动性较高的股票中有62.3%上涨,市场上涨覆盖面广。

逐行业看:涨势的覆盖面没有表面上那么广

等权统计股票数量是一种观察方式;按公司规模加权则是另一种。SPDR的11只行业ETF是后者的简写形式:每只ETF代表标普500指数中一个行业、按市值加权的一篮子股票。两种方法对市场广度的判断存在明显差异。

查询11个行业篮子:6月29日较6月26日收盘,常规交易时段
行业股票代码涨跌幅(%)振幅(%)成交额(百万)高于最差行业(%)
TechnologyXLK2.523.9120754.34
Consumer discretionaryXLY2.372.1711424.2
Communication servicesXLC1.660.786693.48
IndustrialsXLI0.891.2312312.72
FinancialsXLF0.280.6415932.1
Health careXLV0.260.7618972.08
UtilitiesXLU-0.321.187591.5
Consumer staplesXLP-0.381.237641.44
EnergyXLE-0.521.5110981.3
Real estateXLRE-0.641.452171.18
MaterialsXLB-1.822.286260
每个数字背后的完整 SQL
WITH per_etf AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-06-27 00:00:00')) AS friday_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-06-29 00:00:00')) AS monday_close,
        maxIf(toFloat64(high), window_start >= '2026-06-29 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-06-29 00:00:00') AS day_low,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-06-29 00:00:00') / 1e6, 0) AS dollar_volume_m
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('XLB', 'XLC', 'XLE', 'XLF', 'XLI', 'XLK', 'XLP', 'XLRE', 'XLU', 'XLV', 'XLY')
      AND ((window_start >= '2026-06-26 13:30:00' AND window_start < '2026-06-26 20:00:00')
        OR (window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'))
    GROUP BY ticker
)
SELECT
    sector,
    ticker,
    round((monday_close / friday_close - 1) * 100, 2) AS pct_change,
    round((day_high / day_low - 1) * 100, 2) AS range_pct,
    dollar_volume_m,
    round((monday_close / friday_close - 1) * 100 - min((monday_close / friday_close - 1) * 100) OVER (), 2) AS pct_above_worst_sector
FROM (
    SELECT *,
        multiIf(ticker = 'XLB', 'Materials',
                ticker = 'XLC', 'Communication services',
                ticker = 'XLE', 'Energy',
                ticker = 'XLF', 'Financials',
                ticker = 'XLI', 'Industrials',
                ticker = 'XLK', 'Technology',
                ticker = 'XLP', 'Consumer staples',
                ticker = 'XLRE', 'Real estate',
                ticker = 'XLU', 'Utilities',
                ticker = 'XLV', 'Health care',
                'Consumer discretionary') AS sector
    FROM per_etf
)
ORDER BY pct_change DESC
自己运行这个查询

科技行业领涨,位于2.52%;非必需消费品行业紧随其后,位于2.37%;材料行业收于-1.82%,房地产行业收于-0.64%。当日行业表现的离散度,即最佳行业与最差行业之差,为4.34个百分点。在指数上涨的当天,公用事业、必需消费品、能源、房地产和材料行业均下跌。按股票数量计算,涨势覆盖面较广;按权重计算,涨势却较为集中。这正是指数基金上涨可能掩盖的情况。

