Strasmore Research
Deep Dives · Matt ConnorBy Matt Connor · · Updated 2026-10-17

SPCX: SpaceX股票较峰值下跌了多少

SpaceX股票(SPCX)较2026年6月16日峰值低多少?查看最新收盘价、盘中走势、价差、期权资金流和美国证券交易委员会文件。

SpaceX股票(SPCX)在Oct 15, 2026收于$148.64,这是目前记录中最新的完整交易日;较其于Jun 16, 2026录得的$225.64峰值低34.1%。按每股计算,该股较高点低$77。相较于$150的首个正常交易时段成交价,该股目前-0.9%;相较于此次交易所采用的$135发行价,目前10.1%。同期,标普500 ETF(SPY)变动了2.77%。本文所有数据均为截至目前记录中最新交易日的存储查询结果,并已随每周批处理更新;展开任一面板即可查看确切的 SQL。

SPCX较峰值下跌了多少

记分牌一行完整呈现了这一走势:发行价为 $135,常规交易时段首笔成交价为 $150(2026年6月12日上午11:46进行开盘集合竞价;首月深度解析介绍了上市首日的交易机制),Jun 16, 2026的盘中峰值为 $225.64,最新收盘价为 $148.64。该峰值出现在常规交易时段的上午中段,其形成过程可由相邻K线追溯(数据说明)。跌幅以该峰值成交价至最近一个常规交易时段收盘价计算,因此仓库每新增一个交易日,跌幅都会相应变化。

查询单行走势:发行价、首笔成交价、6月峰值和最新收盘价
发行价IPO开盘价峰值价格峰值标签峰值月份峰值日期最新标签最新收盘价较峰值下跌(美元)较峰值跌幅峰值较IPO开盘价涨幅较首次报价涨跌幅较发行价涨跌幅SPY期间涨跌幅SPY较SPCX差值(百分点)SPCX自峰值交易日以来涨跌幅SPY自峰值交易日以来涨跌幅峰值窗口差值(百分点)
135150225.64Jun 16, 2026616Oct 15, 2026148.647734.150.4-0.910.12.773.7-26.42.829.3
每个数字背后的完整 SQL
WITH
    spcx_sessions AS (
        SELECT
            toDate(toTimeZone(window_start, 'America/New_York')) AS d,
            argMax(toFloat64(close), window_start) AS c,
            max(toFloat64(high)) AS hi
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPCX'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
        GROUP BY d
        HAVING count() >= 150
           -- the newest session counts only once it reaches its last half hour
           AND (d < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                        FROM global_markets.delayed_stocks_minute_aggs
                        WHERE ticker = 'SPCX'
                          AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
                OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
    ),
    latest_row AS (
        SELECT max(d) AS latest_d, argMax(c, d) AS latest_c
        FROM spcx_sessions
    ),
    peak_row AS (
        SELECT max(hi) AS peak_hi, argMax(d, (hi, -toInt32(d))) AS peak_d
        FROM spcx_sessions
    ),
    first_print AS (
        SELECT round(toFloat64(argMin(open, window_start)), 2) AS ipo_open_px
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPCX'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < '2026-06-13 00:00:00'
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    ),
    issue_row AS (
        SELECT toFloat64(final_issue_price) AS issue_px
        FROM global_markets.stocks_ipos
        WHERE ticker = 'SPCX'
        ORDER BY listing_date DESC LIMIT 1
    ),
    spy_ret AS (
        SELECT round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 2) AS spy_pct
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    ),
    spy_sessions AS (
        SELECT
            toDate(toTimeZone(window_start, 'America/New_York')) AS d,
            argMax(toFloat64(close), window_start) AS c
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
        GROUP BY d
        HAVING count() >= 150
           -- the newest session counts only once it reaches its last half hour
           AND (d < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                        FROM global_markets.delayed_stocks_minute_aggs
                        WHERE ticker = 'SPY'
                          AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
                OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
    ),
    peak_window AS (
        SELECT
            anyIf(x.c, x.d = pk.peak_d) AS spcx_peak_close,
            anyIf(y.c, y.d = pk.peak_d) AS spy_peak_close,
            anyIf(y.c, y.d = lt.latest_d) AS spy_latest_close
        FROM spcx_sessions x, spy_sessions y, peak_row pk, latest_row lt
        WHERE x.d = y.d
    )
SELECT
    toString(round(ip.issue_px, 2)) AS issue_price,
    fp.ipo_open_px AS ipo_open,
    round(pk.peak_hi, 2) AS peak_price,
    formatDateTime(pk.peak_d, '%b %e, %Y') AS peak_label,
    toMonth(pk.peak_d) AS peak_month,
    toDayOfMonth(pk.peak_d) AS peak_day,
    formatDateTime(lt.latest_d, '%b %e, %Y') AS latest_label,
    round(lt.latest_c, 2) AS latest_close,
    round(pk.peak_hi - lt.latest_c, 2) AS drop_from_peak_usd,
    round((pk.peak_hi - lt.latest_c) / pk.peak_hi * 100, 1) AS decline_from_peak_pct,
    round((pk.peak_hi - fp.ipo_open_px) / fp.ipo_open_px * 100, 1) AS peak_above_ipo_pct,
    round((lt.latest_c / fp.ipo_open_px - 1) * 100, 1) AS vs_first_print_pct,
    round((lt.latest_c / ip.issue_px - 1) * 100, 1) AS vs_issue_pct,
    sr.spy_pct AS spy_period_pct,
    round(sr.spy_pct - (lt.latest_c / fp.ipo_open_px - 1) * 100, 1) AS spy_minus_spcx_pp,
    round((lt.latest_c / pw.spcx_peak_close - 1) * 100, 1) AS spcx_since_peak_session_pct,
    round((pw.spy_latest_close / pw.spy_peak_close - 1) * 100, 1) AS spy_since_peak_session_pct,
    round((pw.spy_latest_close / pw.spy_peak_close - 1) * 100 - (lt.latest_c / pw.spcx_peak_close - 1) * 100, 1) AS peak_window_gap_pp
FROM peak_row pk, first_print fp, issue_row ip, latest_row lt, spy_ret sr, peak_window pw
自己运行这个查询

