Strasmore Research
Market Recap

2026年6月市场行情回顾

Matt ConnorBy Matt Connor Updated 2026-07-23

2026年6月市场呈现分化态势：大盘股指数下跌，而小盘股指数上涨。从成分股表现来看，下跌的股票数量多于上涨的股票数量。SPY 本月收于 $746.32，月涨跌幅为 -1.2%；小盘股指数 IWM 上涨了 4.2%。本月另一显著特征是：一家存储芯片制造商在 21 个交易日内的成交额达到 $995.7 billion，超过了 SPY 本身的成交额。此处所有数据均为存储查询结果；如需查看具体的 SQL 语句，请展开相应面板。

月度行情回顾

查询2026年6月：四大指数ETF开盘至收盘、振幅及常规交易时段成交额
每个数字背后的完整 SQL
SELECT ticker,
    round(argMinIf(toFloat64(open), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_open,
    round(argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_close,
    round((argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / argMinIf(toFloat64(open), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) - 1) * 100, 1) AS month_return_pct,
    round(maxIf(toFloat64(high), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_high,
    round(minIf(toFloat64(low), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_low,
    round(sumIf(toFloat64(close) * toFloat64(volume), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / 1e9, 1) AS rth_dollar_bn
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
  AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY ticker
ORDER BY ticker

数据清晰显示：DIA 2.4% 与 IWM 4.2% 上涨，而 SPY 下跌 -1.2%，QQQ 收于 -0.2% —— 在小盘股上涨 4% 的同月，大盘成长股指数表现持平或下跌。

六月与前五个月的对比

六月的下跌异常吗？后置面板通过单次查询，重新计算了半年中每个月的月度收益率——六月的数据生成逻辑与一月完全一致。

查询2026年1月至6月月度收益率，实时重算 (SPY 和 QQQ)
每个数字背后的完整 SQL
SELECT toString(toStartOfMonth(toDate(toTimeZone(window_start, 'America/New_York')))) AS period_start, ticker,
    round((argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / argMinIf(toFloat64(open), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) - 1) * 100, 1) AS month_return_pct,
    round(argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_close
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ')
  AND window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY period_start, ticker
ORDER BY period_start, ticker

以此衡量，六月的表现属于常态：SPY 的 -1.2% 处于半年收益区间内——三月下跌了 -4.4%，四月上涨了 9.9%。本月的特征是板块轮动，而非整体趋势。

六月行情表现：较往年均值平庸

查询历年6月行情：SPY，按年度一致重算 (显示交易日数量)
每个数字背后的完整 SQL
SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS y,
       uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions,
       round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 1) AS june_return_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY')
  AND window_start >= toDateTime('2003-01-01 00:00:00')
  AND window_start < toDateTime('2026-07-01 00:00:00')
  AND toMonth(toTimeZone(window_start, 'America/New_York')) = 6
  AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY y
HAVING sessions >= 17
ORDER BY y ASC
查询排名记录：本6月与往年对比 (排名1为最优；已排除自身)
每个数字背后的完整 SQL
SELECT round(anyIf(ret, y = 2026), 1) AS june_2026_pct,
       arrayCount(x -> x > anyIf(ret, y = 2026), groupArrayIf(ret, y != 2026)) + 1 AS rank_best,
       count() AS junes_compared,
       min(y) AS first_year,
       anyIf(sessions, y = 2026) AS sessions_2026
FROM (
    SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS y,
           uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions,
           (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS ret
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY')
      AND window_start >= toDateTime('2003-01-01 00:00:00')
      AND window_start < toDateTime('2026-07-01 00:00:00')
      AND toMonth(toTimeZone(window_start, 'America/New_York')) = 6
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY y
    HAVING sessions >= 17
)

自 2004 以来，SPY 的 -1.2% 在所有 23 个六月中的排名为 15（排名 1 为最佳）——处于中游，略低于中位水平。这是一个表现平平的六月，而平庸也是一种有效的结论：该指数层面的月度走势在过去二十年的六月数据中并无特别之处。真正值得关注的是其内部的板块轮动——见下方的广度面板。统计基准：每个日历六月常规交易时段的开盘至收盘表现，每年计算逻辑一致，上限固定在当月月底，以确保对比样本不会随时间无限制扩大。

