Strasmore Research
市場回顧 Matt Connor作者： Matt Connor · 更新於 2026-07-25

2026年7月1日市場回顧

記憶體族群單日市值蒸發一成，META逆勢大漲，多數標普類股仍收紅，指數平靜掩蓋劇烈分歧。

2026年7月1日，週三——下半年的第一個交易日——將本月最平靜的指數日之一，疊加在最劇烈的個股表現之上。SPY收盤-0.08%，QQQ收盤-1.44%，然而推動第2季行情的記憶體族群卻跌掉一成市值，META大漲8.88%，而11檔標普類股基金中仍有7收紅。前一交易日：6月30日。

記分板

變動比較的是7月1日最後一根正常交易時段K線，對照6月30日（週二）。

查詢SPY / QQQ / DIA / IWM — 7月1日與6月30日收盤比較，正常交易時段
每個數據背後的精確 SQL 語法
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 >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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

分歧本身就是重點：DIA 0.02% 與 SPY -0.08% 持平，對比 QQQ 的 -1.44% 與 IWM 的 -0.37% —— 一場成長股拋售，但大盤幾乎無感。

過去一個月內最平靜的指數交易日之一

查詢SPY 開盤至收盤走勢在過去一個月交易日中的排名（排名1 = 絕對波動最大）
每個數據背後的精確 SQL 語法
SELECT round(anyIf(oc_pct, d = toDate('2026-07-01')), 2) AS day_move_pct,
       arrayCount(x -> x > abs(anyIf(oc_pct, d = toDate('2026-07-01'))), groupArrayIf(abs(oc_pct), d != toDate('2026-07-01'))) + 1 AS abs_move_rank,
       count() AS sessions_compared,
       toString(min(d)) AS first_session
FROM (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS oc_pct
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-06-01 00:00:00')
      AND window_start < toDateTime('2026-07-02 00:00:00')
      AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
    GROUP BY d
)

以盤中開盤到收盤的走勢來看——有別於收盤價對收盤價的計分板——SPY 變動了 0.09%：在過去 22 個交易日中，絕對波動幅度排名第 20，只有兩個交易日波動更小。波動率相關商品也印證了這一點。此處並未提供現貨 VIX 指數，因此我們以掛牌交易的 VIX 期貨基金作為檢視依據——這是對避險成本最接近的可交易解讀：

查詢7月1日波動率組合：VIX期貨ETF與週二收盤比較，以SPY為基準
每個數據背後的精確 SQL 語法
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'SVXY', 'UVXY', 'VIXY', 'VXX')
      AND ((window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
        OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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 / day_low - 1) * 100, 2) AS range_pct
FROM per_name
ORDER BY ticker

規模最大的近月 VIX 期貨基金 VXX 上漲 0.72%；VIXY 上漲 0.8%；槓桿型 UVXY 在 3.68% 的區間內波動 1.13%；反向型 SVXY 則變動 -0.42%。與個股的波動相比，這些都只是零頭。

廣度：下跌家數多於上漲 — 但創新高家數多於創新低

查詢7月1日成交額逾百萬美元之個股，上漲、下跌家數及季度新高與新低數
每個數據背後的精確 SQL 語法
WITH per_ticker AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start < '2026-07-01 00:00:00') AS quarter_high,
        minIf(toFloat64(low), window_start < '2026-07-01 00:00:00') AS quarter_low,
        maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low,
        sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 00:00:00') AS day_dollar_volume,
        countIf(window_start < '2026-07-01 00:00:00') AS quarter_bars
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= '2026-04-01 13:30:00' AND window_start < '2026-06-30 20:00:00')
        OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00'))
      AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
    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,
    round(100.0 * countIf(day_close > prior_close AND day_dollar_volume >= 1000000)
        / countIf(day_dollar_volume >= 1000000), 1) AS advancer_pct,
    countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_high > quarter_high) AS new_quarter_highs,
    countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_low < quarter_low) AS new_quarter_lows,
    round(countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_high > quarter_high)
        / countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000 AND day_low < quarter_low), 1) AS highs_per_low,
    countIf(day_dollar_volume >= 1000000 AND quarter_bars >= 1000) AS names_with_a_full_quarter,
    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,
    countIf(day_dollar_volume >= 1000000 AND quarter_bars < 1000) AS dropped_short_quarter_history
FROM per_ticker
WHERE prior_close > 0 AND day_close > 0