逐日交易:持续下行

SPCX自上市以来已完成87个常规交易时段。首个交易时段开盘价为$150,两天后于Jun 16创下$225.64的峰值,并于Oct 15收于$148.64,盘中低点为$140.66。成交量也呈现出不同变化:首日为495.6百万股,峰值所在交易时段为274.5百万股,最近一个交易时段为89.4百万股。该股上市以来首次在常规交易时段收盘价低于首次公开成交价的日期是Jul 7, 2026,对应第16个交易时段;纳斯达克-100指数纳入交易则衡量了此前创下纪录的收盘集合竞价成交。

查询常规交易时段概览:自上市以来每个SPCX交易日的开盘价、收盘价、最低价、最高价和成交量
87 rows (showing 20)
交易日交易日标签常规时段开盘价常规时段收盘价常规时段最低价常规时段最高价成交量(百万)
2026-06-12Jun 12150161.29149.34176.52495.6
2026-06-15Jun 15171.74192.42168.35193219.6
2026-06-16Jun 16200.51201.99195.13225.64274.5
2026-06-17Jun 17209.84192.2187.01213.8179.3
2026-06-18Jun 18188.39184.97172.11190189.3
2026-06-22Jun 22176.04154.59154176.75150.7
2026-06-23Jun 23151.06156.06147.11165.5132.1
2026-06-24Jun 24154.2154.46150.72159.8665
2026-06-25Jun 25156.62153.01150160.6552.4
2026-06-26Jun 26150.62152.74148.51158.466.6
2026-06-29Jun 29157.35164151.74166.1767.9
2026-06-30Jun 30163.38170.72161.64172.471.4
2026-07-01Jul 1171.56157.69155171.7489.8
2026-07-02Jul 2159.72161.86155.88162.1650.7
2026-07-06Jul 6165.95160.4155.04167.975.8
2026-07-07Jul 7158.92149.58148.86159.366.2
2026-07-08Jul 8152.55148.33145.2152.9352.3
2026-07-09Jul 9150.44152.12147.59153.539.8
2026-07-10Jul 10150.12145.4145.07150.5738.8
2026-07-13Jul 13144.7139.19136.78144.9265.2
每个数字背后的完整 SQL
SELECT
    toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
    formatDateTime(toDate(toTimeZone(window_start, 'America/New_York')), '%b %e') AS session_label,
    round(toFloat64(argMin(open, window_start)), 2) AS rth_open,
    round(toFloat64(argMax(close, window_start)), 2) AS rth_close,
    round(toFloat64(min(low)), 2) AS rth_low,
    round(toFloat64(max(high)), 2) AS rth_high,
    round(toFloat64(sum(volume)) / 1e6, 1) AS vol_m
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPCX'
  AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
  AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY session_date, session_label
HAVING count() >= 150
   -- the newest session counts only once it reaches its last half hour
   AND (session_date < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                FROM global_markets.delayed_stocks_minute_aggs
                WHERE ticker = 'SPCX'
                  AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                  AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
        OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
ORDER BY session_date
自己运行这个查询

最新交易时段

下方图表按时间段展示最近一个完整交易时段的走势,从开盘钟声一直到收盘。开盘半小时成交量为 24.73 百万股,股价报收于 $141.46。收盘半小时成交量为 6.39 百万股,收于 $148.64;本时段最低价为 $140.66。