逐日走势

查询SPY，6月全部21个交易日：收盘价及环比变化
每个数字背后的完整 SQL
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
    round(argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS spy_close,
    round((argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / any(prev) - 1) * 100, 1) AS change_pct
FROM global_markets.delayed_stocks_minute_aggs
INNER JOIN (
    SELECT d, lagInFrame(c) OVER (ORDER BY d ASC ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev
    FROM (
        SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d, argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS c
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-05-29 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
        GROUP BY d
    )
) AS p ON toDate(toTimeZone(window_start, 'America/New_York')) = p.d
WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY et_date
ORDER BY et_date

本月单日最大跌幅发生在月初，即 2026-06-05 下跌了 -2.6。从图表可以看出本月的走势：6月中旬持续走低，在 $716.58 附近筑底，随后在季度末的最后几个交易日出现部分回升。关于该回升阶段最后一周的详细逐日走势，请参阅 周回顾。

市场宽度：下跌股多于上涨股

查询6月上涨与下跌股票数量 (对比5月收盘价)，已披露流动性筛选
每个数字背后的完整 SQL
SELECT
    countIf(chg > 0 AND NOT dropped) AS advancers,
    countIf(chg < 0 AND NOT dropped) AS decliners,
    countIf(chg = 0 AND NOT dropped) AS unchanged,
    countIf(dropped) AS dropped_by_liquidity_filter
FROM (
    SELECT ticker,
        argMaxIf(toFloat64(close), window_start, toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-06-01') AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199)
      - argMaxIf(toFloat64(close), window_start, toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-05-29') AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS chg,
        sumIf(toFloat64(close) * toFloat64(volume), toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-06-01')) < 5e6 AS dropped
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= toDateTime('2026-05-29 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    GROUP BY ticker
    HAVING countIf(toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-05-29') AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) > 0
       AND countIf(toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-06-01') AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) > 0
)

本月有 4608 只股票下跌，而 4240 只股票上涨。尽管四只指数 ETF 中有两只上涨，但市场宽度呈负值。指数权重宽度与等权重宽度反映了不同的维度；六月的表现两者并不一致。流动性筛选排除了六月成交额低于 500 万美元的 2896 只股票，此处将其计入统计而非忽略。日线级别的趋势与个股趋势一致：本月 21 个交易日中，有 12 个交易日的 SPY 收盘下跌，而 9 个交易日收盘上涨。

查询6月内SPY上涨与下跌交易日对比
每个数字背后的完整 SQL
SELECT countIf(day_ret > 0) AS up_sessions,
       countIf(day_ret < 0) AS down_sessions,
       countIf(day_ret = 0) AS flat_sessions,
       count() AS sessions_total
FROM (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 2) AS day_ret
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-06-01 00:00:00')
      AND window_start < toDateTime('2026-07-01 00:00:00')
      AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
    GROUP BY d
)

市场领涨股

查询6月常规交易时段全市场成交额 (排除一个待核实实体的重复代码)
每个数字背后的完整 SQL
SELECT ticker,
    round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 1) AS dollar_bn,
    round(100 * sum(toFloat64(close) * toFloat64(volume)) / max(sum(toFloat64(close) * toFloat64(volume))) OVER (), 1) AS pct_of_leader
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
  AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
  AND ticker NOT IN ('SPCX')
GROUP BY ticker
ORDER BY dollar_bn DESC
LIMIT 8

MU 全月表现最佳，规模达 $995.7 十亿。SPY 位列第二，规模为 77.5%。NVDA 排在第四，规模为 $523 十亿；您可以阅读 其逐笔交易深度分析。半导体板块占据主导，八个标的中包含四个。数据统计范围：6月1日至30日常规交易时段；由于需核实实体身份，已排除一个重复代码的6月上市标的；其首月数据另有专题报道。

期权交易概览：6月对比5月

查询6月：全市场期权合约成交量及当日到期占比 (单次扫描)
每个数字背后的完整 SQL
SELECT round(sum(toFloat64(volume)) / 1e6, 1) AS contracts_mm,
       round(100.0 * sumIf(toFloat64(volume), toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))) / sum(toFloat64(volume)), 1) AS zero_dte_pct,
       uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime('2026-06-01 00:00:00')
  AND window_start < toDateTime('2026-07-01 00:00:00')
查询5月，为作对比一致重算 (单次扫描)
每个数字背后的完整 SQL
SELECT round(sum(toFloat64(volume)) / 1e6, 1) AS contracts_mm,
       round(100.0 * sumIf(toFloat64(volume), toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))) / sum(toFloat64(volume)), 1) AS zero_dte_pct,
       uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime('2026-05-01 00:00:00')
  AND window_start < toDateTime('2026-06-01 00:00:00')

