Strasmore Research
市场回顾 Matt Connor作者： Matt Connor · 更新于 2026-07-23

2026年7月2日美股行情回顾

节前市场轮动明显，QQQ下跌但多数板块收涨，科技股与存储器板块领跌，深度解析行情逻辑。

2026年7月2日（独立日假期前的最后一个交易日）呈现轮动行情，表面表现为抛售。QQQ下跌了 -1.71%，而 DIA上涨了 1.04%，市场宽度为正面：3398 的流动性股票上涨，而增长型指数下跌，2758 的股票下跌，54.6% 的股票上涨。11个板块基金中有8个收涨；抛售主要集中在科技板块和 前一日 破位的存储器板块。

市场表现

查询SPY / QQQ / DIA / IWM — 7月2日对比7月1日收盘（常规交易时段）
每个数字背后的完整 SQL
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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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 >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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.ticker

今日行情概括：DIA 涨 1.04%，QQQ 涨 -1.71%。工业股与成长股的日收益率差距近三个百分点。SPY 涨幅居中，为 -0.12%；IWM 收于 -0.59%。

今日走势异常吗？

单一图表包含两个视角：SPY 的日内涨跌幅与 QQQ 的收盘涨跌幅。两者均按绝对值大小对过去一个月进行排名（排名 1 为最大）。

查询SPY 与 QQQ 在过去一个月交易中的排名（排名1 = 绝对涨跌幅最大）
每个数字背后的完整 SQL
WITH per_day AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS oc_pct,
           argMax(toFloat64(close), window_start) AS rth_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'QQQ')
      AND window_start >= toDateTime('2026-06-02 00:00:00')
      AND window_start < toDateTime('2026-07-03 00:00:00')
      AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
    GROUP BY ticker, d
),
with_prev AS (
    SELECT ticker, d, oc_pct,
           lagInFrame(rth_close) OVER (PARTITION BY ticker ORDER BY d) AS prev_close,
           (rth_close / lagInFrame(rth_close) OVER (PARTITION BY ticker ORDER BY d) - 1) * 100 AS cc_pct
    FROM per_day
)
SELECT
    round(anyIf(oc_pct, ticker = 'SPY' AND d = toDate('2026-07-02')), 2) AS spy_open_to_close_pct,
    arrayCount(x -> x > abs(anyIf(oc_pct, ticker = 'SPY' AND d = toDate('2026-07-02'))),
               groupArrayIf(abs(oc_pct), ticker = 'SPY' AND d != toDate('2026-07-02'))) + 1 AS spy_abs_move_rank,
    countIf(ticker = 'SPY') AS spy_sessions_compared,
    round(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-07-02')), 2) AS qqq_close_over_close_pct,
    arrayCount(x -> x > abs(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-07-02'))),
               groupArrayIf(abs(cc_pct), ticker = 'QQQ' AND d != toDate('2026-07-02') AND isFinite(cc_pct) AND prev_close > 0)) + 1 AS qqq_abs_move_rank,
    countIf(ticker = 'QQQ' AND isFinite(cc_pct) AND prev_close > 0) AS qqq_sessions_compared,
    toString(minIf(d, ticker = 'SPY')) AS first_session
FROM with_prev

从指数层面来看，并不异常。SPY 的 -0.35% 日内涨跌幅在过去 22 个交易日中排名 15 —— 处于后半部分。QQQ 的波动更剧烈，但仍未达到极端水平：其 -1.71% 的收盘涨跌幅在有明确前一交易日收盘价的 21 个交易日中排名 9 —— 回溯至 2026-06-02 —— 对于成长型指数而言，这只是表现平平的一天。个股层面的波动在 7 月 2 日表现显著。