上漲 2928 家，下跌 3465 家，持平 82 家 — 具流動性的股票中有 45.2% 收漲。但涵蓋範圍不等於跌幅輕重：相對於第2季的常規交易時段區間，在 6217 檔具備完整季度交易紀錄的標的中，有 836 檔在這個下跌日創下季度新高，而 246 檔創下新低 — 相當於每出現一檔新低就有 3.4 檔新高。多數股票只是滑落，並未跌破區間。下跌部分：在 11910 檔通過百萬美元流動性篩選的雙交易時段標的中，有 5435 檔下跌，另有 258 檔具流動性但未滿一個完整季度K線的標的。

板塊全貌：傷害僅限於單一板塊

十一檔 SPDR 板塊型 ETF 是成本最低的全市場橫斷面——同一組籃子，每個交易日都一樣。

查詢11檔標普類股ETF於7月1日表現，由最佳至最差與週二收盤比較
每個數據背後的精確 SQL 語法
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 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 >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
        OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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 pct_above_worst_sector,
    sum(if(day_close > prior_close, 1, 0)) OVER (ORDER BY (day_close / prior_close) DESC ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS green_so_far,
    day_dollar_bn
FROM per_name
ORDER BY pct_chg DESC

通訊服務（XLC）——持有 META 的那檔板塊基金——以 2.41% 領漲，金融（XLF）緊隨其後，報 2.2%。科技（XLK）獨自墊底，落後領漲板塊 -2.56% 與 4.97 個百分點。總計 11 檔基金中有 7 檔收紅——非必需消費 0.68%、醫療保健 0.57%——而公用事業（-1.28%）、工業（-0.98%）與能源（-0.6%）收黑。這就是「指數幾乎紋風不動」的底層樣貌。

今日焦點：記憶體崩跌，META 反向而行

八檔個股主導了今日的分化走勢：四檔在第2季領漲的記憶體與儲存類股，以及圍繞它們的四檔晶片與平台股。以下呈現聯動關係、幅度與時間點；數據本身並未說明原因。

查詢記憶體概念股與巨型股：與週二收盤比較之漲跌、區間時機與成交金額
每個數據背後的精確 SQL 語法
WITH per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-01 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-01 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start >= '2026-07-01 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-01 00:00:00') AS day_low,
        argMinIf(window_start, (toFloat64(low), toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-01 00:00:00') AS low_bar,
        argMaxIf(window_start, (toFloat64(high), -toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-01 00:00:00') AS high_bar,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-01 00:00:00') / 1e9, 2) AS day_dollar_bn
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AMD', 'META', 'MRVL', 'MU', 'NVDA', 'SNDK', 'STX', 'WDC')
      AND ((window_start >= '2026-06-30 13:30:00' AND window_start < '2026-06-30 20:00:00')
        OR (window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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,
    formatDateTime(toTimeZone(high_bar, 'America/New_York'), '%H:%i') AS day_high_et,
    formatDateTime(toTimeZone(low_bar, 'America/New_York'), '%H:%i') AS day_low_et,
    toHour(toTimeZone(low_bar, 'America/New_York')) * 60 + toMinute(toTimeZone(low_bar, 'America/New_York')) AS low_minute_et,
    round((day_high / day_low - 1) * 100, 2) AS range_pct,
    day_dollar_bn
FROM per_name
ORDER BY ticker

SanDisk (-10.45%) 與美光 (-10.23%) 各自跌掉超過十分之一的市值；Marvell -8.68%、AMD -6.87%、Western Digital -6.3%、Seagate -5.11%。MU 成交額高達 $42.94 億，超過 SPY 全天的交易量，且 MU、AMD 與 Marvell 都在收盤前最後幾分鐘（美東時間 15:59、15:57、15:58）打出盤中低點——賣壓一路灌進收盤集合競價，而非一個在盤初就修復的真空區（MU 深度解析涵蓋了其背後的季度表現）。