6月全盘 期权成交量 为 1477.9 百万份合约，其中 34.3% 为当日到期 —— 而5月为 1394.6 百万份及 30.3%。成交量增加且当日到期占比上升：6月的 0DTE 占比为上半年最高，自1月以来的演变趋势见 上半年回顾。6月有三分之一的期权成交量在交易当日到期。

查询SPY 中位数报价价差：6月样本交易日对比5月 (每月第二个周三)
每个数字背后的完整 SQL
SELECT toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session,
       round(quantileDeterministicIf(0.5)((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, toUInt64(toUnixTimestamp64Micro(sip_timestamp)), bid_price > 0 AND ask_price >= bid_price), 3) AS med_spread_bps,
       round(count() / 1e6, 2) AS quote_updates_m,
       countIf(NOT (bid_price > 0 AND ask_price > 0 AND ask_price >= bid_price)) AS invalid_dropped
FROM global_markets.cache_stocks_quotes
WHERE ticker = 'SPY'
  AND ((sip_timestamp >= toDateTime64('2026-05-13 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-05-13 20:00:00', 9))
    OR (sip_timestamp >= toDateTime64('2026-06-10 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-06-10 20:00:00', 9)))
GROUP BY session
ORDER BY session ASC

大额交易成本呈现相同趋势：SPY 在6月样本交易日（0.409 bps，6月10日）的中位数报价价差，高于5月（0.27 bps，5月13日）。基准说明：数据采用单日标记样本（每月第二个周三），而非全月中位数；无效报价已计入样本。

利率：收益率曲线波动极小

查询截至6月的国债收益率：10年期、2年期及2s10s利差
每个数字背后的完整 SQL
SELECT toString(date) AS d,
    round(yield_10_year, 2) AS y10,
    round(yield_2_year, 2) AS y2,
    round((yield_10_year - yield_2_year) * 100, 0) AS spread_2s10s_bp
FROM global_markets.treasury_yields
WHERE date >= toDate('2026-06-01') AND date <= toDate('2026-06-30')
  AND isNotNull(yield_10_year) AND isNotNull(yield_2_year)
ORDER BY date

10年期国债6月收于 4.44%，2s10s 利差为 30 个基点。相较于波动剧烈的上半年，利率走势表现平稳（关于半年期收益率曲线的详情，请参阅 H1 回顾）。

行情日历：季末交易密集，缺少一个申报日

查询6月公司日历 — 股息、拆股、上市、备案 (已披露6月30日指数缺口)
每个数字背后的完整 SQL
SELECT
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date >= toDate('2026-06-01') AND ex_dividend_date <= toDate('2026-06-30')) AS ex_div_events,
    (SELECT count() FROM global_markets.stocks_splits WHERE execution_date >= toDate('2026-06-01') AND execution_date <= toDate('2026-06-30')) AS splits,
    (SELECT count() FROM global_markets.stocks_ipos WHERE listing_date >= toDate('2026-06-01') AND listing_date <= toDate('2026-06-30')) AS ipos,
    (SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date >= toDate('2026-06-01') AND filing_date <= toDate('2026-06-30')) AS june_filings,
    (SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = toDate('2026-06-30')) AS filings_jun30,
    (SELECT count() FROM global_markets.stocks_news WHERE published_utc >= toDateTime('2026-06-01 00:00:00') AND published_utc < toDateTime('2026-07-01 00:00:00')) AS news_articles

6 月份包含 6651 除权事件、164 拆股以及 35 新股上市。其中，本月最受关注的上市案例已在 SpaceX 首月深度分析 中逐笔进行了详细解析。关于申报数量的一项说明：SEC 指数显示 6 月共有 68388 份申报文件，但 6 月 30 日当天仅有 31 份——由于该指数尚未统计完该月最后一天的完整数据（相邻日期的申报量达数千份），因此在数据回填前，6 月的总数被低估了。这是 2026 年季末模式的一部分，并附有 诊断说明。