市场宽度：涨幅覆盖面广，增长指数走低

查询7月2日成交额至少 $1M 的个股：上涨 vs 下跌家数
每个数字背后的完整 SQL
WITH per_ticker AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-02 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-02 00:00:00')) AS day_close,
        sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-02 00:00:00') AS day_dollar_volume
    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')
       OR (window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00')
    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,
    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,
    round(100.0 * countIf(day_close > prior_close AND day_dollar_volume >= 1000000)
        / countIf(day_dollar_volume >= 1000000), 1) AS advancer_pct,
    reverse(arrayStringConcat(extractAll(reverse(toString(countIf(day_close > prior_close AND day_dollar_volume >= 1000000))), '[0-9]{1,3}'), ',')) AS advancers_fmt,
    reverse(arrayStringConcat(extractAll(reverse(toString(countIf(day_close < prior_close AND day_dollar_volume >= 1000000))), '[0-9]{1,3}'), ',')) AS decliners_fmt,
    reverse(arrayStringConcat(extractAll(reverse(toString(count() - countIf(day_dollar_volume >= 1000000))), '[0-9]{1,3}'), ',')) AS dropped_by_liquidity_filter_fmt,
    reverse(arrayStringConcat(extractAll(reverse(toString(count())), '[0-9]{1,3}'), ',')) AS tickers_traded_both_sessions_fmt
FROM per_ticker
WHERE prior_close > 0 AND day_close > 0

3,398 只涨，2,758 只跌，63 持平 —— 在 QQQ 下跌之际，54.6% 的活跃股票上涨。市值加权指数与等权重宽度指标表现不一；此类行情导致两者均被列入观察名单。该过滤器排除了 5,317 的 11,536 个交易额低于 100 万美元的双交易日股票。

板块表现：涨跌分布情况

市场广度反映了参与个股的数量，但无法体现行业分布。通过对 11 只 SPDR 板块基金进行行业分类，我们可以通过涨跌幅差距来衡量当日的市场离散度。

查询11 只 SPDR 板块 ETF — 7月2日收盘对比7月1日收盘（常规交易时段）
每个数字背后的完整 SQL
WITH per_etf AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-02 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-02 00:00:00')) AS day_close,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-02 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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00')
        OR (window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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 pts_above_worst_sector,
    day_dollar_bn
FROM per_etf
ORDER BY ticker

医疗保健 (XLV) 领涨，涨幅为 2.63%；其次是公用事业 2.23%、必需消费品 2% 和材料 1.94%。科技 (XLK) 表现最差，跌幅为 -2.71%，是唯一跌幅超过一个百分点的板块；非必需消费品 (-0.81%) 和通信服务 (-0.13%) 也录得下跌，其余八个板块均上涨。最大涨跌幅差距为：5.34 个百分点。市场呈现出 DIA 上涨而 QQQ 下跌的分化态势，这种现象不仅限于四只权重股。因此，在纳斯达克下跌时，上涨-下跌线（advance-decline line）呈现上涨趋势并不矛盾。

今日亮点：存储板块抛售，第二天

周三开始下跌的板块在周四跌幅扩大——表现为波动幅度和联动性增强，而非原因变化。

查询存储与内存板块：对比周三收盘的涨跌幅、波动区间及成交额
每个数字背后的完整 SQL
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-02 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-02 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start >= '2026-07-02 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-02 00:00:00') AS day_low,
        argMinIf(window_start, toFloat64(low), window_start >= '2026-07-02 00:00:00') AS low_bar,
        argMaxIf(window_start, toFloat64(high), window_start >= '2026-07-02 00:00:00') AS high_bar,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-02 00:00:00') / 1e9, 2) AS day_dollar_bn
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('MU', 'SNDK', 'STX', 'WDC')
      AND ((window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00')
        OR (window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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, 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,
    day_dollar_bn
FROM per_name
ORDER BY ticker

SanDisk 下跌 -14.32%，Seagate 下跌 -10.38%，Western Digital 下跌 -9.92%，MU 下跌 -5.57% —— 对应 MU 约 $51.4 billion 的成交额，约为 SPY 成交额的 1.5 倍。MU 和 SanDisk 在盘尾触及低点 (15:26, 15:26 ET)，Seagate 和 Western Digital 触及低点较早 (14:23, 13:59)。背景参考：周三 与 MU 深度分析。