当日焦点:内存与存储

四只股票交易的是同一主题,但结果大不相同。数据仅显示它们的联动性和波动幅度,并未说明原因。

查询内存/存储类股:较周五收盘的变动及日内区间
股票代码6月26日收盘价6月29日收盘价涨跌幅日内最高价日内最高价(ET)日内最低价日内最低价(ET)振幅(%)
MU1122.9211451.971148.7915:591023.6510:1812.22
SNDK2091.082051.29-1.92090.7109:30189510:1810.33
STX895.27968.48.17987.5714:48880.0110:0012.22
WDC586.32651.711.15652.9815:5959009:3110.67
每个数字背后的完整 SQL
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-06-27 00:00:00')) AS friday_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-06-29 00:00:00')) AS monday_close,
        maxIf(toFloat64(high), window_start >= '2026-06-29 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-06-29 00:00:00') AS day_low,
        argMinIf(window_start, toFloat64(low), window_start >= '2026-06-29 00:00:00') AS low_bar,
        argMaxIf(window_start, toFloat64(high), window_start >= '2026-06-29 00:00:00') AS high_bar
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('MU', 'SNDK', 'STX', 'WDC')
      AND ((window_start >= '2026-06-26 13:30:00' AND window_start < '2026-06-26 20:00:00')
        OR (window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'))
    GROUP BY ticker
)
SELECT
    ticker,
    round(friday_close, 2) AS jun26_close,
    round(monday_close, 2) AS jun29_close,
    round((monday_close / friday_close - 1) * 100, 2) AS pct_chg,
    round(day_high, 2) AS day_high,
    formatDateTime(toTimeZone(high_bar, 'America/New_York'), '%H:%i') AS day_high_et,
    round(day_low, 2) AS day_low,
    formatDateTime(toTimeZone(low_bar, 'America/New_York'), '%H:%i') AS day_low_et,
    round((day_high / day_low - 1) * 100, 2) AS range_pct
FROM per_name
ORDER BY ticker
自己运行这个查询

MU是“区间波动”与“净变动”差异的典型案例:盘中波动区间为12.22%,在10:18 ET触及$1023.65低点,在15:59触及$1148.79高点,但收盘价仍较周五高1.97%。Western Digital上涨11.15%,Seagate上涨8.17%;SanDisk在10.33%的区间内收盘上涨-1.9%,是这一组股票中唯一收盘下跌的股票。单看收盘价,无法反映持有者盘中的实际经历。

Where the money traded

By dollars traded, Micron (MU) towered over everything, index funds included: $58.47 billion against SPY's $33.97 billion. By share count, a different day.

查询成交量领先者(两种口径):成交额前6名、成交股数前4名
股票代码排行榜美元成交额(十亿)美元金额(百万)股数(百万)占榜首百分比
MUby dollars traded58.47None53.5100
SPYby dollars traded33.97None4658.1
QQQby dollars traded27.67None38.547.3
NVDAby dollars traded21.66None111.837
TSLAby dollars traded20.66None51.435.3
SNDKby dollars traded19.73None1033.7
SOXSby shares traded2.84None695.3100
INLFby shares traded0.0223353.850.9
TZAby shares traded1.3None330.747.6
BITOby shares traded2.03None250.736.1
每个数字背后的完整 SQL
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 >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'
    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 >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'
    GROUP BY ticker
    ORDER BY shares_m DESC
    LIMIT 4
)
ORDER BY leaderboard ASC, if(leaderboard = 'by dollars traded', dollar_volume_bn, shares_m) DESC
自己运行这个查询

Share-count boards mislead: the share leaders were SOXS, a 3x-leveraged inverse semiconductor ETF (695.3 million shares), and INLF, a penny stock whose 353.8 million shares were worth about $23 million all day. Dollar volume shows where money moved; relative volume shows whether a name's activity is unusual for itself.

In 30-minute New York buckets, June 29 traces the classic volume "smile":

查询每30分钟区间的成交股数,常规交易时段(十亿股)
ET时间股数(十亿)占最大类别百分比高于谷值百分比
09:302.396.3199.9
10:001.979.5147.6
10:301.4259.485.1
11:001.2351.660.6
11:301.146.243.7
12:000.9138.218.8
12:300.8535.410.4
13:000.9238.620.2
13:300.7732.10
14:000.8234.26.4
14:300.8234.57.4
15:001.054436.9
15:302.39100211.4
每个数字背后的完整 SQL
SELECT
    formatDateTime(toStartOfInterval(toTimeZone(window_start, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,
    round(sum(toFloat64(volume)) / 1e9, 2) AS shares_bn,
    round(100 * sum(toFloat64(volume)) / max(sum(toFloat64(volume))) OVER (), 1) AS pct_of_biggest_bucket,
    round(100 * (sum(toFloat64(volume)) / min(sum(toFloat64(volume))) OVER () - 1), 1) AS pct_above_trough
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'
GROUP BY et_time
ORDER BY et_time
自己运行这个查询

2.3 billion shares in the opening half hour, a 0.77 billion trough at 13:30, and the biggest bucket, 2.39 billion, in the closing half hour, where closing auctions and index-tracking flows concentrate.