查询最新完整交易日的半小时走势:收盘价、最低价和成交量
美东时间收盘价低端区间成交量(百万)
09:30141.46140.6624.73
10:00145.13141.2513.59
10:30147.36144.757.86
11:00148.47146.996.94
11:30146.56146.265.45
12:00145.24145.213.71
12:30146.36145.112.82
13:00146.78145.972.78
13:30146.73145.954.18
14:00146.46146.052.56
14:30147.39146.462.94
15:00148.27147.375.42
15:30148.64147.66.39
每个数字背后的完整 SQL
WITH latest_session AS (
    SELECT max(d) AS latest_d
    FROM (
        SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPCX'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
        GROUP BY d
        HAVING count() >= 150
           -- the newest session counts only once it reaches its last half hour
           AND (d < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                        FROM global_markets.delayed_stocks_minute_aggs
                        WHERE ticker = 'SPCX'
                          AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
                OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
    )
)
SELECT
    formatDateTime(toTimeZone(toStartOfInterval(window_start, INTERVAL 30 MINUTE), 'America/New_York'), '%H:%i') AS et_time,
    round(toFloat64(argMax(close, window_start)), 2) AS close_px,
    round(toFloat64(min(low)), 2) AS bucket_low,
    round(toFloat64(sum(volume)) / 1e6, 2) AS vol_m
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPCX'
  AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
  AND toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT latest_d FROM latest_session)
  AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY et_time
ORDER BY et_time
自己运行这个查询

买卖价差、上市首周与当前情况

买卖价差是每笔可成交订单都要支付的隐性成本。在上市首日,买卖价差平均为中间价的 10.74 个基点;在交易最活跃的交易日,平均为 7.14 个基点;在 Oct 15,平均为 3.13 个基点。最优报价档位的平均深度在首个交易日为 9506 股,而样本中最近一个交易日为 394 股。报价数据取自两个时间窗口:上市后的四周和最近三周。因此,这项比较的成本足够低,可以每周重新运行。

查询按交易日统计的股票报价价差和盘口深度:上市后四周及最近三周
33 rows (showing 20)
交易日交易日标签平均价差(基点)平均深度已剔除无效项
2026-06-12Jun 1210.74950624988
2026-06-15Jun 155.1923678411
2026-06-16Jun 167.1414787679
2026-06-17Jun 17810794348
2026-06-18Jun 183.9786110114
2026-06-22Jun 222.5355303898
2026-06-23Jun 233.4446574050
2026-06-24Jun 246.552411970
2026-06-25Jun 255.632401335
2026-06-26Jun 264.348252960
2026-06-29Jun 294.543312280
2026-06-30Jun 304.413201227
2026-07-01Jul 13.423123839
2026-07-02Jul 24.53191411
2026-07-06Jul 63.823842449
2026-07-07Jul 74.1832653394
2026-07-08Jul 84.814562013
2026-07-09Jul 94.723281485
2026-07-10Jul 103.66853692
2026-09-28Sep 281.893396247
每个数字背后的完整 SQL
SELECT
    toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session_date,
    formatDateTime(toDate(toTimeZone(sip_timestamp, 'America/New_York')), '%b %e') AS session_label,
    round(avgIf((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price > bid_price), 2) AS avg_spread_bps,
    round(avgIf((toFloat64(ask_size) + toFloat64(bid_size)) / 2, bid_price > 0 AND ask_price > bid_price), 0) AS avg_depth,
    countIf(NOT (bid_price > 0 AND ask_price > bid_price)) AS dropped_invalid
FROM global_markets.cache_stocks_quotes
WHERE ticker = 'SPCX'
  AND sip_timestamp < now()
  AND ((sip_timestamp >= '2026-06-12 00:00:00' AND sip_timestamp < '2026-07-11 00:00:00')
       OR sip_timestamp >= now() - INTERVAL 21 DAY)
  AND (toHour(toTimeZone(sip_timestamp, 'America/New_York')) * 60 + toMinute(toTimeZone(sip_timestamp, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY session_date, session_label
HAVING countIf(bid_price > 0 AND ask_price > bid_price) > 0
ORDER BY session_date
自己运行这个查询

期权:当前的交易情况

在有 SPCX 期权成交记录的最新交易日 Oct 16, 2026,成交最活跃的合约是将于 Oct 16, 2026 到期、成交量为 53230 张的 145-strike put,其次是成交量为 41815 张的 147-strike call。SPCX 提供每周和每月到期合约,而不是每日到期合约,因此大多数交易日都没有当日到期的 0DTE 合约。过去三周内,认沽/认购成交量比在 Sep 28 为 0.64,在 Oct 16 为 0.9。单日成交量最高的合约并不能单独确定期权持有人在到期时收益最低的行权价;这正是最大痛点所衡量的指标。最大痛点的计算会读取整个期权链的未平仓合约,而不是单个交易日的成交记录。