权重股中的另一半轮动：

查询巨头股轮动：对比周三收盘的涨跌幅、波动区间及成交额
每个数字背后的完整 SQL
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-02 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-02 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start >= '2026-07-02 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-02 00:00:00') AS day_low,
        argMinIf(window_start, toFloat64(low), window_start >= '2026-07-02 00:00:00') AS low_bar,
        argMaxIf(window_start, toFloat64(high), window_start >= '2026-07-02 00:00:00') AS high_bar,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-02 00:00:00') / 1e9, 2) AS day_dollar_bn
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'TSLA')
      AND ((window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00')
        OR (window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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, 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,
    day_dollar_bn
FROM per_name
ORDER BY ticker

AAPL 呈单边上涨趋势，涨幅 4.75% —— 低点位于 09:30 ET，高点位于收盘前三分钟的 15:57 —— 而 TSLA 的走势完全相反，跌幅为 -7.65%。MSFT 上涨 1.41%；NVDA 收盘下跌 -1.55%。同个指数，走势截然相反。

资金流向

查询成交量领头羊：成交额前6名，成交量前4名（排除一个待核实的重复代码）
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 >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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 >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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) DESC

MU 以 $51.4 十亿的成交额连续第四个交易日领涨 (周一, 周二, 周三)，而 SPY 的成交额为 $32.7 十亿。SanDisk 以 $26.57 十亿的成交额成为前四名中第二家存储股。SOXS（3倍做空半导体 ETF）以 748.2 百万的成交额位居榜首。成交量统计中，低价股以股数计，高价股以金额计，相对成交量 是将当前成交量与该股自身的常态进行比较。数据基准：7月2日常规交易时段，已排除一个重复代码的上市项目 (收据)。

查询每30分钟时段的成交股数，常规交易时段（单位：十亿）
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
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00'
GROUP BY et_time
ORDER BY et_time

开盘半小时内成交 2.13 十亿股；14:30 时达到 0.81 十亿股的低点；2.3 十亿股在节前收盘时成交 —— 由于 收盘竞价 会将剩余订单合并为单一成交价，收盘时段的成交量为全天最大。

期权行情：移位的周权

查询全天期权概况：成交量、当日到期、节假日调整周及7月月度数据
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 >= '2026-07-02 00:00:00' AND sip_timestamp < '2026-07-03 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 >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 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) = '260702') / 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, substring(ticker, length(ticker) - 14, 6) = '260710')) / 1e6, 2) AS jul10_weekly_contracts_m,
    round(toFloat64(sumIf(size, substring(ticker, length(ticker) - 14, 6) = '260717')) / 1e6, 2) AS jul17_monthly_contracts_m,
    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_fmt,
    round(top_contract.7, 3) AS top_contract_avg_price,
    round(top_contract.2 - spy_regular_close, 2) AS top_strike_minus_spy_close,
    round(spy_regular_close - top_contract.2, 2) AS spy_close_minus_strike
FROM global_markets.options_trades
WHERE sip_timestamp >= '2026-07-02 00:00:00' AND sip_timestamp < '2026-07-03 00:00:00'

期权成交量达 80.96 百万份合约，共计 13.15 百万次打印，其中 47.4% 的成交量在同一周四到期。全天没有任何 7 月 3 日到期的合约（共 0 次打印），因此周四同时面临每日到期和本周移位的周权到期。交易最活跃的合约是当日到期的 SPY $740 看跌期权——成交 540,403 份合约，平均权利金为 $0.499，SPY 收盘价高于行权价 4.8 美元，处于价外；在 周二 和 周三 均为看涨期权的行情中，出现了看跌期权。看涨期权仍占成交量的 58.4%；下一周的周权成交量为 9.64 百万份合约，7 月月权为 8.82 百万份（到期机制）。

The quote tape: what it cost to trade

Prices say what happened; quotes say what it cost. The bid-ask spread is the toll on every round trip, in basis points of the mid-price (a basis point is a hundredth of a percent). We measure it every session, ordinary or not — which is what makes "spreads blew out" a falsifiable claim.