META 則是鏡像對照：8.88%，成交額 $22.72 億，其低點出現在美東時間 09:30——開盤第一根 K 棒——且此後再未觸及。NVDA 在 -1.09% 幾乎紋絲不動（NVDA 的六月表現）。

報導內容

本頁面不推斷因果。但我們授權的新聞來源就像任何表格一樣——當天刊載的內容如下：

查詢當日最後12則提及MU、SNDK、STX、WDC或META的新聞（單一授權資訊源）
每個數據背後的精確 SQL 語法
SELECT published_et, publisher, names_tagged, headline
FROM (
    SELECT
        published_utc,
        formatDateTime(toTimeZone(published_utc, 'America/New_York'), '%H:%i') AS published_et,
        JSONExtractString(publisher, 'name') AS publisher,
        arrayStringConcat(arrayFilter(x -> x IN ('MU', 'SNDK', 'STX', 'WDC', 'META'), tickers), ' ') AS names_tagged,
        substring(title, 1, 72) AS headline
    FROM global_markets.stocks_news
    WHERE published_utc >= '2026-07-01 04:00:00' AND published_utc < '2026-07-02 04:00:00'
      AND hasAny(tickers, ['MU', 'SNDK', 'STX', 'WDC', 'META'])
      AND NOT has(tickers, 'SPCX')
      AND position(title, 'SPCX') = 0
    ORDER BY published_utc DESC
    LIMIT 12
)
ORDER BY published_utc ASC

The Motley Fool 在美東時間 14:11 發布的美光午後報導，標題為「Why Micron Stock Is Plummeting Today」。其晚間摘要（美東時間 17:12）及四分鐘後的後續報導（美東時間 17:16），均將 META 的股價跳升與一項據傳將多餘 AI 算力作為雲端業務出售的計畫並列。此為該媒體的敘事框架，並非交易紀錄中的發現，而 12 篇來自兩家出版商的文章，僅代表單一新聞來源的關注度，並非全市場的共識。

資金流向何處

查詢成交量雙指標：成交金額前6名、成交股數前4名（一重複代碼上市待實體驗證，暫予排除）
每個數據背後的精確 SQL 語法
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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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 $42.94 億 的交易金額領先全場 — SPY 位居第二，金額為 $27.76 億，META 第四，金額為 $22.72 億 — 一檔下跌中的股票，其交易量比指數基金多出一半。走勢最極端的個股，正是榜單上最喧囂的名字。股票排行板一如往常，是面哈哈鏡：SOXS，這檔三倍反向半導體 ETF，以 553.1 萬股居成交量之冠 — 在晶片股崩跌當日最為忙碌 — 而一檔低價股則以 189.8 萬股、價值 $319 萬元的成交量墊底（相對成交量 正好凸顯了這一點）。基礎：7 月 1 日正常交易時段，排除一檔重複使用代碼的掛牌標的（存託憑證）。