查询最新有记录交易日:按成交量计最活跃的SPCX期权合约
标签到期日标签交易日标签成交量名义金额(百万)
145-strike putOct 16, 2026Oct 16, 2026532300.05
147-strike callOct 16, 2026Oct 16, 2026418150.03
150-strike callOct 16, 2026Oct 16, 2026407110.01
145-strike callOct 16, 2026Oct 16, 2026356490.04
146-strike callOct 16, 2026Oct 16, 2026332930.03
120-strike putOct 19, 2026Oct 16, 2026306130
146-strike putOct 16, 2026Oct 16, 2026278690.03
148-strike callOct 16, 2026Oct 16, 2026233530.01
144-strike putOct 16, 2026Oct 16, 2026201020.01
142-strike putOct 16, 2026Oct 16, 2026187600
每个数字背后的完整 SQL
WITH latest_opt_session AS (
    SELECT max(toDate(toTimeZone(sip_timestamp, 'America/New_York'))) AS d
    FROM global_markets.options_trades
    WHERE ticker LIKE 'O:SPCX%'
      AND length(ticker) = 21
      AND sip_timestamp >= now() - INTERVAL 8 DAY AND sip_timestamp < now()
)
SELECT
    concat(toString(toUInt32OrZero(substring(ticker, 14, 8)) / 1000), '-strike ', if(substring(ticker, 13, 1) = 'C', 'call', 'put')) AS label,
    formatDateTime(toDate(concat('20', substring(ticker, 7, 2), '-', substring(ticker, 9, 2), '-', substring(ticker, 11, 2))), '%b %e, %Y') AS expiry_label,
    formatDateTime(max(toDate(toTimeZone(sip_timestamp, 'America/New_York'))), '%b %e, %Y') AS session_label,
    sum(size) AS volume,
    round(sum(toFloat64(size) * toFloat64(price)) / 1e6, 2) AS notional_m
FROM global_markets.options_trades
WHERE ticker LIKE 'O:SPCX%'
  AND length(ticker) = 21
  AND sip_timestamp >= now() - INTERVAL 8 DAY AND sip_timestamp < now()
  AND toDate(toTimeZone(sip_timestamp, 'America/New_York')) = (SELECT d FROM latest_opt_session)
GROUP BY label, expiry_label
ORDER BY volume DESC
LIMIT 10
自己运行这个查询
查询按交易日统计的看跌/看涨成交量比率,最近三周
交易日交易日标签认沽认购比认购量认沽量
2026-09-28Sep 280.64367289235809
2026-09-29Sep 290.52475801247958
2026-09-30Sep 300.62438347270427
2026-10-01Oct 10.66455750300312
2026-10-02Oct 20.81938299762034
2026-10-05Oct 50.621044687646917
2026-10-06Oct 60.73653328479866
2026-10-07Oct 70.85584405497058
2026-10-08Oct 80.99531400525781
2026-10-09Oct 90.59877288513379
2026-10-12Oct 120.53647832341399
2026-10-13Oct 130.54640269345626
2026-10-14Oct 140.71604790429970
2026-10-15Oct 150.8701857562244
2026-10-16Oct 160.9698656630590
每个数字背后的完整 SQL
SELECT
    toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session_date,
    formatDateTime(toDate(toTimeZone(sip_timestamp, 'America/New_York')), '%b %e') AS session_label,
    round(sumIf(size, substring(ticker, 13, 1) = 'P') / sumIf(size, substring(ticker, 13, 1) = 'C'), 2) AS pc_ratio,
    sumIf(size, substring(ticker, 13, 1) = 'C') AS call_vol,
    sumIf(size, substring(ticker, 13, 1) = 'P') AS put_vol
FROM global_markets.options_trades
WHERE ticker LIKE 'O:SPCX%'
  AND length(ticker) = 21
  AND sip_timestamp >= now() - INTERVAL 21 DAY AND sip_timestamp < now()
GROUP BY session_date, session_label
HAVING sumIf(size, substring(ticker, 13, 1) = 'C') > 0
ORDER BY session_date
自己运行这个查询

期权报价仍然较宽

该股票的最优买卖价与其期权链并非采用同一报价尺度。SPCX合约的平均报价价差在1500.54个基点,在Oct 12的交易日为1831.35个基点,在Oct 16的交易日为3.13个基点;相比之下,该股自身最近交易日的价差为209个基点。上述两个交易日中,最优报价处的平均挂单量分别为211张和211张。本面板有意落后于股票面板:cache_options_quotes的数据接入延迟在仓库中最长,因此其最近交易日比市场成交数据晚一到两天。