查询个股 NBBO 更新次数：7月2日对比7月1日，含指定代码更新数（单位：百万）
每个数字背后的完整 SQL
SELECT
    round(countIf(toDate(sip_timestamp) = toDate('2026-07-02')) / 1e6, 2) AS jul2_updates_m,
    round(countIf(toDate(sip_timestamp) = toDate('2026-07-01')) / 1e6, 2) AS jul1_updates_m,
    round((countIf(toDate(sip_timestamp) = toDate('2026-07-02')) / countIf(toDate(sip_timestamp) = toDate('2026-07-01')) - 1) * 100, 1) AS day_over_day_pct,
    round(countIf(toDate(sip_timestamp) = toDate('2026-07-02') AND ticker = 'SPY') / 1e6, 2) AS jul2_spy_updates_m,
    round(countIf(toDate(sip_timestamp) = toDate('2026-07-02') AND ticker = 'QQQ') / 1e6, 2) AS jul2_qqq_updates_m,
    round(countIf(toDate(sip_timestamp) = toDate('2026-07-02') AND ticker = 'MU') / 1e6, 2) AS jul2_mu_updates_m
FROM global_markets.cache_stocks_quotes
WHERE sip_timestamp >= '2026-07-01 00:00:00' AND sip_timestamp < '2026-07-03 00:00:00'

The national best bid and offer — the top of the consolidated book — was rewritten 597.22 million times on July 2 against 449.15 million on July 1: a 33% jump into the closure. QQQ took 7.56 million, above SPY's 5.42 million; MU 1.01 million.

查询常规交易时段中值报价价差（基点）：指数 ETF、巨头股及存储板块
每个数字背后的完整 SQL
SELECT
    ticker,
    round(med_bps, 2) AS median_spread_bps,
    round(med_dollars * 100, 1) AS median_spread_cents,
    round(med_bps / min(med_bps) OVER (), 1) AS times_the_spy_spread,
    round(quote_updates / 1e6, 2) AS rth_updates_m,
    invalid_quotes_dropped
FROM (
    SELECT
        ticker,
        quantileExactIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000,
                             toFloat64(bid_price) > 0 AND toFloat64(ask_price) > toFloat64(bid_price)) AS med_bps,
        quantileExactIf(0.5)(toFloat64(ask_price) - toFloat64(bid_price),
                             toFloat64(bid_price) > 0 AND toFloat64(ask_price) > toFloat64(bid_price)) AS med_dollars,
        count() AS quote_updates,
        countIf(NOT (toFloat64(bid_price) > 0 AND toFloat64(ask_price) > toFloat64(bid_price))) AS invalid_quotes_dropped
    FROM global_markets.cache_stocks_quotes
    WHERE ticker IN ('SPY', 'QQQ', 'AAPL', 'TSLA', 'NVDA', 'MU', 'SNDK', 'WDC')
      AND sip_timestamp >= '2026-07-02 13:30:00' AND sip_timestamp < '2026-07-02 20:00:00'
    GROUP BY ticker
)
ORDER BY median_spread_bps ASC

SPY quoted a median 0.27 basis points wide: about 2 cents on a $744.8 ETF. QQQ came in at 0.83 bps, NVDA 1.03. The names doing the falling were the expensive ones to trade: MU 5.52 bps, SanDisk 10.4, Western Digital 10.79 — 40x SPY's spread. Crossing a basket of memory names cost multiples of crossing the index, before any price impact. Invalid quotes (one-sided, crossed) are counted per name, not hidden.

