Strasmore Research
Deep Dives · Matt ConnorBy Matt Connor · · Updated 2026-08-08

MU: 2026年6月美光成交额与市场排名

美光6月常规交易时段成交额达995.7十亿美元,位列市场第first,重估降温至14%,并详解成交、波动率与期权数据。

美光在2026年上半年经历了剧烈重估。6月股价降温,但成交并未平静。MU 6月收于 $1151.01,上涨 14%,为2月以来最平静的月份;此前5月上涨 89.8%。其常规交易时段成交额为 $995.7 billion,在整个美国市场成交额中排名 first,甚至高于SPY本身。按日计算,6月也是上半年波动率最高的月份(年化 127.6%)。这种平静只是终点造成的错觉。以下内容涵盖6月成交数据、交易记录、财报周申报文件、波动率、同业、价差、期权、空头,以及这六个月的走势。所有数字均来自已存储的查询;展开任一面板即可查看其SQL。

单行概览

查询MU六月单行概览:开盘、收盘、极值、成交额及其回报
月初开盘价月末收盘价月度回报率 (%)月内最高价月内最高价首次出现时间(美东时间)月内最低价月内最低价首次出现时间(美东时间)常规交易时段最低价−延长交易时段最低价月成交股数(十亿)常规交易时段成交额(十亿美元)观测交易日数SPY 6月19日K线数
1009.721151.011412552026-06-25 09:35850.12026-06-05 16:344.251.08995.7210
每个数字背后的完整 SQL
WITH
    (
        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 spy_jun19,
    (
        SELECT max(toFloat64(high)) FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'MU'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    ) AS hi,
    (
        SELECT min(toFloat64(low)) FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'MU'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    ) AS lo
SELECT
    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(hi, 2) AS month_high,
    formatDateTime(toTimeZone(minIf(window_start, toFloat64(high) >= hi - 0.011), 'America/New_York'), '%Y-%m-%d %H:%i') AS month_high_first_bar_et,
    round(lo, 2) AS month_low,
    formatDateTime(toTimeZone(minIf(window_start, toFloat64(low) <= lo + 0.011), 'America/New_York'), '%Y-%m-%d %H:%i') AS month_low_first_bar_et,
    round(minIf(toFloat64(low), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) - lo, 2) AS rth_minus_extended_low,
    round(toFloat64(sum(volume)) / 1e9, 2) AS month_shares_bn,
    round(sumIf(toFloat64(close) * toFloat64(volume), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / 1e9, 1) AS rth_dollar_bn,
    uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS session_days_observed,
    spy_jun19 AS spy_bars_june19
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'MU'
  AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
自己运行这个查询

对于这样规模的股票而言,月内波动区间极其庞大:最低价为$850.12026-06-05 16:34 ET),最高价为$12552026-06-25 09:35 ET),区间甚至超过多数股票全年的波动范围。6月19日全市场休市(0 SPY K线),因此当月共计21个交易日。

与半年走势相比,六月表现

+14%算高吗?对该ticker而言,在这半年中,六月是最平静的月份。该面板每月以完全相同的方式实时重新计算。

查询MU逐月实时重算:回报、收盘价及常规交易时段成交额
期间开始月度回报率 (%)月末收盘价常规交易时段成交额(十亿美元)
2026-01-0140.5414.73235.8
2026-02-010412.25236
2026-03-01-15.9337.62342.7
2026-04-0148.4517.63335
2026-05-0189.8971.58716.8
2026-06-01141151.01995.7
每个数字背后的完整 SQL
SELECT toString(toStartOfMonth(toDate(toTimeZone(window_start, 'America/New_York')))) AS period_start,
    round((argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) / argMinIf(toFloat64(open), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) - 1) * 100, 1) AS month_return_pct,
    round(argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959), 2) AS month_close,
    round(sumIf(toFloat64(close) * toFloat64(volume), (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) / 1e9, 1) AS rth_dollar_bn
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'MU'
  AND window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY period_start
ORDER BY period_start
自己运行这个查询

走势如下:一月为40.5%,二月持平,为0%;三月出现-15.9%,收盘价降至半年低点($337.62);随后四月为48.4%,五月为89.8%。六个月内,价格从$414.73升至$1151.01。成交额也随之上升:一月为$235.8 billion,六月为$995.7 billion。六月的价格变动为二月以来最小,但成交额为该区间内最高。