期权成交明细

期权成交 66.33百万张合约,共计 11.04百万笔成交。

查询整个期权交易日一行:成交量、0DTE、假日调整周
期权成交笔数(百万)合约数(百万)看涨期权成交量占比当日期权到期占比7月2日(周四)到期合约数(百万)7月3日(周五)成交笔数盘前成交笔数盘前成交笔数标签盘前非指数成交笔数盘前标的数SPY合约数(百万)QQQ合约数(百万)最高成交合约标的最高成交合约行权价最高成交合约类型最高成交合约到期日最高成交合约成交量最高成交合约成交量标签最高成交合约平均价格最高行权价减SPY收盘价
11.0466.3355.735.810.7304062140,6210RUTW, SPX, SPXW, VIX, VIXW, XSP12.017.32SPY741C2026-06-29788133788,1330.4740.12
每个数字背后的完整 SQL
WITH
    (
        SELECT (any(underlying_symbol), any(toFloat64(strike_price)), any(option_type),
                any(toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6)))),
                sum(size), count(), round(avg(toFloat64(price)), 3))
        FROM global_markets.options_trades
        WHERE sip_timestamp >= '2026-06-29 00:00:00' AND sip_timestamp < '2026-06-30 00:00:00'
        GROUP BY ticker
        ORDER BY sum(size) DESC
        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 >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 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(100.0 * sumIf(size, substring(ticker, length(ticker) - 14, 6) = '260629') / 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,
    countIf(sip_timestamp < '2026-06-29 13:30:00') AS premarket_prints,
    reverse(arrayStringConcat(extractAll(reverse(toString(countIf(sip_timestamp < '2026-06-29 13:30:00'))), '[0-9]{1,3}'), ',')) AS premarket_prints_label,
    countIf(sip_timestamp < '2026-06-29 13:30:00'
        AND underlying_symbol NOT IN ('SPX', 'SPXW', 'XSP', 'RUTW', 'VIX', 'VIXW')) AS premarket_non_index_prints,
    arrayStringConcat(arraySort(groupUniqArrayIf(underlying_symbol, sip_timestamp < '2026-06-29 13:30:00')), ', ') AS premarket_underlyings,
    round(toFloat64(sumIf(size, underlying_symbol = 'SPY')) / 1e6, 2) AS spy_contracts_m,
    round(toFloat64(sumIf(size, underlying_symbol = 'QQQ')) / 1e6, 2) AS qqq_contracts_m,
    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_expiry,
    top_contract.5 AS top_contract_volume,
    reverse(arrayStringConcat(extractAll(reverse(toString(assumeNotNull(top_contract.5))), '[0-9]{1,3}'), ',')) AS top_contract_volume_label,
    round(top_contract.7, 3) AS top_contract_avg_price,
    round(top_contract.2 - spy_regular_close, 2) AS top_strike_minus_spy_close
FROM global_markets.options_trades
WHERE sip_timestamp >= '2026-06-29 00:00:00' AND sip_timestamp < '2026-06-30 00:00:00'
自己运行这个查询

看涨期权占合约成交量的 55.7%,当日成交合约中有 35.8% 于同一个周一到期,即零日期权(0DTE)占比。全市场最活跃的单一合约是当日到期的 SPY $741 看涨期权:成交 788,133,平均权利金为 $0.474。SPY 收盘价低于行权价 0.12美元,因此当日成交量最大的期权最终价外到期。SPY 作为标的成交 12.01百万张合约;QQQ 为 7.32百万张。

该面板还统计了美股9:30开盘前的 40,621 笔期权成交,其中每一笔的标的都是现金结算的指数代码(RUTW, SPX, SPXW, VIX, VIXW, XSP);同期股票或 ETF 期权仅成交 0 笔。这是交易规则,并非偶然:指数期权设有延长的全球交易时段,股票和 ETF 期权则随股票市场开盘。股票可以在盘前和盘后交易,其期权不能。