查询流动性是否异常？SPY 常规时段中值价差对比过去一个月交易
每个数字背后的完整 SQL
WITH per_day AS (
    SELECT toDate(sip_timestamp) AS d,
           quantileExact(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000) AS med_bps
    FROM global_markets.cache_stocks_quotes
    WHERE ticker = 'SPY'
      AND sip_timestamp >= '2026-06-02 00:00:00' AND sip_timestamp < '2026-07-03 00:00:00'
      AND (toHour(sip_timestamp) * 60 + toMinute(sip_timestamp)) BETWEEN 810 AND 1199
      AND toFloat64(bid_price) > 0 AND toFloat64(ask_price) > toFloat64(bid_price)
    GROUP BY d
)
SELECT
    round(anyIf(med_bps, d = toDate('2026-07-02')), 3) AS jul2_median_spread_bps,
    round(quantileExact(0.5)(med_bps), 3) AS trailing_median_bps,
    round(anyIf(med_bps, d = toDate('2026-07-02')) - quantileExact(0.5)(med_bps), 3) AS jul2_minus_trailing_bps,
    arrayCount(x -> x > anyIf(med_bps, d = toDate('2026-07-02')), groupArrayIf(med_bps, d != toDate('2026-07-02'))) + 1 AS wider_rank,
    count() AS sessions_compared,
    round(max(med_bps), 3) AS widest_session_bps
FROM per_day

An ordinary day for liquidity, and that is the finding: SPY's median spread of 0.27 bps sits 0 bps from the trailing month's median (0.27 bps), ranking 11 of 22 sessions by wideness — nowhere near the month's widest at 0.409 bps. A concentrated rout under a green tape did not stress the plumbing.

利率：7月2日数据已更新

查询国债记录：7月2日国债发行数据
每个数字背后的完整 SQL
SELECT
    (SELECT count() FROM global_markets.treasury_yields WHERE date = '2026-07-02') AS jul2_rows,
    (SELECT count() FROM global_markets.treasury_yields WHERE date = '2026-07-01') AS jul1_rows

国债数据通常比实时行情滞后一两天：最初发布时，7月2日的收盘数据尚未录入，本页面当时并未进行推测。目前数据已更新 —— 7月2日共有 1 行，7月1日共有 1 行 —— 因此下表反映的是该交易日的实际曲线。

查询当日收益率曲线：7月2日对比7月1日（仅限已公布期限）
每个数字背后的完整 SQL
SELECT
    t.1 AS curve_point,
    round(t.2, 2) AS jul2_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 = '2026-07-02') AS d,
         (SELECT * FROM global_markets.treasury_yields WHERE date = '2026-07-01') AS p
)

收盘时，10年期国债收益率为 4.49%，2s10s 利差为 0.35 个基点。

交易日历回顾

查询7月2日公司日历与信息流（含导致单一虚假筛选器变动的8次拆股）
每个数字背后的完整 SQL
WITH
    (
        SELECT (count(), uniqExact(publisher))
        FROM global_markets.stocks_news
        WHERE toDate(toTimeZone(published_utc, 'America/New_York')) = '2026-07-02'
    ) 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')) = '2026-07-02'
            )
            WHERE t != 'SPCX'
            GROUP BY t
        )
    ) AS top_news,
    (
        SELECT (count(), countIf(split_to > split_from), countIf(split_to < split_from),
                arrayStringConcat(groupArray(concat(ticker, ' ', toString(split_to), '-for-', toString(split_from))), '; '))
        FROM global_markets.stocks_splits
        WHERE execution_date = '2026-07-02' AND ticker NOT IN ('SPCX')
    ) AS splits
SELECT
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-02') AS ex_dividend_records,
    splits.1 AS splits_executed,
    splits.2 AS forward_splits,
    splits.3 AS reverse_splits,
    splits.4 AS split_records,
    (SELECT count() FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-02') AS ipos_listed,
    (SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-02') AS sec_filings,
    (SELECT uniqExactIf(accession_number, form_type = '4') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-02') AS insider_form4_filings,
    (SELECT uniqExactIf(accession_number, form_type = '8-K') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-02') AS filings_8k,
    (SELECT arrayStringConcat(groupArray(concat(ticker, ' — ', issuer_name)), '; ') FROM (
        SELECT ticker, issuer_name FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-02' 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_articles,
    (SELECT any(split_from) FROM global_markets.stocks_splits WHERE ticker = 'CRWD' AND execution_date = '2026-07-02') AS crwd_split_from,
    (SELECT any(split_to) FROM global_markets.stocks_splits WHERE ticker = 'CRWD' AND execution_date = '2026-07-02') AS crwd_split_to,
    (SELECT round(toFloat64(argMax(close, window_start)), 2) FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'CRWD' AND window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00') AS crwd_prev_close,
    (SELECT round(toFloat64(argMax(close, window_start)), 2) FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'CRWD' AND window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00') AS crwd_day_close,
    (SELECT round(sum(toFloat64(close) * toFloat64(volume)) / 1e6, 2) FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'CRWD' AND window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00') AS crwd_dollar_m,
    (SELECT count() FROM (
        SELECT ticker FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN (SELECT ticker FROM global_markets.stocks_splits WHERE execution_date = '2026-07-02')
          AND window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00'
        GROUP BY ticker
    )) AS split_names_with_bars