价格降温了,波动率没有。

一个上涨14%的月份算平静吗?已实现波动率反映每日收盘价变动,并按年化计算。按这一指标看,六月则完全不同。

查询MU逐月数据:年化实现波动率、平均日内区间、单日最大变动
期间开始年化已实现波动率 (%)占峰值波动率 (%)日均波动幅度 (%)最大单日变动 (%)收益日数
2026-01-0164.850.85.41019
2026-02-0167.853.16.31019
2026-03-0178.261.369.922
2026-04-0159.246.45.59.121
2026-05-01101.479.47.219.320
2026-06-01127.61007.615.821
每个数字背后的完整 SQL
SELECT
    toString(toStartOfMonth(et_date)) AS period_start,
    round(stddevSamp(log_ret) * sqrt(252) * 100, 1) AS realized_vol_ann_pct,
    round(100 * stddevSamp(log_ret) / max(stddevSamp(log_ret)) OVER (), 1) AS pct_of_peak_vol,
    round(avg(day_range_pct), 1) AS avg_day_range_pct,
    round(max(abs(day_move_pct)), 1) AS biggest_day_move_pct,
    count() AS return_days
FROM (
    SELECT et_date, day_range_pct,
        if(prev_close > 0, ln(close_usd / prev_close), NULL) AS log_ret,
        if(prev_close > 0, (close_usd / prev_close - 1) * 100, NULL) AS day_move_pct
    FROM (
        SELECT et_date, close_usd, day_range_pct,
            lagInFrame(close_usd) OVER (ORDER BY et_date ASC ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
        FROM (
            SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
                argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS close_usd,
                (maxIf(toFloat64(high), (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) / minIf(toFloat64(low), (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) - 1) * 100 AS day_range_pct
            FROM global_markets.delayed_stocks_minute_aggs
            WHERE ticker = 'MU'
              AND window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
            GROUP BY et_date
        )
    )
)
WHERE isFinite(log_ret) AND log_ret IS NOT NULL
GROUP BY period_start
ORDER BY period_start
自己运行这个查询

按这一指标衡量,六月是上半年波动最剧烈的月份:年化波动率为127.6%,甚至高于五月的101.4%;日均交易区间为7.6%,其中还有一次收盘价较前一日收盘价变动15.8%。期初和期末较为平静,但期间的交易日并不平静。

逐个交易时段

查询21个交易日:收盘价、收盘至收盘变动、全天成交量
21 rows (showing 20)
美东日期收盘价(美元)变动 (%)成交股数(百万)
2026-06-011034.83None43.7
2026-06-021064.082.843
2026-06-031079.561.537.5
2026-06-04997.17-7.651.6
2026-06-05864.01-13.471.3
2026-06-08949.479.950.5
2026-06-09935.89-1.470.2
2026-06-10891.5-4.752.8
2026-06-11995.6511.753.7
2026-06-12980.71-1.538.9
2026-06-151087.810.939.8
2026-06-161020.83-6.241.6
2026-06-171041.41243.4
2026-06-181132.018.748.2
2026-06-221211.2746.3
2026-06-231051.42-13.254
2026-06-241048.5-0.364.6
2026-06-251214.5915.877.2
2026-06-261122.92-7.558.8
2026-06-291145257.8
每个数字背后的完整 SQL
SELECT et_date, close_usd,
    round(if(prev_close = 0, NULL, (close_usd / prev_close - 1) * 100), 1) AS change_pct,
    shares_m
FROM (
    SELECT et_date, close_usd, shares_m,
           lagInFrame(close_usd) OVER (ORDER BY et_date ASC ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
    FROM (
        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 close_usd,
            round(toFloat64(sum(volume)) / 1e6, 1) AS shares_m
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'MU'
          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
自己运行这个查询

该表在整个期间剧烈双向波动,从2026-06-01的$1034.83一路经历动荡,最终在最后一个交易时段达到$1151.01。这正是“本月上涨14%”所掩盖的情况:只有起点和终点较为平静。最剧烈的几行数据集中在财报周,下面将重点列出。

这些波动是否与已披露的季度业绩相吻合?