查询期权买卖价差及最优价位挂单量:过去一周半的有记录交易日
交易日交易日标签期权价差(基点)平均规模已剔除无效项报价数
2026-10-12Oct 121500.542091426593359002
2026-10-13Oct 131585.01210929195434948
2026-10-14Oct 141925.5623511585103435679
2026-10-15Oct 151902.2722922234121734295
2026-10-16Oct 161831.3521111946121519218
每个数字背后的完整 SQL
SELECT
    toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session_date,
    formatDateTime(toDate(toTimeZone(sip_timestamp, 'America/New_York')), '%b %e') AS session_label,
    round(avgIf((toFloat64(ask_price) - toFloat64(bid_price)) / ((toFloat64(ask_price) + toFloat64(bid_price)) / 2) * 10000, bid_price > 0 AND ask_price > bid_price), 2) AS opt_spread_bps,
    round(avgIf((toFloat64(ask_size) + toFloat64(bid_size)) / 2, bid_price > 0 AND ask_price > bid_price), 0) AS avg_size,
    countIf(NOT (bid_price > 0 AND ask_price > bid_price)) AS dropped_invalid,
    count() AS quotes
FROM global_markets.cache_options_quotes
WHERE ticker LIKE 'O:SPCX%'
  AND sip_timestamp >= now() - INTERVAL 8 DAY AND sip_timestamp < now()
  AND (toHour(toTimeZone(sip_timestamp, 'America/New_York')) * 60 + toMinute(toTimeZone(sip_timestamp, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY session_date, session_label
HAVING countIf(bid_price > 0 AND ask_price > bid_price) > 0
ORDER BY session_date
自己运行这个查询

SPCX与市场表现对比

跌幅是从峰值开始计算的,因此市场对比也从这一点开始。从Jun 16, 2026峰值交易日收盘到最新收盘,SPCX变动了-26.4%,SPY变动了2.8%,两者相差29.3个百分点。若从上市时点开始计算,SPY变动了2.77%,SPCX自首次公开交易以来变动了-0.9%。这一时间区间既包括上涨至峰值的阶段,也包括随后出现的下跌。下方图表按交易日展示相同的测算结果:在Oct 15,SPY开盘至收盘变动了0.72%,SPCX变动了1.18%。

查询SPY与SPCX的开盘至收盘表现,常规交易时段,最近三周
交易日交易日标签SPY涨跌幅SPCX百分比
2026-09-28Sep 28-0.36-2.02
2026-09-29Sep 29-0.341.77
2026-09-30Sep 30-0.521.52
2026-10-01Oct 1-0.04-1.63
2026-10-02Oct 2-0.126.29
2026-10-05Oct 50.687.61
2026-10-06Oct 60.13-0.01
2026-10-07Oct 70.18-0.28
2026-10-08Oct 8-0.13-4.08
2026-10-09Oct 90.3-1.66
2026-10-12Oct 12-0.09-0.72
2026-10-13Oct 130.09-3.33
2026-10-14Oct 14-0.68-1.75
2026-10-15Oct 150.721.18
每个数字背后的完整 SQL
SELECT
    a.session_date AS session_date,
    a.session_label AS session_label,
    round(a.spy_pct, 2) AS spy_pct,
    round(b.spcx_pct, 2) AS spcx_pct
FROM (
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
        formatDateTime(toDate(toTimeZone(window_start, 'America/New_York')), '%b %e') AS session_label,
        (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS spy_pct
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= now() - INTERVAL 21 DAY AND window_start < now()
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY session_date, session_label
    HAVING count() >= 150
       -- the newest session counts only once it reaches its last half hour
       AND (session_date < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                    FROM global_markets.delayed_stocks_minute_aggs
                    WHERE ticker = 'SPY'
                      AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
            OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
) a
INNER JOIN (
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
        (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS spcx_pct
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPCX'
      AND window_start >= '2026-06-12 00:00:00'
      AND window_start >= now() - INTERVAL 21 DAY AND window_start < now()
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY session_date
    HAVING count() >= 150
       -- the newest session counts only once it reaches its last half hour
       AND (session_date < (SELECT max(toDate(toTimeZone(window_start, 'America/New_York')))
                    FROM global_markets.delayed_stocks_minute_aggs
                    WHERE ticker = 'SPCX'
                      AND window_start >= now() - INTERVAL 10 DAY AND window_start < now()
                      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
            OR max((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')))) >= 930)
) b ON a.session_date = b.session_date
ORDER BY a.session_date
自己运行这个查询