全天没有任何合约成交带有7月3日(周五)的到期代码(0笔),因为市场当日休市;7月2日(周四)到期的合约成交了 10.73百万张。

报价带:当天交易成本是多少

本页的每个价格都来自报价流,即全国最佳买卖报价(NBBO)。该报价会针对每只上市证券持续重新发布。最佳买价与最佳卖价之间的差额,即买卖价差,就是订单成交时为跨越价差所支付的成本。

查询跨越买卖价差的成本:NBBO更新次数及报价中位宽度,常规交易时段
股票代码NBBO更新次数(百万)价差中位数(基点)开盘30分钟价差(基点)午盘价差(基点)开盘减午盘基点已剔除无效报价
MU0.754.66.554.112.44414
QQQ4.420.840.980.550.42629
SPY3.980.410.410.270.141544
WDC0.128.214.337.556.7843
每个数字背后的完整 SQL
SELECT
    ticker,
    round(count() / 1e6, 2) AS nbbo_updates_m,
    round(quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price >= bid_price), 2) AS median_spread_bps,
    round(quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price >= bid_price AND sip_timestamp >= '2026-06-29 13:30:00' AND sip_timestamp < '2026-06-29 14:00:00'), 2) AS open_30min_spread_bps,
    round(quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price >= bid_price AND sip_timestamp >= '2026-06-29 17:00:00' AND sip_timestamp < '2026-06-29 17:30:00'), 2) AS midday_spread_bps,
    round(quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price >= bid_price AND sip_timestamp >= '2026-06-29 13:30:00' AND sip_timestamp < '2026-06-29 14:00:00')
        - quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price >= bid_price AND sip_timestamp >= '2026-06-29 17:00:00' AND sip_timestamp < '2026-06-29 17:30:00'), 2) AS open_minus_midday_bps,
    countIf(NOT (bid_price > 0 AND ask_price >= bid_price)) AS dropped_invalid_quotes
FROM global_markets.cache_stocks_quotes
WHERE ticker IN ('SPY', 'QQQ', 'MU', 'WDC')
  AND sip_timestamp >= '2026-06-29 13:30:00' AND sip_timestamp < '2026-06-29 20:00:00'
GROUP BY ticker
ORDER BY ticker
自己运行这个查询

SPY的报价中位价差为其中间价的0.41个基点;QQQ为0.84个基点,Micron为4.6个基点,Western Digital为8.2个基点,是四者中最宽的。1万美元订单每一个基点对应1美元,因此,按报价买入并立即卖出1万美元的SPY,成本约为0.41美元;Western Digital的同样往返交易成本为8.2美元。交易规模没有变化,变化的是证券本身。

四只证券在开盘后半小时的报价价差都宽于午间对照时段。SPY分别为0.41个基点和0.27个基点,Western Digital分别为14.33个基点和7.55个基点;对于价差最宽的证券,开盘溢价为6.78个基点。交易活跃度是另一面:正常交易时段内,SPY的NBBO更新达到3.98百万次,QQQ为4.42百万次。

利率:收益率曲线几乎未变

美国国债市场周一交投平静。收益率为每日收盘数据,变动均为相对于6月26日的变化。

查询美国国债收益率曲线:6月29日收盘较6月26日(仅已填充期限)
曲线点6月29日收益率(%)单日变动(基点)
1 month3.711
3 month3.874
1 year3.973
2 year4.13
5 year4.142
10 year4.380
30 year4.86-1
2s10s spread0.28-3
每个数字背后的完整 SQL
SELECT
    t.1 AS curve_point,
    round(t.2, 2) AS jun29_yield_pct,
    round((t.2 - t.3) * 100) AS one_day_change_bp
FROM (
    SELECT arrayJoin([
        ('1 month',  toFloat64(mon.yield_1_month),  toFloat64(fri.yield_1_month)),
        ('3 month',  toFloat64(mon.yield_3_month),  toFloat64(fri.yield_3_month)),
        ('1 year',   toFloat64(mon.yield_1_year),   toFloat64(fri.yield_1_year)),
        ('2 year',   toFloat64(mon.yield_2_year),   toFloat64(fri.yield_2_year)),
        ('5 year',   toFloat64(mon.yield_5_year),   toFloat64(fri.yield_5_year)),
        ('10 year',  toFloat64(mon.yield_10_year),  toFloat64(fri.yield_10_year)),
        ('30 year',  toFloat64(mon.yield_30_year),  toFloat64(fri.yield_30_year)),
        ('2s10s spread', toFloat64(mon.yield_10_year - mon.yield_2_year), toFloat64(fri.yield_10_year - fri.yield_2_year))
    ]) AS t
    FROM (SELECT * FROM global_markets.treasury_yields WHERE date = '2026-06-29') AS mon,
         (SELECT * FROM global_markets.treasury_yields WHERE date = '2026-06-26') AS fri
)
自己运行这个查询