可以确定日期:根据SEC自身的索引,MU在6月的文件记录与这些日期的股价走势相互对应。

查询MU六月SEC文件及季度8-K后交易日
业绩8-K已提交6月24日8-K10-Q已提交8-K至10-Q天数6月文件总数8-K文件数Form 4文件数下一交易日涨跌幅下一交易日成交股数(百万)领先第二活跃品种成交股数(百万)6月25日月内高点
2026-06-2412026-06-25182315.877.25.91
每个数字背后的完整 SQL
WITH
    (
        SELECT maxIf(filing_date, form_type = '8-K')
        FROM global_markets.stocks_sec_edgar_index
        WHERE cik = '0000723125' AND filing_date >= toDate('2026-06-01') AND filing_date <= toDate('2026-06-30')
    ) AS last_8k_date,
    (
        SELECT minIf(filing_date, form_type = '10-Q')
        FROM global_markets.stocks_sec_edgar_index
        WHERE cik = '0000723125' AND filing_date >= toDate('2026-06-01') AND filing_date <= toDate('2026-06-30')
    ) AS tenq_date,
    (
        SELECT (count(), countIf(form_type = '8-K'), countIf(form_type = '4'))
        FROM global_markets.stocks_sec_edgar_index
        WHERE cik = '0000723125' AND filing_date >= toDate('2026-06-01') AND filing_date <= toDate('2026-06-30')
    ) AS filing_census,
    (
        SELECT toDate(toTimeZone(min(window_start), 'America/New_York'))
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'MU'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
          AND toFloat64(high) >= (
              SELECT max(toFloat64(high)) FROM global_markets.delayed_stocks_minute_aggs
              WHERE ticker = 'MU' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
          ) - 0.011
    ) AS month_high_date
SELECT
    toString(last_8k_date) AS earnings_8k_filed,
    if(last_8k_date = toDate('2026-06-24'), 1, 0) AS eightk_on_jun24,
    toString(tenq_date) AS tenq_filed,
    dateDiff('day', last_8k_date, tenq_date) AS days_8k_to_10q,
    filing_census.1 AS june_filings_total,
    filing_census.2 AS eightk_filings,
    filing_census.3 AS form4_filings,
    round((anyIf(close_usd, et_date = toDate('2026-06-25')) / anyIf(close_usd, et_date = toDate('2026-06-24')) - 1) * 100, 1) AS next_session_move_pct,
    round(anyIf(shares_m, et_date = toDate('2026-06-25')), 1) AS next_session_shares_m,
    round(anyIf(shares_m, et_date = toDate('2026-06-25')) - maxIf(shares_m, et_date != toDate('2026-06-25')), 1) AS shares_lead_over_next_busiest_m,
    if(month_high_date = toDate('2026-06-25'), 1, 0) AS month_high_on_jun25
FROM (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
        argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS close_usd,
        toFloat64(sum(volume)) / 1e6 AS shares_m
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MU'
      AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    GROUP BY et_date
)
自己运行这个查询

MU的季度8-K日期为2026-06-24,10-Q晚一天,即18为6月提交的文件,3为内部人士提交的Form 4)。8-K日期后的交易日收盘上涨15.8%,成交量为77.2百万股,为当月最高,比次高成交量多5.9百万股;当月$1255的高点也在同一交易日创出(2026-06-25 09:35 ET;协议栏确认了这一对应关系)。这里仅陈述这一时间对应关系,本文不作进一步判断。

美光的故事,还是存储行业的故事?

其他存储和内存相关股票是否也同步上涨?这组股票是固定且预先确定的:包括六月新闻中与 MU 最常共同出现的三只存储股,以及作为基准的 NVDA 和 SPY。

查询六月并列对比:存储篮子、NVDA和SPY
ticker6月回报率相对MU百分点常规交易时段成交额(十亿美元)占最高成交额百分比
SNDK31.317.3381.638.3
INTC27.513.5272.427.4
WDC19.15.1105.110.6
MU140995.7100
SPY-1.2-15.2771.577.5
NVDA-7.4-21.452352.5
每个数字背后的完整 SQL
WITH (
    SELECT (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
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MU' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
) AS mu_return
SELECT ticker,
    round(june_return_pct, 1) AS june_return_pct,
    round(june_return_pct - mu_return, 1) AS vs_mu_pct_points,
    rth_dollar_bn,
    round(100 * rth_dollar_bn / max(rth_dollar_bn) OVER (), 1) AS pct_of_top_turnover
FROM (
    SELECT ticker,
        (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 AS june_return_pct,
        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 ('MU', 'SNDK', 'WDC', 'INTC', 'NVDA', 'SPY')
      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 june_return_pct DESC
自己运行这个查询

这是一次存储板块行情,而 MU 的表现落后于板块。SNDK上涨了 31.3%,INTC上涨了 27.5%,WDC上涨了 19.1%;每只存储股的表现都比 MU 高出 5.117.3个百分点,而 SPYNVDA六月收跌。MU 的特点是:其成交额在这里每一行中都位居最高。

