Strasmore Research
市场回顾 Matt Connor作者: Matt Connor · 更新于 2026-09-28

2026年6月29日股市复盘:关键数字

6月29日市场由成长股领涨,指数上涨但范围较窄,行业分化达四个百分点,存储股冲高回落,0DTE期权、报价价差与利率亦受关注。

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,2327只股票下跌,但近半数行业篮子收跌。所有数字均来自存储查询;展开任意面板即可查看 SQL。该交易日的逐笔交易层面分析:6月29日微观结构深度分析。

记分板

每项变化均比较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日与6月26日收盘价对比,正常交易时段
代码6月26日收盘6月29日开盘6月29日收盘涨跌幅占最佳涨跌幅日内最高日内最低成交股数(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,而周五收盘价为$729.09,最终收于$740.88,低于其$741.56的盘中高点。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。本面板按收盘价与前一交易日收盘价之间的绝对变动幅度,将6月29日与过去一个月进行排名比较。

查询QQQ和SPY:6月29日相对过去一个月交易日的排名(排名1 = 绝对变动最大)
QQQ收盘至收盘涨跌幅QQQ绝对波动排名QQQ比较交易日数QQQ月内最大波动幅度QQQ上涨交易日数SPY收盘至收盘涨跌幅SPY绝对波动排名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

幅度较大,但并非纪录:在自May 29, 2026以来的21个交易日中,QQQ当日的2.57%变动排名第5;该月单日最大变动为4.76%。SPY的1.62%变动在21个交易日中排名第4。变动来源同样重要:SPY开盘至收盘的持续上涨仅为0.59%,因此大部分涨幅来自隔夜跳空,随后常规交易时段的首根K线才完成交易。QQQ在其中10个交易日收盘上涨,几乎相当于正反面各半的月份。

Breadth: how wide was the rally?

An advancer is a ticker whose Monday close beat Friday's, among names trading at least $1 million, a filter dropping 5,108 of 11,475 dual-session tickers.

查询6月29日成交额至少为$1M的股票中,上涨股与下跌股
上涨股下跌股平盘股高流动性代码两交易日均交易代码两交易日均交易代码标签流动性筛选剔除数流动性筛选剔除标签上涨股占比
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

3968 advancers, 2327 decliners, 72 unchanged: 62.3% of the liquid tape rose, counted one name at a time, a wide day.

逐行业看:涨势比表面上更集中

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代表了第二种方式:每个行业对应一篮子按市值加权的标普500指数成分股。其结果与上涨家数统计明显不同。

查询11个行业篮子:6月29日与6月26日收盘价对比,正常交易时段
行业代码涨跌幅振幅成交额(百万)高于最弱行业幅度
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

科技板块领涨,涨幅为2.52%;非必需消费品板块紧随其后,涨幅为2.37%;原材料板块收于-1.82%,房地产板块收于-0.64%。当日行业表现的离散度,即最好板块与最差板块之差,为4.34个百分点。公用事业、必需消费品、能源、房地产和原材料板块均下跌,而指数仍然上涨。按股票数量看,涨势较广;按权重看,涨势集中。这正是指数基金上涨可能掩盖的情况。

当日焦点:存储器与存储设备

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。

查询存储器/存储类股票:相对周五收盘价的变动及日内区间
代码6月26日收盘6月29日收盘涨跌幅日内最高东部时间日内最高价日内最低东部时间日内最低价振幅
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,并在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%的波动区间内收盘上涨-1.9%,是这一组股票中唯一收盘下跌的股票。收盘价掩盖了持仓者经历的盘中波动。

成交资金流向

按成交金额计算,Micron(MU)远超其他标的,包括指数基金:成交额为 $58.47 billion,而 SPY 为 $33.97 billion。按成交股数计算,结果则不同。

查询成交量领先者的两种口径:成交额前6名、成交股数前4名
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

按成交股数排名容易产生误导:成交股数最多的是 SOXS,这是一只三倍杠杆反向半导体ETF,成交量为 695.3 million 股;另一只则是 INLF,这只低价股全天成交 353.8 million 股,但成交金额约为 $23 million。成交金额反映资金流向;相对成交量则显示某只股票自身的交易活跃度是否异常。

以纽约时间每30分钟为一个区间,6月29日呈现出典型的成交量“微笑”形态:

查询每30分钟区间的成交股数,正常交易时段;最后区间包含收盘竞价成交(十亿股)
东部时间股数(十亿)占最大类别百分比高于谷值百分比
09:302.359.8199.9
10:001.949.3147.6
10:301.4236.985.1
11:001.233260.6
11:301.128.643.7
12:000.9123.718.8
12:300.852210.4
13:000.922420.2
13:300.7719.90
14:000.8221.26.4
14:300.8221.47.4
15:001.0527.336.9
15:303.85100401.8
每个数字背后的完整 SQL
SELECT
    et_time,
    round(sum(shares) / 1e9, 2) AS shares_bn,
    round(100 * sum(shares) / max(sum(shares)) OVER (), 1) AS pct_of_biggest_bucket,
    round(100 * (sum(shares) / min(sum(shares)) OVER () - 1), 1) AS pct_above_trough
FROM
(
    SELECT
        formatDateTime(toStartOfInterval(toTimeZone(window_start, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,
        toFloat64(volume) AS shares
    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'
    UNION ALL
    SELECT
        '15:30' AS et_time,
        toFloat64(size) AS shares
    FROM global_markets.stocks_trades
    WHERE sip_timestamp >= '2026-06-29 20:00:00' AND sip_timestamp < '2026-06-29 20:15:00'
      AND has(conditions, 8)
)
GROUP BY et_time
ORDER BY et_time
自己运行这个查询

开盘半小时成交 2.3 billion 股,13:30时降至 0.77 billion 股的低谷;收盘半小时成交量最大,达到 3.85 billion 股。收盘竞价和跟踪指数的资金流通常集中在这一时段。

期权成交情况

期权成交量为 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及假期调整后的周度数据
期权成交笔数(百万)合约数(百万)看涨期权成交量占比当日到期占比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)最大合约标的最大合约行权价最大合约类型最大合约到期日最大合约成交量最大合约成交量标签最大合约平均价格最大行权价减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%,当日所有成交合约中有35.8%于同一个周一到期,即零日到期(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张合约,平均权利金为$0.474。SPY收盘价低于行权价0.12美元,因此当日成交最活跃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。

该面板还统计了股票市场9:30开盘前的40,621笔期权成交,其中每一笔的标的均为现金结算的指数代码(RUTW, SPX, SPXW, VIX, VIXW, XSP);同期股票或ETF期权成交为0笔。这是交易规则,而非偶然现象: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。相关股票可以提前交易,参见盘前和盘后交易;其期权不能提前交易。

带有7月3日周五到期代码的合约全天没有成交(0笔),因为市场当周五休市;7月2日周四到期的合约成交量为10.73百万张。

报价带:当天交易的成本

本页的每个价格都来自报价流,即全国最佳买价和卖价(NBBO)。该报价会针对每只上市证券持续更新。最佳买价与最佳卖价之间的差额,即买卖价差,就是订单为跨越价差而支付的成本。

查询跨越买卖价差的成本:NBBO更新次数及报价中位价差,正常交易时段
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)午盘利差(基点)开盘减午盘(基点)已删除无效报价
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。1万美元订单的一个基点等于1美元。因此,按报价买入并立即卖出1万美元的SPY,交易成本约为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大于午间对照时段。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。价差最宽的证券在开盘时的溢价为6.78个基点。交易活跃度是另一项指标:常规交易时段内,SPY的NBBO更新次数为3.98百万次,QQQ为4.42百万次。

利率:收益率曲线几乎未动

美国国债市场周一交投平静。收益率为日收盘值,变动均较6月26日计算。

查询美国国债收益率曲线:6月29日收盘价与6月26日对比(仅显示有数据的期限)
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年期与2年期收益率之差)收于0.28个百分点(-3个基点):仍为正值,但略微趋平。

日历背后的交易日

查询6月29日公司日历与信息流,汇总为一行
6月29日除息记录知名公司除息已核查知名公司窗口期最繁忙除息日最繁忙除息日记录已执行拆股6月29日上市IPO7月1日IPO首日交易SEC备案文件424B2招股说明书备案内部人士Form 4备案8-K备案新闻文章新闻发布商NVDA相关文章相关文章第二名NVDA减相关文章第二名HON拆股记录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。投资者必须在除息日前持有股票,否则无权领取股息。但在我们核查的25个知名公司中,仅有0个出现相关记录。季度末行情在July 1的746笔记录处达到峰值。当天完成了23次拆分,并有0家公司IPO上市;周三已有BSP, ITG, LIME家公司排定上市。