分红潮

查询截至6月的每日除息事件
每个数字背后的完整 SQL
SELECT toString(ex_dividend_date) AS d, count() AS ex_div_events
FROM global_markets.stocks_dividends
WHERE ex_dividend_date >= toDate('2026-06-01') AND ex_dividend_date <= toDate('2026-06-30')
GROUP BY d
ORDER BY d

分红行情在月初集中爆发：6月首日即出现 807 次除权事件。从图表看，全月节奏呈现规律：每日除权数量维持在数百次左右，并在月末出现高峰。关于除权对股价的具体影响，请参阅 除权详解。

空头头寸：6月两份报告均已发布

查询已备案的空头头寸结算：5月29日、6月15日及6月30日
每个数字背后的完整 SQL
SELECT toString(settlement_date) AS settlement, count() AS tickers
FROM global_markets.stocks_short_interest
WHERE settlement_date >= toDate('2026-05-20')
GROUP BY settlement
ORDER BY settlement

空头头寸每两周结算一次，且数据存在滞后。目前 6 月的两份报告均已发布：2026-06-30 结算报告包含 22207 股票，其数据分别对应 6 月 15 日的 22178 和 5 月 29 日的 21987。每日 卖空成交量 是另一套数据集；其 6 月份的局限在于 6 月 29 日的数据文件不完整，相关内容已收录在 周度回顾 和 6月29日深度解析 中。

交易时段统计

查询21个交易日，经行情核实 (包含Juneteenth休市记录)
每个数字背后的完整 SQL
SELECT
    (SELECT uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')) AS june_sessions,
    (SELECT count() FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-06-19 00:00:00') AND window_start < toDateTime('2026-06-20 00:00:00')) AS juneteenth_spy_bars,
    (SELECT countIf((toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) FROM global_markets.delayed_stocks_minute_aggs
     WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')) AS regular_bars_june

6 月共有 21 个交易时段。Juneteenth（6 月 19 日）显示了 0 个 SPY K线。8190 个常规 K线正好对应 21 个完整的 390 分钟交易时段。

数据说明

完整数据说明
  • 卖空头寸涵盖至 6 月 30 日结算日 — 本月两份报告均已归档，并已整合在上方内容中。
  • 6 月 30 日的申报指数数据存在显著缺失（在数千份相邻日期的申报中，仅包含少量行政申报）；在数据回填前，6 月份的申报总量会被低估。所有 2026 年最后一天为工作日的月末数据均存在此情况 —— 诊断说明 中包含相关凭证；Q2 回顾 中包含季度层面的说明。
  • 6 月 29 日 FINRA 卖空成交量文件在全市场范围内均不完整 — 相关凭证见周回顾及 6 月 29 日深度分析报告。
  • 成交量领先者排除说明： 6 月份有一项上市交易使用了重复代码，在完成实体验证前，该项数据不计入排行榜；相关验证凭证见其专属报告。
  • 市场宽度对比： 将每个代码的 6 月最后收盘价与 5 月最后收盘价进行对比；若缺少其中任一收盘价，则该代码会被排除；流动性过滤器排除的代码也计入样本池中。

方法论

  • 统计周期为 2026 年 6 月 1 日至 30 日，共 21 个交易日，已通过观测 K 线（见上方收据面板）进行验证。月度收益率计算方式为该周期内常规交易时段的开盘价至收盘价。
  • 时间戳以 UTC 存储，并使用原始 UTC 范围进行过滤；2026 年 6 月全部采用 EDT 时间，因此常规交易时段为 13:30–20:00 UTC。成交金额为常规交易时段内每分钟收盘价乘以每分钟成交量。
  • 滚动月度对比数据在查询 6 月数据时实时重新计算，不读取存储值。历年 6 月的历史数据块同样基于全分钟线进行计算（采用东部标准时间常规交易时段——这是避开夏令时问题的多年期惯例——其上限固定在当月月底，并显示每年的最小交易日限制）；深度验证详见 H1 回顾 的方法论。
  • 数据通过受限的只读路径生成；公开页面从不查询实时数据。数据仓库状态截至 2026 年 7 月 5 日。

这是定期月度回顾的首版——7 月份版本将链接至此处。如需查看该月最后一周的逐日详情，请参阅 6 月 29 日当周回顾；如需查看本月结束的季度数据，请参阅 Q2 回顾。

#market recap#monthly#breadth#rates#成交量