盘面上成交额最大的代码

查询全美股市按2026年6月常规交易时段成交额排名(一个重复使用的代码因实体待核验而排除)
ticker正常交易时段成交额(十亿美元)占领先者百分比
MU995.7100
SPY771.577.5
QQQ672.867.6
NVDA52352.5
SNDK381.638.3
TSLA342.734.4
MRVL302.730.4
INTC272.427.4
AAPL27027.1
MSFT268.627
每个数字背后的完整 SQL
SELECT ticker,
    round(sum(toFloat64(volume) * toFloat64(close)) / 1e9, 1) AS regular_hours_dollar_bn,
    round(100 * sum(toFloat64(volume) * toFloat64(close)) / max(sum(toFloat64(volume) * toFloat64(close))) 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 regular_hours_dollar_bn DESC
LIMIT 10
自己运行这个查询
查询排名凭证:MU的排名、领先下一名的幅度及依据
MU排名MU成交额(十亿美元)领先第二名(十亿美元)
1995.7224.3
每个数字背后的完整 SQL
WITH (
    SELECT sum(toFloat64(volume) * toFloat64(close))
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MU'
      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
) AS mu_d
SELECT
    countIf(d > mu_d AND ticker != 'MU') + 1 AS mu_rank,
    round(mu_d / 1e9, 1) AS mu_dollar_bn,
    round((mu_d - maxIf(d, d < mu_d AND ticker != 'MU')) / 1e9, 1) AS lead_over_next_bn
FROM (
    SELECT ticker, sum(toFloat64(volume) * toFloat64(close)) AS d
    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
)
自己运行这个查询

按六月常规交易时段的成交额计算,MU在所有美国上市代码中排名第first,成交额为$995.7十亿,比排名第二的SPY高出$224.3十亿。一家公司连续一个月的成交额超过旗舰指数基金,这种盘面结构并不常见;其背景可参见上文的财报周和同业部分。统计口径:六月1日至30日常规交易时段,剔除一个重复使用的代码,待完成实体核验(其成交记录)。全市场视角请参见六月回顾

行情成交由何构成

查询MU全量交易单行概览:成交笔数、单笔规模及报价统计
成交笔数(百万)单笔成交股数中位数单笔成交股数均值零股成交占比碎股成交占比NBBO更新(百万)有效双边报价占比交叉报价更新单边或空报价更新
35.17838.391.79.0419.6499.861696378
每个数字背后的完整 SQL
WITH
    (
        SELECT (round(count() / 1e6, 2),
                round(100.0 * countIf(bid_price > 0 AND ask_price > 0 AND ask_price > bid_price) / count(), 2),
                countIf(bid_price > 0 AND ask_price > 0 AND ask_price < bid_price),
                countIf(bid_price <= 0 OR ask_price <= 0))
        FROM global_markets.cache_stocks_quotes
        WHERE ticker = 'MU'
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
    ) AS quote_census
SELECT
    round(count() / 1e6, 2) AS prints_m,
    quantileDeterministic(0.5)(toFloat64(size), toUInt64(abs(sequence_number))) AS median_print_shares,
    round(avg(toFloat64(size)), 1) AS avg_print_shares,
    round(100.0 * countIf(size < 100) / count(), 1) AS odd_lot_pct_of_prints,
    round(100.0 * countIf(toFloat64(size) != round(toFloat64(size))) / count(), 2) AS fractional_pct_of_prints,
    quote_census.1 AS nbbo_updates_m,
    quote_census.2 AS clean_two_sided_pct,
    quote_census.3 AS crossed_updates,
    quote_census.4 AS one_sided_or_empty_updates
FROM global_markets.stocks_trades
WHERE ticker = 'MU'
  AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
自己运行这个查询

共有 35.17 百万笔成交,每笔成交的中位数为 8 股,另有 91.7% 笔零碎股成交,是我们测量过的最偏向散户分拆的成交记录之一(NVDA 6月的数据明显较低;其深度分析包含双面板)。在股价达到四位数时,“整手”意味着很大的资金规模,因此小额成交占主导是必然结果;零碎股成交(9.04%)也指向同一结论。报价部分包括 19.64 百万次NBBO更新,其中 99.86% 次为有效双边报价,16963 次为交叉报价,78 次为单边报价或无报价;这些数据均已披露,并未被剔除。

重新定价期间的买卖价差

一只在一个季度内接近上涨至原来三倍的股票,会以不同方式引出价差问题:在价格寻找新水平的过程中,买卖报价是否仍然保持紧密?

查询按交易日的价差:常规交易时段中位数(美分和基点)
21 rows (showing 20)
交易时段中位价差(美分)中位价差(基点)报价更新丢弃的无效数据
2026-06-01413.96497073428
2026-06-02403.84482044467
2026-06-03464.31389386341
2026-06-04414.1546741456
2026-06-05414.459462201190
2026-06-08394.08713643406
2026-06-09525.681165907595
2026-06-10475.13905403668
2026-06-11495.3112089022487
2026-06-12525.27532349273
2026-06-15413.81740689450
2026-06-16535.04924925227
2026-06-17524.971195996252
2026-06-18413.651327917617
2026-06-22443.715801441139
2026-06-23454.2940595554
2026-06-245251051175537
2026-06-2557.54.788155321003
2026-06-265851030596412
2026-06-29504.62748086414
每个数字背后的完整 SQL
SELECT session,
    round(quantileDeterministicIf(0.5)(toFloat64(ask_price) - toFloat64(bid_price), toUInt64(toUnixTimestamp64Micro(sip_timestamp)), bid_price > 0 AND ask_price >= bid_price) * 100, 1) AS med_spread_cents,
    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), 2) AS med_spread_bps,
    count() AS quote_updates,
    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 = 'MU'
  AND sip_timestamp >= toDateTime64('2026-06-01 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
  AND (toHour(sip_timestamp) * 60 + toMinute(sip_timestamp)) BETWEEN 810 AND 1199
GROUP BY toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session
ORDER BY session
自己运行这个查询