10年期国债收益率收于4.38%,日内持平(0个基点);3个月期国库券收益率上升4个基点,至3.87%。2s10s利差(10年期减去2年期)收于0.28个百分点(-3个基点):仍为正值,但略有趋平。

日历背后的交易日

查询6月29日公司日历及信息流,一行呈现
6月29日除息记录知名公司除息数已检查知名公司数窗口期最繁忙除息日最繁忙除息日记录数已执行拆股6月29日上市IPO数7月1日IPO首发数SEC申报文件424B2招股说明书申报数内部人士Form 4申报数8-K申报数新闻文章数新闻发布商数NVDA文章数次高关注度文章数NVDA减次高关注度数HON拆股记录数HON拆股前HON拆股后HON 6月26日收盘价HON 6月29日收盘价
449025July 1746230BSP, ITG, LIME617314731277231170314122121231.3227.71
每个数字背后的完整 SQL
WITH
    (
        SELECT (argMax(d, n), max(n))
        FROM (
            SELECT ex_dividend_date AS d, count() AS n
            FROM global_markets.stocks_dividends
            WHERE ex_dividend_date BETWEEN '2026-06-22' AND '2026-07-02'
            GROUP BY d
        )
    ) AS peak_ex_div,
    (
        SELECT (countIf(form_type = '424B2'), countIf(form_type = '4'), countIf(form_type = '8-K'), count())
        FROM global_markets.stocks_sec_edgar_index
        WHERE filing_date = '2026-06-29'
    ) AS filings,
    (
        SELECT (count(), uniqExact(publisher), countIf(has(tickers, 'NVDA')))
        FROM global_markets.stocks_news
        WHERE toDate(toTimeZone(published_utc, 'America/New_York')) = '2026-06-29'
    ) AS news,
    (
        SELECT 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')) = '2026-06-29'
            )
            WHERE t NOT IN ('NVDA', 'SPCX')
            GROUP BY t
        )
    ) AS runner_up_articles,
    (
        SELECT (any(split_from), any(split_to), count())
        FROM global_markets.stocks_splits
        WHERE ticker = 'HON' AND execution_date = '2026-06-29'
    ) AS hon_split,
    (
        SELECT (
            round(toFloat64(argMaxIf(close, window_start, window_start < '2026-06-27 00:00:00')), 2),
            round(toFloat64(argMaxIf(close, window_start, window_start >= '2026-06-29 00:00:00')), 2)
        )
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'HON'
          AND ((window_start >= '2026-06-26 13:30:00' AND window_start < '2026-06-26 20:00:00')
            OR (window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'))
    ) AS hon_close
SELECT
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-06-29') AS ex_dividend_records_jun29,
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-06-29'
        AND ticker IN ('AAPL', 'MSFT', 'NVDA', 'AMZN', 'GOOGL', 'GOOG', 'META', 'TSLA', 'JPM', 'JNJ',
                       'XOM', 'KO', 'PG', 'V', 'MA', 'HD', 'WMT', 'CVX', 'MRK', 'PEP',
                       'SPY', 'QQQ', 'DIA', 'IWM', 'VTI')) AS household_name_ex_dividends,
    length(['AAPL', 'MSFT', 'NVDA', 'AMZN', 'GOOGL', 'GOOG', 'META', 'TSLA', 'JPM', 'JNJ',
            'XOM', 'KO', 'PG', 'V', 'MA', 'HD', 'WMT', 'CVX', 'MRK', 'PEP',
            'SPY', 'QQQ', 'DIA', 'IWM', 'VTI']) AS household_names_checked,
    concat(monthName(peak_ex_div.1), ' ', toString(toDayOfMonth(peak_ex_div.1))) AS busiest_ex_div_day_of_window,
    peak_ex_div.2 AS busiest_ex_div_day_records,
    (SELECT count() FROM global_markets.stocks_splits WHERE execution_date = '2026-06-29') AS splits_executed,
    (SELECT count() FROM global_markets.stocks_ipos WHERE listing_date = '2026-06-29') AS ipos_listed_jun29,
    (SELECT arrayStringConcat(groupArray(ticker), ', ') FROM (
        SELECT ticker FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-01' ORDER BY ticker
    )) AS jul1_ipo_debuts,
    filings.4 AS sec_filings,
    filings.1 AS prospectus_424b2_filings,
    filings.2 AS insider_form4_filings,
    filings.3 AS filings_8k,
    news.1 AS news_articles,
    news.2 AS news_publishers,
    news.3 AS nvda_articles,
    runner_up_articles AS next_most_covered_articles,
    news.3 - runner_up_articles AS nvda_minus_next_most_covered,
    hon_split.3 AS hon_split_records,
    hon_split.1 AS hon_split_from,
    hon_split.2 AS hon_split_to,
    hon_close.1 AS hon_close_jun26,
    hon_close.2 AS hon_close_jun29
自己运行这个查询