319 股息记录已进入 除息期，2 股票新股上市（MIACU — Meridian3 Industrials Acquisition Corp.; VIIU — Viking Acquisition Corp. II），SEC 指数记录了 5200 份文件——包括 2109 4 号表格 和 258 8-K 文件。新闻流包含来自 3 家发行商的 201 篇文章（其中 NVDA 为覆盖率最高的 18）。

仅查看收盘价原始数据会误导投资者。CRWD 执行了 4 拆 1 1 的拆股，因此未经调整的行情显示周三为 $772.45，周四为 $193.67——这看似价格下跌，实则是每股拆出四股新股。并非仅此一家：8 笔拆股记录已执行，包括 5 拆股和 3 合股（split_records 列列出了这些记录）。合股会产生相反的假象——原始价格会在隔夜间大幅跳升。在我们的行情中，仅有 2 的股票涉及此类变动；CRWD 高达 $1473.51 的成交额足以影响屏幕显示，因此本处的涨跌幅筛选器已将其排除。

待定事项

日历事实而非预测 —— 以下是后续交易日的统计数据。

查询节假日后：下一交易日、除权除息与拆股、下次预定休市及卖空头寸滞后数据
每个数字背后的完整 SQL
SELECT
    (SELECT count() FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'SPY' AND window_start >= '2026-07-06 13:30:00' AND window_start < '2026-07-06 20:00:00') AS jul6_spy_regular_bars,
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-06') AS exdiv_records_jul6,
    (SELECT arrayStringConcat(groupArray(ticker), ', ') FROM global_markets.stocks_dividends
     WHERE ex_dividend_date = '2026-07-06'
       AND ticker IN ('AAPL', 'MSFT', 'JPM', 'JNJ', 'XOM', 'KO', 'PG', 'WMT', 'CVX', 'HD')) AS household_exdivs_jul6,
    (SELECT count() FROM global_markets.stocks_splits WHERE execution_date = '2026-07-06') AS splits_jul6,
    (SELECT toString(min(date)) FROM global_markets.stocks_market_holidays WHERE date > '2026-07-02') AS next_scheduled_closure,
    (SELECT any(name) FROM global_markets.stocks_market_holidays
     WHERE date = (SELECT min(date) FROM global_markets.stocks_market_holidays WHERE date > '2026-07-02')) AS next_closure_name,
    (SELECT any(status) FROM global_markets.stocks_market_holidays
     WHERE date = (SELECT min(date) FROM global_markets.stocks_market_holidays WHERE date > '2026-07-02')) AS next_closure_status,
    (SELECT toString(max(settlement_date)) FROM global_markets.stocks_short_interest
     WHERE settlement_date <= '2026-07-02') AS latest_si_settlement,
    (SELECT dateDiff('day', max(settlement_date), toDate('2026-07-02')) FROM global_markets.stocks_short_interest
     WHERE settlement_date <= '2026-07-02') AS si_settlement_age_days

7月6日周一开盘，390 交易量全满，其自身K线已证实。该交易日包含 118 股除权记录 —— 在我们调查的十家知名公司中（JPM）包含一家 —— 以及 15 次拆股执行。下次预定收盘时间：Labor Day, 2026-09-07 (closed)。空头头寸数据如往常一样已成旧闻 —— 最新结算记录为 2026-06-30，即 2 天前，发布时间通常滞后于结算约两周 (原因)。