以基点计算,整个上涨过程中买卖价差始终达到机构级别:3.96个基点(对应2026-06-01),上一交易日为4.19个基点;以美分计的价差大致随股价水平本身变化。关于具体机制,请参阅买卖价差说明

期权:双向持仓

查询MU期权市场单行概览:总量、到期日及看跌/看涨拆分
成交笔数(百万)不同合约数成交合约数(百万)权利金名义金额(十亿美元)月度认沽认购比成交到期日数量最活跃行权价(美元)
4.691178916.7677.130.99231200
每个数字背后的完整 SQL
SELECT
    round(count() / 1e6, 2) AS prints_m,
    uniqExact(ticker) AS distinct_contracts,
    round(sum(size) / 1e6, 2) AS contracts_traded_m,
    round(sum(toFloat64(price) * size) * 100 / 1e9, 2) AS premium_notional_busd,
    round(toFloat64(sumIf(size, substring(ticker, 11, 1) = 'P')) / toFloat64(sumIf(size, substring(ticker, 11, 1) = 'C')), 2) AS month_put_call_ratio,
    uniqExact(substring(ticker, 5, 6)) AS expiries_traded,
    round(intDiv(toUInt32OrZero(substring(argMax(ticker, sz), 12, 8)), 1000), 0) AS busiest_strike_usd
FROM (
    SELECT ticker, price, size, sum(size) OVER (PARTITION BY ticker) AS sz
    FROM global_markets.options_trades
    WHERE startsWith(ticker, 'O:MU') AND length(ticker) = 19
      AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
)
自己运行这个查询

16.76百万张合约,涵盖11789个不同合约,权利金总额为$77.13十亿。持仓呈双向分布:当月看跌/看涨期权比率为0.99,基本处于平价水平(NVDA 6月合约偏向看涨;比较)。在剧烈重新定价期间,期权市场在行情两边都有参与。接近平价只说明市场分布在涨跌两侧,数据反映的是这种分布,而非交易意图。

查询合约分布:按行权价区间统计看涨和看跌成交量
行权价区间看涨期权合约看跌期权合约认沽占比
$0866432910497.4
$100662833021898
$200537211175195.4
$300885520491395.9
$4002505035861793.5
$5002365466979896.6
$6003005994070696.9
$7006779487024292.8
$800209357125782985.7
$9001137271146023656.2
$10001923982107658935.9
$1100167873559600426.2
$120012890971092087.8
$1300601699172282.8
$140033043187072.6
$15001056463189161.8
每个数字背后的完整 SQL
SELECT
    concat('$', toString(toUInt32(bucket))) AS strike_bucket,
    call_contracts,
    put_contracts,
    round(100.0 * put_contracts / (call_contracts + put_contracts), 1) AS put_share_pct
FROM (
    SELECT
        least(floor(toFloat64(toUInt32OrZero(substring(ticker, 12, 8))) / 1000 / 100) * 100, 1500) AS bucket,
        toUInt64(sumIf(size, substring(ticker, 11, 1) = 'C')) AS call_contracts,
        toUInt64(sumIf(size, substring(ticker, 11, 1) = 'P')) AS put_contracts
    FROM global_markets.options_trades
    WHERE startsWith(ticker, 'O:MU') AND length(ticker) = 19
      AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
    GROUP BY bucket
)
ORDER BY toUInt32OrZero(substring(strike_bucket, 2))
自己运行这个查询

行权价分布覆盖了一个在1月看来不可思议的区间。从$0档位到$1500以上的上限,都有实际成交量。这显示了标的价格的移动幅度。持有这段波动需要付出多少成本?当月最后一个交易日给出了答案:

查询月末波动价格:六月最后一个平值跨式组合
最近到期日距到期日自然日数现货收盘价平值行权价跨式期权美元值跨式期权占现货价百分比双边行权价
2026-07-0221151.01115069.956.08135
每个数字背后的完整 SQL
WITH (
    SELECT argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199)
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MU' AND window_start >= toDateTime('2026-06-30 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
) AS spot
SELECT
    toString(any(expiry)) AS nearest_expiry,
    dateDiff('day', toDate('2026-06-30'), any(expiry)) AS calendar_days_to_expiry,
    round(spot, 2) AS spot_close,
    argMin(strike_usd, (dist, strike_usd)) AS atm_strike,
    round(argMin(call_last + put_last, (dist, strike_usd)), 2) AS straddle_usd,
    round(argMin(call_last + put_last, (dist, strike_usd)) / spot * 100, 2) AS straddle_pct_of_spot,
    count() AS two_sided_strikes
FROM (
    SELECT expiry, strike_usd, abs(strike_usd - spot) AS dist,
        anyIf(last_px, opt_type = 'C') AS call_last,
        anyIf(last_px, opt_type = 'P') AS put_last
    FROM (
        SELECT
            toDateOrNull(concat('20', substring(ticker, 5, 2), '-', substring(ticker, 7, 2), '-', substring(ticker, 9, 2))) AS expiry,
            substring(ticker, 11, 1) AS opt_type,
            toFloat64(toUInt32OrZero(substring(ticker, 12, 8))) / 1000 AS strike_usd,
            argMax(toFloat64(price), (sip_timestamp, toFloat64(price))) AS last_px
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:MU') AND length(ticker) = 19
          AND sip_timestamp >= toDateTime64('2026-06-30 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
        GROUP BY expiry, opt_type, strike_usd
    )
    WHERE expiry > toDate('2026-06-30')
    GROUP BY expiry, strike_usd
    HAVING countIf(opt_type = 'C') > 0 AND countIf(opt_type = 'P') > 0
)
WHERE expiry = (
    SELECT min(toDateOrNull(concat('20', substring(ticker, 5, 2), '-', substring(ticker, 7, 2), '-', substring(ticker, 9, 2))))
    FROM global_markets.options_trades
    WHERE startsWith(ticker, 'O:MU') AND length(ticker) = 19
      AND sip_timestamp >= toDateTime64('2026-06-30 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
      AND toDateOrNull(concat('20', substring(ticker, 5, 2), '-', substring(ticker, 7, 2), '-', substring(ticker, 9, 2))) > toDate('2026-06-30')
)
自己运行这个查询

截至6月30日收盘,最近到期日还有2个日历日;以$1150为行权价的平值看涨期权和看跌期权,合计最新成交价为$69.95,相当于$1151.01股价的6.08%。买方需要标的在这2天内向任一方向移动达到这一幅度,才能实现盈亏平衡。6月收盘时,市场对大幅波动的定价仍然很高。

新闻流

查询六月MU相关文章:数量、头部发布商占比及共同标签
6月文章数出版商头部出版商头部出版商占比NVDA相关公司文章数SNDK相关公司文章数INTC相关公司文章数
1954The Motley Fool59863221
每个数字背后的完整 SQL
WITH
    (
        SELECT (JSONExtractString(any(publisher), 'name'), count())
        FROM global_markets.stocks_news
        WHERE has(tickers, 'MU')
          AND published_utc >= toDateTime('2026-06-01 00:00:00') AND published_utc < toDateTime('2026-07-01 04:00:00')
        GROUP BY JSONExtractString(publisher, 'name') ORDER BY count() DESC LIMIT 1
    ) AS top_pub
SELECT
    count() AS june_articles,
    uniqExact(JSONExtractString(publisher, 'name')) AS publishers,
    top_pub.1 AS top_publisher,
    round(100.0 * top_pub.2 / count(), 0) AS top_publisher_pct,
    countIf(has(tickers, 'NVDA')) AS nvda_co_articles,
    countIf(has(tickers, 'SNDK')) AS sndk_co_articles,
    countIf(has(tickers, 'INTC')) AS intc_co_articles
FROM global_markets.stocks_news
WHERE has(tickers, 'MU')
  AND published_utc >= toDateTime('2026-06-01 00:00:00') AND published_utc < toDateTime('2026-07-01 04:00:00')
自己运行这个查询

请批判性地阅读来自 4 家出版商的 195 篇带有 MU 标签的文章;其中 The Motley Fool 家出版商单独撰写了 59% 篇。共同标签勾勒出一条半导体主线:NVDA 出现在 86 篇文章中,SNDK 出现在 32 篇,INTC 出现在 21 篇。文章讨论的是什么?供应商自身的文章标签提供了相关词汇,但并不代表我们采纳这些表述:

查询六月MU报道主题:统计发布商自有文章标签
关键词文章数文章占比
AI infrastructure4925.1
memory chips4322.1
semiconductor stocks3819.5
DRAM2412.3
semiconductor199.7
artificial intelligence189.2
data centers189.2
high-bandwidth memory147.2
Micron Technology136.7
AI chips126.2
每个数字背后的完整 SQL
SELECT keyword, count() AS articles,
    round(100.0 * count() / (SELECT count() FROM global_markets.stocks_news WHERE has(tickers, 'MU') AND published_utc >= toDateTime('2026-06-01 00:00:00') AND published_utc < toDateTime('2026-07-01 04:00:00')), 1) AS pct_of_articles
FROM global_markets.stocks_news
ARRAY JOIN keywords AS keyword
WHERE has(tickers, 'MU')
  AND published_utc >= toDateTime('2026-06-01 00:00:00') AND published_utc < toDateTime('2026-07-01 04:00:00')
GROUP BY keyword
ORDER BY articles DESC, keyword ASC
LIMIT 10
自己运行这个查询