449笔股息记录于6月29日除息。您必须在该股票的除息日前持有,否则无权获得股息。但在我们核查的25个知名公司中,只有0个出现了相关记录。季度末行情在July 1746笔记录处达到峰值。当天完成了23次拆股并有0家公司完成IPO上市;周三的新股首日交易(BSP, ITG, LIME)已列入日历。

SEC记录了日期为6月29日的6173份申报文件:1473份结构性产品定价补充文件(表格424B2)和1277内部人交易报告(表格4),数量远超受到新闻关注的231份8-K文件。我们的新闻源收录了来自3家出版机构的170篇文章;排除一个标签含义不明确且在查询中剔除的重复代码后,报道最多的公司是NVDA,共有14篇文章;排名第二的公司为12篇。

数据说明

异常数据会单独注明,不会被默默剔除。以下四点会影响标题数据。

  • 行业篮子采用预先声明的方法。“行业”指11只SPDR行业ETF,按市值加权。每个交易时段使用相同的成分,而不是供应商按ticker划分的分类。
  • 美元成交额是每分钟的代理指标。计算方法为每分钟K线的收盘价乘以成交量后求和。该结果接近逐笔成交金额之和,但并不完全相同。
  • 报价价差已排除无效报价。包括单边报价或交叉NBBO记录。面板会统计剔除数量(SPY为1544)。报价中位宽度是报价统计指标,并不代表每笔交易成本,因为订单通常会在报价区间内成交。
  • 单笔成交可能污染一分钟K线的最高价或最低价。QQQ在美国东部时间11:07的K线录得709.58美元的低点,而相邻K线均未跌破715.09美元;其中一笔成交比同期市场价格低5.51美元。上文所有最高价和最低价均已与相邻K线交叉核对。QQQ的705.172美元盘中低点通过了核验。

:::details完整数据说明

  • 国债期限覆盖范围少于数据结构设定。所列四个期限,即6个月、3年、7年和20年,从未填充过数据。收益率曲线展示现有的七个期限,另加2s10s一行。
  • Honeywell的一次“反向拆股”与交易记录不符。数据源载有一条日期为6月29日的HON记录1:反向拆股将2股旧股转换为1股新股。HON周五收于231.3美元,周一收于227.71美元,并未翻倍。因此我们未应用该调整。
  • 新闻数量来自一家供应商的资讯源。统计的是我们收录的3家媒体,而不是“所有市场新闻”。
  • **逐笔成交记录、交叉报价、虚假成交量修正、截断的FINRA卖空成交量文件,以及成交量不等于卖空权益的原因,均见深度解析

:::