新闻资讯流显示的内容

头条数量是可以统计的。从上市日至最新数据,供应商资讯流共收录 808 篇带有 SPCX 标签的文章,来自 5 家出版商。其中,仅 The Motley Fool 家出版商就撰写了 82.4% 篇。报道最密集的一天是上市日,即 6 月 12 日,共有 42 篇文章;6 月 16 日这一波段高点当天有 31 篇。此后没有任何一天的文章数接近上市日,差距少于 13 篇。上市当周日均发布 25.7 篇文章。最近一周则为 3.9 篇。另有 157 篇文章同时标注 Tesla;34 篇的标题中包含“Nasdaq”。在这轮下跌过程中,没有出现任何报道占主导的单日。

查询从上市日到最新读数的新闻流关注度:数量、集中度及最近一周
文章总数发布方数量头部发布方头部发布方占比最繁忙月份最繁忙日期IPO日文章数峰值时段文章数峰值后单日最大数IPO日减峰值后最大数首周平均数最近7日平均数TSLA共同标记数标题含NASDAQ数
8085The Motley Fool82.46124231291325.73.915734
每个数字背后的完整 SQL
WITH daily_counts AS (
    SELECT toDate(toTimeZone(published_utc, 'America/New_York')) AS d, count() AS n
    FROM global_markets.stocks_news
    WHERE has(tickers, 'SPCX')
      AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
    GROUP BY d
),
top_pub AS (
    SELECT JSONExtractString(publisher, 'name') AS p, count() AS n
    FROM global_markets.stocks_news
    WHERE has(tickers, 'SPCX')
      AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
    GROUP BY p ORDER BY n DESC, p ASC LIMIT 1
)
SELECT
    count() AS total_articles,
    uniqExact(JSONExtractString(publisher, 'name')) AS publishers,
    (SELECT p FROM top_pub) AS top_publisher,
    round(100.0 * (SELECT n FROM top_pub) / count(), 1) AS top_publisher_share_pct,
    (SELECT toMonth(argMax(d, (n, -toInt32(toDayOfYear(d))))) FROM daily_counts) AS busiest_month,
    (SELECT toDayOfMonth(argMax(d, (n, -toInt32(toDayOfYear(d))))) FROM daily_counts) AS busiest_dom,
    countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-12')) AS ipo_day_articles,
    countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-16')) AS peak_session_articles,
    (SELECT max(n) FROM daily_counts WHERE d > toDate('2026-06-16')) AS max_daily_after_peak,
    countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-06-12')) - (SELECT max(n) FROM daily_counts WHERE d > toDate('2026-06-16')) AS ipo_day_minus_max_after,
    (SELECT round(sum(n) / 7, 1) FROM daily_counts WHERE d <= toDate('2026-06-18')) AS first_week_avg,
    (SELECT round(sum(n) / 7, 1) FROM daily_counts WHERE d > today() - 7) AS last7_avg,
    countIf(has(tickers, 'TSLA')) AS tsla_co_tagged,
    countIf(positionCaseInsensitive(title, 'nasdaq') > 0) AS nasdaq_titled
FROM global_markets.stocks_news
WHERE has(tickers, 'SPCX')
  AND published_utc >= toDateTime('2026-06-12 04:00:00') AND published_utc < now()
自己运行这个查询

内幕申报与 EDGAR 记录

表格4是公司内部人士买卖公司股票后,须在两个工作日内提交的文件。从6月12日的挂牌记录到最新数据,EDGAR申报索引显示,SPCX共有23份申报文件:8份8-K当前报告、1份表格3初始持股声明、3份表格4,以及11份其他文件。最早的表格4日期为Jun 17, 2026,即股价见顶后的第二个日历日。该索引记录文件类型和日期,但不包含交易方向或规模。自股价见顶以来,记录中共有19份任何类型的申报文件;最新一份日期为Sep 30, 2026,距本次数据读取已有17天。

查询EDGAR索引中自6月12日上市以来的每份SPCX申报文件,逐行列示
申报总数Form 4申报数Form 3申报数8-K申报数其他申报数首次Form 4标签首次Form 4月份首次Form 4日期最后申报标签距上次申报天数峰值以来申报次数
2331811Jun 17, 2026617Sep 30, 20261719
每个数字背后的完整 SQL
SELECT
    count() AS total_filings,
    countIf(form_type = '4') AS form4_filings,
    countIf(form_type = '3') AS form3_filings,
    countIf(form_type = '8-K') AS eightk_filings,
    countIf(form_type NOT IN ('4', '3', '8-K')) AS other_filings,
    formatDateTime(minIf(filing_date, form_type = '4'), '%b %e, %Y') AS first_form4_label,
    toMonth(minIf(filing_date, form_type = '4')) AS first_form4_month,
    toDayOfMonth(minIf(filing_date, form_type = '4')) AS first_form4_dom,
    formatDateTime(max(filing_date), '%b %e, %Y') AS last_filing_label,
    toInt32(today() - max(filing_date)) AS days_since_last_filing,
    countIf(filing_date > toDate('2026-06-16')) AS filings_since_peak
FROM global_markets.stocks_sec_edgar_index
WHERE ticker = 'SPCX'
  AND filing_date >= toDate('2026-06-12') AND filing_date <= today()
自己运行这个查询

IPO交易通常多久会完成往返?