AI infrastructure”在 195 篇文章中有 49 篇位居首位,其后是“memory chips”和“DRAM”,以及“high-bandwidth memory”。这些是人工智能与存储器相关的词汇,本文仅将其作为标签计数呈现,而非据此作出解释。

空头头寸减少,但数据覆盖仍有缺口

查询FINRA场外做空成交量:MU六月覆盖范围及标记做空占比
卖空股数(百万)场外交易卖空占比
2026-06-016.6331.2
2026-06-0210.0647.1
2026-06-038.2945.1
2026-06-0514.841.7
2026-06-087.632.3
2026-06-0914.3641.3
2026-06-119.3134.4
2026-06-128.9445.2
2026-06-156.8337.1
2026-06-176.6328.8
2026-06-187.0731.7
2026-06-22838.8
2026-06-2410.4541.9
2026-06-2517.5546.6
2026-06-2615.4454.7
2026-06-309.3250.9
每个数字背后的完整 SQL
SELECT toString(date) AS d,
    round(toFloat64(any(short_volume)) / 1e6, 2) AS short_shares_m,
    round(100 * toFloat64(any(short_volume)) / toFloat64(any(total_volume)), 1) AS short_pct_of_offexchange
FROM global_markets.stocks_short_volume
WHERE ticker = 'MU' AND date >= toDate('2026-06-01') AND date <= toDate('2026-06-30')
GROUP BY date
ORDER BY date
自己运行这个查询

先说明覆盖情况:MU 6月空头成交量文件仅包含 16 个交易日中的 21 个。除全市场6月29日数据截断外,MU的几行数据也缺失,因此无法计算月度比例。逐日数据行均为实际记录,缺口已披露。

查询六月结算双点:月中和月末空头权益
6月中旬结算额6月中旬卖空股数(百万)月末结算额月末卖空股数(百万)减少股数(百万)月末回补天数
2026-06-1541.592026-06-3031.679.920.53
每个数字背后的完整 SQL
SELECT
    toString(maxIf(settlement_date, settlement_date <= toDate('2026-06-20'))) AS mid_june_settlement,
    round(toFloat64(maxIf(short_interest, settlement_date <= toDate('2026-06-20'))) / 1e6, 2) AS mid_june_shares_short_m,
    toString(maxIf(settlement_date, settlement_date > toDate('2026-06-20'))) AS eom_settlement,
    round(toFloat64(maxIf(short_interest, settlement_date > toDate('2026-06-20'))) / 1e6, 2) AS eom_shares_short_m,
    round((toFloat64(maxIf(short_interest, settlement_date <= toDate('2026-06-20'))) - toFloat64(maxIf(short_interest, settlement_date > toDate('2026-06-20')))) / 1e6, 2) AS decline_m_shares,
    round(toFloat64(maxIf(short_interest, settlement_date > toDate('2026-06-20'))) / toFloat64(maxIf(avg_daily_volume, settlement_date > toDate('2026-06-20'))), 2) AS eom_days_to_cover
FROM global_markets.stocks_short_interest
WHERE ticker = 'MU' AND settlement_date >= toDate('2026-06-01') AND settlement_date <= toDate('2026-06-30')
自己运行这个查询

结算数据完整:在 2026-06-15 结算日,空头股数为 41.59 百万股;到 2026-06-30 降至 31.67 百万股,后半月减少 9.92 百万股。财报发布周包含在这段后半月内。月末空头头寸相当于 0.53 天的平均成交量,对该股票而言规模较小。本页首次发布时,这条记录尚未到账(延迟属于正常情况);上方数字就是该记录到达后的结果。

财报数据背后的基本面

公司自身披露的数据说明了什么?需要注意的是:该数据源滞后于财报日历,最新一行早于六月季度报告(10-Q),因此这里展示的是这段窗口期内的趋势,而不是最新情况。

查询最近六个已披露季度记录:收入、净利润及摊薄每股收益
季度末营收(十亿美元)占峰值营收百分比净利润(十亿美元)摊薄每股收益
2024-08-297.7556.80.890.8
2024-11-288.7163.91.871.67
2025-02-278.05591.581.41
2025-05-299.368.21.881.68
2025-08-2811.32833.22.84
2025-11-2713.641005.244.6
每个数字背后的完整 SQL
SELECT quarter_end, revenue_bn,
    round(100 * revenue_bn / max(revenue_bn) OVER (), 1) AS pct_of_peak_revenue,
    net_income_bn, diluted_eps
FROM (
    SELECT toString(period_end) AS quarter_end,
        round(toFloat64(revenue) / 1e9, 2) AS revenue_bn,
        round(toFloat64(net_income_loss_attributable_common_shareholders) / 1e9, 2) AS net_income_bn,
        round(toFloat64(diluted_earnings_per_share), 2) AS diluted_eps
    FROM global_markets.stocks_income_statements
    WHERE has(tickers, 'MU') AND timeframe = 'quarterly'
    ORDER BY period_end DESC
    LIMIT 6
)
ORDER BY quarter_end ASC
自己运行这个查询