SEC记录了日期为6月29日的6173份申报文件。其中,1473份结构性产品定价补充文件(424B2表)和1277份内部人交易报告(Form 4),数量远超经常成为新闻焦点的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。剔除一个标签含义不明确、且在查询中已删除的重复代码后,报道最多的是NVDA,共有14篇;排名第二的股票有12篇。

数据说明

异常数据会在此说明,不会被静默剔除。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。每个交易日使用相同的成分名称,而不是供应商按股票代码划分的分类。
  • 美元成交额是按分钟计算的代理指标:每分钟K线的收盘价乘以成交量后求和。该数值接近逐笔成交金额之和,但并不完全相同。
  • 成交量面板的收盘前半小时包含收盘竞价成交。一分钟K线会排除所有竞价成交。因此,半小时面板会将合并行情中时间戳为美东时间下午4:00至4:15、且带有收盘成交条件的每笔交易,加到最后一个时间段。
  • 报价价差排除了无效报价,包括单边报价或交叉NBBO记录。面板会统计被剔除的记录(SPY为1544)。报价中位宽度是报价统计指标,不代表每笔交易的成本,因为订单通常会在报价区间内成交。
  • 单笔成交可能会污染一分钟K线的最高价或最低价。QQQ美东时间11:07的K线出现了709.58美元的低点,但相邻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。以上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。
完整数据说明
  • 国债覆盖范围少于数据结构中列出的范围。四个标注的期限——6个月、3年、7年和20年——从未填入数据。收益率曲线显示现有的七个期限,另加2s10s利差。
  • Honeywell的一项“反向拆股”与行情记录不符。数据源包含一条日期为6月29日的1 HON记录: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。我们未采用该记录。
  • 新闻数量来自一家供应商的资讯源,覆盖我们收录的3家发布方,并不代表“全部市场新闻”。
  • 逐笔成交回执、交叉报价、虚假成交量修正、截断的FINRA卖空成交量文件,以及卖空成交量不等于卖空权益的原因,均见深度解析。

经核实的交易时段

查询交易时段检查:SPY观测到的分钟K线区间,以及行情中的周五休市
7月3日SPY柱线首个 SPY K线(美东时间)最后一个 SPY K线(美东时间)SPY 分钟K线常规交易时段K线QQQ 11:07 单独低点QQQ 11:07 相邻K线低点QQQ 低于相邻值的单独打印
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04:00至19:59,常规交易时段恰好有390根K线。根据成交记录核实,这是完整交易时段。(交易所日历数据集仅包含即将到来的休市安排。)当周的7月3日周五全天休市,0根SPY K线全天均有成交记录;7月4日恰逢周六。四个交易日的一周另有专门回顾。

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收盘价较周五高出2.57%,SPY高出1.62%,DIA高出0.81%,IWM高出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?

重要,但并非异常:QQQ收盘价较前一交易日的2.57%变动,按绝对值计,在过去一个月的21个交易日中排名第5。该月最大变动为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%)在11个SPDR行业篮子中领涨;材料板块垫底,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,有多少属于0DTE?

当日到期的期权占成交的66.33百万张合约中的35.8%。成交最活跃的单一期权合约是当日到期的SPY $741看涨期权,共成交788,133张,最终价外到期。

为什么股票市场开盘前也有期权成交?

只有指数期权会在开盘前交易。2026年6月29日东部时间上午9:30前的全部40,621笔期权成交,都来自现金结算的指数标的(RUTW, SPX, SPXW, VIX, VIXW, XSP)。这些指数期权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;日变动比较6月29日与6月26日,交易时段已根据实际观测到的K线时间范围核实。
  • 过去一个月的排名采用常规交易时段收盘价对收盘价的变动计算,并剔除第一个交易时段,因为窗口内没有此前的收盘价。期权到期日会重新从 OCC ticker 中解析,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的只读路径读取一次。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,包含图表、表格和 SQL。将其中任意对象粘贴到 Strasmore 终端即可。下一交易时段:6月30日】【。