SPCX用了16个交易日,收盘价才首次低于上市首笔成交价。下方图表采用相同方法,分析近期四宗备受关注的美国IPO:CoreWeave、Klarna、Medline和Cerebras。我们先取每只股票在正常交易时段的首笔成交价,再统计其正常交易时段收盘价首次低于该价格前经过的交易日数量,观察期为各股票上市后的前26个日历日。Klarna开盘价较发行价高30%,并在上市首个交易日收盘时跌破首笔成交价;Cerebras开盘价较发行价高89.2%,同样在首个交易日跌破;CoreWeave开盘价较发行价低2.5%,并在第2个交易日跌破。Medline在其16个交易日的观察窗口内始终未跌破。SPCX是四只发生跌破的股票中持有时间最长的,期间的50.4%绕行走势也使其情况与众不同。《2026年上半年IPO市场回顾》汇总了全市场上市后表现数据。

查询从上市到首次收盘价低于首笔成交价的交易日:SPCX与四只近期IPO对比
股票代码已上市发行价首个常规交易时段开盘价开盘价较发行价 (%)开盘价较发行价绝对值 (%)窗口内交易时段数收盘低于首笔成交价首次突破突破标签突破交易时段序号
CRWV2025-03-284039-2.52.51732Mar 31, 20252
KLAR2025-09-104052303018181Sep 10, 20251
MDLN2025-12-17293520.720.7160never in windownever in window0
CBRS2026-05-1418535089.289.217171May 14, 20261
SPCX2026-06-1213515011.111.116116Jul 7, 202616
每个数字背后的完整 SQL
WITH daily AS (
    SELECT ticker,
        toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
        argMin(toFloat64(open), window_start) AS rth_open,
        argMax(toFloat64(close), window_start) AS rth_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((ticker = 'CRWV' AND window_start >= '2025-03-28 00:00:00' AND window_start < '2025-04-23 00:00:00')
        OR (ticker = 'KLAR' AND window_start >= '2025-09-10 00:00:00' AND window_start < '2025-10-06 00:00:00')
        OR (ticker = 'MDLN' AND window_start >= '2025-12-17 00:00:00' AND window_start < '2026-01-12 00:00:00')
        OR (ticker = 'CBRS' AND window_start >= '2026-05-14 00:00:00' AND window_start < '2026-06-09 00:00:00')
        OR (ticker = 'SPCX' AND window_start >= '2026-06-12 00:00:00' AND window_start < '2026-07-08 00:00:00'))
      AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
    GROUP BY ticker, session_date
),
w AS (
    SELECT ticker, session_date, rth_close,
        row_number() OVER (PARTITION BY ticker ORDER BY session_date) AS rn,
        first_value(rth_open) OVER (PARTITION BY ticker ORDER BY session_date) AS d1_open
    FROM daily
),
agg AS (
    SELECT ticker,
        min(session_date) AS first_session,
        any(d1_open) AS day1_open,
        count() AS sessions_in_window,
        countIf(rth_close < d1_open) AS closes_below,
        minIf(toInt32(rn), rth_close < d1_open) AS break_rn,
        minIf(session_date, rth_close < d1_open) AS break_d
    FROM w GROUP BY ticker
)
SELECT a.ticker AS ticker,
    toString(a.first_session) AS listed,
    round(l.issue_px, 2) AS issue_price,
    round(a.day1_open, 2) AS first_rth_open,
    round((a.day1_open / l.issue_px - 1) * 100, 1) AS open_vs_issue_pct,
    round(abs((a.day1_open / l.issue_px - 1) * 100), 1) AS open_vs_issue_pct_abs,
    a.sessions_in_window AS sessions_in_window,
    a.closes_below AS closes_below_first_print,
    if(a.closes_below > 0, toString(a.break_rn), 'never in window') AS first_break,
    if(a.closes_below > 0, formatDateTime(a.break_d, '%b %e, %Y'), 'never in window') AS break_label,
    a.break_rn AS break_session_n
FROM agg a
INNER JOIN (
    SELECT ticker, min(listing_date) AS ld, argMin(toFloat64(final_issue_price), listing_date) AS issue_px
    FROM global_markets.stocks_ipos
    WHERE ticker IN ('SPCX', 'CBRS', 'MDLN', 'CRWV', 'KLAR') AND listing_date >= '2025-01-01' AND ipo_status = 'history'
    GROUP BY ticker
) l ON a.ticker = l.ticker
ORDER BY a.first_session
自己运行这个查询

常见问题

SpaceX股价较峰值下跌了多少?