在已收录的六个季度中,营收介于7.75亿美元(2024-08-29)和13.64亿美元(2025-11-27)之间。最新一行处于该窗口期的峰值,当季净利润为5.24亿美元,摊薄每股收益为4.6美元。走势并非直线上升,但该窗口期最终以高点收尾。

接下来关注什么

这里只列出日历事实:下一次空头利息结算将在七月中旬完成,并按照 FINRA 通常的滞后时间发布;截至六月申报的季度数据将在供应商数据源更新后纳入基本面数据行;七月的交易数据将在本系列下一期采用同样方式处理。

常见问题

MU股票为何在2026年6月大幅波动?

本页旨在衡量波动,而非解释原因:MU在$850.1至$1255之间交易;季度8-K日期为2026-06-24,下一交易日成交量创当月最高,股价上涨15.8%;同期整个存储芯片板块走势相同。

MU在2026年6月的波动有多大?

这是其半年内波动最大的月份:年化实现波动率为127.6%,平均单日波动区间为7.6%,但期初至期末回报仅为14%。

MU在6月的走势是公司特有,还是整个板块的走势?

这是整个板块的走势,而MU在上涨个股中表现落后:SNDK上涨31.3%,所有存储芯片股的表现都超过MU的14%;SPY和NVDA则收盘走低。MU的特点在于成交额:995.7十亿美元,为该板块最高。

MU的空头持仓高吗?

相对于自身成交量而言并不高:截至2026-06-30结算日,空头持仓为31.67百万股,约需0.53个平均成交量日才能回补;较6月中旬减少9.92百万股。空头持仓数据总是滞后于结算日公布。

MU的看跌/看涨期权比率意味着什么?

6月该比率为0.99,意味着看跌期权和看涨期权的成交量几乎相等,市场呈双向交易,而不是单边押注。低于一通常表示看涨期权占优(NVDA 6月的情况),显著高于一则表示看跌期权占优。

数据说明

完整数据说明
  • 实体。 MU指美光科技公司(Micron Technology, Inc.),CIK为0000723125,始终使用同一EDGAR实体身份;不存在股票代码重复使用的特殊情况。
  • 卖空成交量覆盖范围。 六月文件涵盖16个交易日中的21个(包括6月29日数据截断以及MU特有的数据缺失);文中仅展示逐日比例。
  • 同业篮子。 包括SNDK、WDC、INTC——它们是6月MU新闻流中最常见的存储行业关联标的——以及作为参照的NVDA和SPY;篮子事先设定,并非事后拼接。
  • 期权解析。 根据OCC代码重新解析到期日、类型和行权价(第5、11、12位);权利金按每张合约100股的乘数计算。
  • 跨式策略方法。 采用最接近期末收盘价的行权价、月末之后最近到期日对应的最新成交价(不是报价)。数据来自成交回执,而非模型隐含波动率。
  • 基本面滞后。 利润表数据源滞后于申报日历;其中最新的MU数据早于6月10-Q申报,仅用于趋势参考。
  • 6月19日休市。 已通过SPY零成交柱记录核实。
  • 价差面板。 排除交叉报价和单边报价,并在对应行披露剔除数量。
  • 包括该股票位列全市场成交记录排行榜首位在内的全市场背景信息,见2026年6月回顾

方法

  • 统计区间为2026年6月1日至6月30日(21个交易时段,已根据观测到的K线核验)。回报率按正常交易时段开盘价至正常交易时段收盘价计算。6月全程采用EDT,因此正常交易时段的原始时间边界为UTC 13:30至20:00。滚动面板按东部时钟筛选,涵盖以EST计的月份。
  • 实现波动率等于每日收盘价至收盘价对数回报的样本标准差,并乘以252的平方根进行年化。每月第一笔回报跨越月度边界,计入后一个月。
  • 滚动比较实时重新计算,从不使用存储值。
  • 生成过程仅通过受控的只读路径批量执行;公开页面从不查询实时数据。数据仓库截至2026年7月12日。

每个面板对应一个存储对象,包括图表、表格和SQL。可在Strasmore终端中进一步运行任意查询。

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