本交易时段已核实

查询交易时段检查:SPY观测到的分钟K线区间,以及周五休市在行情记录中的体现
7月3日SPY柱数SPY首根柱(美东时间)SPY 最后一根K线(美东时间)SPY 分钟K线常规交易时段K线QQQ 1107 单独低点QQQ 1107 相邻K线低点QQQ 低于相邻价位的单独成交
004:0019:59897390709.58715.095.51
每个数字背后的完整 SQL
WITH
    (
        SELECT (
            round(toFloat64(minIf(low, formatDateTime(toTimeZone(window_start, 'America/New_York'), '%H:%i') = '11:07')), 2),
            round(toFloat64(minIf(low, formatDateTime(toTimeZone(window_start, 'America/New_York'), '%H:%i') IN ('11:04', '11:05', '11:06', '11:08', '11:09', '11:10'))), 2)
        )
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'QQQ' AND window_start >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00'
    ) AS qqq_lone
SELECT
    (SELECT count() FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'SPY' AND window_start >= '2026-07-03 00:00:00' AND window_start < '2026-07-04 00:00:00') AS jul3_spy_bars,
    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 >= '2026-06-29 13:30:00' AND window_start < '2026-06-29 20:00:00') AS regular_session_bars,
    qqq_lone.1 AS qqq_1107_lone_low,
    qqq_lone.2 AS qqq_1107_adjacent_bars_low,
    round(qqq_lone.2 - qqq_lone.1, 2) AS qqq_lone_print_below_adjacent
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2026-06-29 00:00:00' AND window_start < '2026-06-30 00:00:00'
自己运行这个查询

SPY的K线覆盖纽约时间04:0019:59,常规交易时段恰好包含390根K线,构成完整交易时段;这一点已根据逐笔成交记录核实(交易所日历数据集仅记录即将到来的休市日)。当年7月3日星期五全天休市,0根SPY K线全天均无成交;7月4日为星期六。这一周仅有四个交易日,另有专门回顾

常见问题

2026年6月29日股市表现如何?

成长股领涨,市场上涨:QQQ较周五收盘上涨2.57%,SPY上涨1.62%,DIA上涨0.81%,IWM上涨0.45%。成交额达到100万美元或以上的股票中,有62.3%收高。

2026年6月29日是纳斯达克的重要交易日吗?

表现强劲,但并不异常:QQQ较前一交易日收盘的2.57%涨跌幅,按绝对值计算,在过去一个月的21个交易日中排名5。该月最大单日涨跌幅为4.76%。

2026年6月29日哪些板块领涨?

科技板块(2.52%)和非必需消费品板块(2.37%)领涨十一只SPDR行业篮子。材料板块垫底,涨跌幅为-1.82%,板块间差距为4.34个百分点。公用事业、必需消费品、能源和房地产板块也收低。

2026年6月29日的期权成交量中,有多少是0DTE?

当日到期的期权占成交的35.8%。当日共成交66.33百万张合约。单一合约中成交最活跃的是一份当日到期的SPY $741看涨期权,共成交788,133张,最终价外到期。

为什么期权会在股市开盘前交易?

只有指数期权会这样交易。6月29日美国东部时间上午9:30前的全部40,621笔期权成交,均对应现金结算的指数根(RUTW, SPX, SPXW, VIX, VIXW, XSP)。这些指数根提供延长的全球交易时段。同期股票和ETF期权成交笔数为0

方法

  • 时间戳以 UTC 存储,并在查询中转换为纽约时间。“收盘价”指常规交易时段最后一分钟的K线,不包括集合竞价成交价;日变化比较6月29日与6月26日,交易时段已根据观测到的K线时间跨度完成核验。
  • 过去一个月的排名采用常规交易时段的收盘价对收盘价涨跌幅,并剔除首个交易时段,因为窗口内没有其前一收盘价。期权到期日会根据 OCC ticker 重新解析,因为表格自身的到期日列存在错误。
  • 每个面板均在撰写时通过受限只读路径读取一次。数据仓库状态截至2026年7月13日。

每个面板都是一个存储查询结果对象,其中包含图表、表格和 SQL。您可以将其中任何一个粘贴到 Strasmore 终端。下一交易时段:6月30日