SPCX在Jun 16, 2026达到峰值225.64,并于Oct 15, 2026收于148.64。从峰值成交价到该收盘价,跌幅为34.1%,即每股下跌77。本页每周都会将这一差距重新计算至最近一个完整交易日。

SPCX的交易价格低于IPO价格吗?

按最近收盘价计算,SPCX相较于首个正常交易时段成交价150的-0.9%,相较于发行价135的10.1%。首次正常交易时段收盘价低于首笔成交价的日期是Jul 7, 2026。盘中低于该水平的成交更早出现,分别是在上市首日(6月12日盘中低点为149.34)以及Jun 23(交易日低点为147.11)。

SPCX的下跌是全市场走势吗?

不是。从Jun 16, 2026峰值交易日收盘到最近收盘,SPCX变动了-26.4%,而SPY变动了2.8%,两者相差29.3个百分点。逐个交易日来看,在Oct 15,SPY开盘至收盘变动0.72%,SPCX变动1.18%。

SpaceX内部人士在股价下跌期间卖出股票了吗?

SEC申报索引显示,自6月12日上市以来,共有3份SPCX Form 4申报,最早日期为Jun 17, 2026。该索引不提供交易方向,因此无法据此判断这些申报代表买入还是卖出。自峰值以来,记录中共有19份任何类型的SPCX申报。

IPO股票通常能在首个交易价格上方维持多久?

通常不会太久。按照相同口径比较四宗备受关注的2025—26年上市交易,Klarna和Cerebras在上市首个交易日收盘时已低于首个正常交易时段成交价,CoreWeave则在第2个交易日跌破该水平;SPCX维持到第16个交易日,Medline在最初16个交易日内尚未跌破该水平。

数据说明

  • 实体核验(复用代码):此前,SPCX代码指向另一家无关公司,其交易记录延续至2026年4月;因此,2026年6月12日上市前的任何数据均不归属于SpaceX,本页面所有面板的数据起点也均设为该日期。记分板中的发行价记录对应stocks_ipos条目(Space Exploration Technologies Corp.,于2026-06-12上市);首月深度分析载有完整的核验记录。
  • “最新完整交易时段”是指最近一个纽约交易时段,且该时段至少包含150根正常交易时段的分钟K线。这一定义允许纳入按计划缩短的交易时段,并排除尚未完整录入的交易日。数据仓库通常比实时行情滞后约一个交易时段,因此最新读数通常对应前一交易时段。
  • 峰值已通过孤立成交核验:峰值交易日的最高价连续两分钟出现(纽约时间上午10:02至10:03),相邻K线的价格相差约两美元以内。这是经过追踪确认的极值,而非孤立成交。若出现新高,将突破本页面设定的峰值日期界限,并进入复核流程。
  • 报价面板排除单边报价、交叉报价或锁定报价记录,并在同一面板的dropped_invalid列中统计剔除数量。股票报价面板采用两个时间窗口(自上市起的四周,以及最近三周),因此页面持续更新时,扫描成本仍保持稳定。
  • 成交量仅统计正常交易时段的分钟K线总和;盘前及盘后成交,包括首月文章提到的6月23日盘前低点,均不计入本页面的任何面板。
  • 新闻数量来自一家供应商的资讯源,并按纽约日历日归类;The Motley Fool撰写了82.4%篇带标签的文章,因此该数量衡量的是资讯源关注度,而非新闻重要性。
  • EDGAR索引仅包含表格类型、日期和URL。本文不对任何Form 4的交易方向作出判断。
  • 往返比较扫描每只股票上市后的前26个日历日,并固定使用明确的日期字面值,因此日后仍可复现;“窗口内从未出现”即确切表示该情况。

方法论

  • 这是一个滚动更新的页面。每个当前状态面板均以执行时点为界,并在每周批处理时重新测算;页面还会标注“数据截至”时间。历史比较面板使用明确的日期字面量,因此日后任何时间运行都能复现相同数据。
  • 时间戳以 UTC 存储,并在查询中转换为纽约时间;常规交易时段按美东时间筛选,即分钟级K线的上午 9:30 至下午 3:59,因此时间窗口在夏令时切换前后均保持正确。“收盘价”指常规交易时段最后一分钟的K线价格;价格来自延迟的综合行情视图。
  • 比率计算前,十进制列会转换为 64 位浮点数。期权到期日、类型和行权价均从 OCC ticker 中解析;对于这一四字符根代码,解析位置为第 7、13 和 14 位;length(ticker) = 21会精确限定根代码,因此不会混入外观相似的根代码。

本文是 SPCX 系列的第三篇,前两篇分别是首月深度分析和纳斯达克100指数纳入交易。所有数据均来自已存储的查询,请在 Strasmore 终端自行运行 SQL。