交易时段确认——以及那个并未发生的周五

查询交易时段检查：SPY 观察到的分钟线跨度，及7月3日收盘数据
每个数字背后的完整 SQL
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 >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00') AS regular_session_bars,
    uniqExactIf(toDate(toTimeZone(window_start, 'America/New_York')), window_start >= '2026-07-02 13:30:00' AND window_start < '2026-07-02 20:00:00') AS day_sessions,
    (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
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2026-07-02 00:00:00' AND window_start < '2026-07-03 00:00:00'

7月2日是完整交易时段，而非早盘收盘：SPY 的 K 线从纽约时间 04:00 持续至 19:59（包括 盘前与盘后 K 线），常规交易时段共有 390 根 K 线。7月3日（周五）共生成了 0 根 SPY K 线——由于7月4日独立日恰逢周六，该交易日完成了完整收盘。本周四个交易日的总结：周回顾。

常见问题

为什么 2026 年 7 月 2 日道琼斯指数上涨而纳斯达克指数下跌？

这两个指数包含不同的成分股：DIA 收盘涨 1.04%，QQQ 收盘跌 -1.71%。板块构成也存在差异——医疗保健、公用事业和必需消费品占比最高，科技股占比最低，仅为 -2.71%，两者差距达 5.34 点。

独立日周的周五股市开盘了吗？

没有。由于独立日是在周六，交易所决定在本次交易后的周五全天休市。我们的数据记录显示，该时段内 SPY 的分钟线数据为 0。

拆股对股价有何影响？

拆股会将总股数乘以 4，同时将股价除以 4；持仓总价值保持不变。以 CRWD 为例，7 月 2 日：周三未经调整的收盘价为 $772.45，周四为 $193.67——如果筛选器未考虑拆股因素，会显示虚假的下跌。

2026 年 7 月 2 日的买卖价差有多大？

在常规交易时段，SPY 的中位数报价价差为中间价的 0.27 个基点——在过去 22 个交易日的价差宽度中，该数值仅排在 11 位，属于正常水平。个股价差较宽：MU 为 5.52 bps，WDC 为 10.79。

数据说明

  • 成交额为分钟级代理指标 — 计算方式为：收盘价 × 成交量，按 K 线周期累加。
  • 7 月份 2 年期国债数据在首次发布后才更新 — 原版注释通过行数核对确认了数据的缺失；本次修订已包含该数据，并附上核对记录。
  • CRWD 的原始收盘价变动受拆股影响 — 已从涨跌幅筛选器中剔除。
完整数据说明
  • 板块看板由 11 只 SPDR Select Sector 基金组成 (XLB, XLC, XLE, XLF, XLI, XLK, XLP, XLRE, XLU, XLV, XLY) —— 这是固定的公开篮子，并非供应商提供的板块字段。
  • 报价行情统计按 SIP 时间戳的 UTC 日期进行归类；夏季交易时段会被计入同一个 UTC 日期内。
  • 已从排行榜中剔除一个重复符号的 6 月份上市项目 (核对记录)；详细的逐笔分析见深度研究报告。

方法论

  • 统计周期为一个交易时段（1 个时段，已通过观测 K 线验证）。时间戳以 UTC 存储，并在查询时转换为纽约时间；“收盘”指常规交易时段的最后一分钟 K 线；日期变更以 7 月 2 日对比 7 月 1 日。7 月 3 日的收盘数据已通过 K 线验证，而非假设。
  • 价差（买入价与卖出价之差）以中价的基点（bps）报价，取常规交易时段 NBBO 更新的中位数，基于确定性分位数。小数在进行比例运算前转换为浮点数；期权到期日根据 OCC 代码重新解析。每个面板在编写时通过受限的只读路径读取一次。

图表、表格和 SQL 为统一对象。您可以将任何面板粘贴到 Strasmore 终端进行自定义。前一交易日：7 月 1 日。本周：包含四个交易日的假期周。

#recap#daily#spy#qqq#market structure