選擇權市場掃描

查詢單列呈現整日選擇權概況：成交量、當日到期、買賣權偏斜與最活躍合約
每個數據背後的精確 SQL 語法
WITH
    (
        SELECT (any(underlying_symbol), any(toFloat64(strike_price)), any(option_type),
                sum(size), round(avg(toFloat64(price)), 3),
                any(if(substring(ticker, length(ticker) - 14, 6) = '260701', 1, 0)))
        FROM global_markets.options_trades
        WHERE sip_timestamp >= '2026-07-01 00:00:00' AND sip_timestamp < '2026-07-02 00:00:00'
        GROUP BY ticker
        ORDER BY sum(size) DESC, ticker ASC
        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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 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(sumIf(toFloat64(size), option_type = 'P') / sumIf(toFloat64(size), option_type = 'C'), 2) AS put_call_ratio,
    round(100.0 * sumIf(size, substring(ticker, length(ticker) - 14, 6) = '260701') / 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, underlying_symbol = 'SPY' AND option_type = 'P')) / 1e6, 2) AS spy_put_contracts_m,
    round(100.0 * sumIf(size, underlying_symbol = 'SPY' AND option_type = 'P' AND toFloat64(strike_price) < spy_regular_close * 0.98)
        / sumIf(size, underlying_symbol = 'SPY' AND option_type = 'P'), 1) AS spy_puts_2pct_below_pct,
    round(100.0 * sumIf(size, underlying_symbol = 'SPY' AND option_type = 'C' AND toFloat64(strike_price) > spy_regular_close * 1.02)
        / sumIf(size, underlying_symbol = 'SPY' AND option_type = 'C'), 1) AS spy_calls_2pct_above_pct,
    round(sumIf(toFloat64(size), underlying_symbol = 'MU' AND option_type = 'P')
        / sumIf(toFloat64(size), underlying_symbol = 'MU' AND option_type = 'C'), 2) AS mu_put_call_ratio,
    round(sumIf(toFloat64(size), underlying_symbol = 'META' AND option_type = 'P')
        / sumIf(toFloat64(size), underlying_symbol = 'META' AND option_type = 'C'), 2) AS meta_put_call_ratio,
    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_volume,
    reverse(arrayStringConcat(extractAll(reverse(toString(assumeNotNull(top_contract.4))), '\\d{1,3}'), ',')) AS top_contract_volume_fmt,
    round(top_contract.5, 3) AS top_contract_avg_price,
    top_contract.6 AS top_contract_is_same_day,
    round(top_contract.2 - spy_regular_close, 2) AS top_strike_minus_spy_close,
    spy_regular_close AS spy_close
FROM global_markets.options_trades
WHERE sip_timestamp >= '2026-07-01 00:00:00' AND sip_timestamp < '2026-07-02 00:00:00'

選擇權交易量達 68.46 萬口合約，分佈於 11.22 萬筆成交紀錄——買權佔總量 58.6%，當日到期合約佔 33.5%。全市場無人避險指數：全市場賣權買權比為 0.71，而 SPY 的 5.76 萬口賣權中，僅 11.6% 口履約價低於其 745.69 收盤價逾兩個百分點——即在崩盤時能獲利的極端價外履約價。偏斜集中在個股：美光（Micron）的賣權數量超過買權（每口買權對應 1.11 口賣權），而 META 的買權數量則以優於二比一的比例勝過賣權（0.39）。最活躍合約為當日到期 SPY $748 買權——878,947 口合約，均價 $0.707——到期時價外 2.31 美元，與週二情況相同。全日無任何 7 月 3 日到期的成交紀錄（0 筆成交——該週五休市）；週四到期的週選擇權則成交 14.43 萬口。

利率：長端緩步走高，短端下滑

殖利率為每日收盤價，對比基準日6月30日。

查詢美國公債殖利率曲線，7月1日收盤與6月30日比較（僅列有報價之存續期）
每個數據背後的精確 SQL 語法
SELECT
    t.1 AS curve_point,
    round(t.2, 2) AS jul1_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 = '2026-07-01') AS d,
         (SELECT * FROM global_markets.treasury_yields WHERE date = '2026-06-30') AS p
)

10年期公債殖利率上升4個基點至4.48%，30年期上升6個基點，而1個月期國庫券則變動-3個基點——中段與長端走高，短端下滑。2年期與10年期利差收在0.31個百分點：此處走勢與股市表現並無對應關係。

這一天背後的日曆

查詢7月1日企業行事曆與資訊流，單列彙整
每個數據背後的精確 SQL 語法
WITH
    (
        SELECT (count(), uniqExact(publisher))
        FROM global_markets.stocks_news
        WHERE toDate(toTimeZone(published_utc, 'America/New_York')) = '2026-07-01'
    ) 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')) = '2026-07-01'
            )
            WHERE t != 'SPCX'
            GROUP BY t
        )
    ) AS top_news
SELECT
    (SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS ex_dividend_records,
    (SELECT countIf(frequency = 12) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS monthly_payers,
    (SELECT countIf(frequency = 4) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS quarterly_payers,
    (SELECT round(100.0 * countIf(frequency = 12) / count(), 1) FROM global_markets.stocks_dividends WHERE ex_dividend_date = '2026-07-01') AS monthly_payer_pct,
    (SELECT count() FROM global_markets.stocks_splits WHERE execution_date = '2026-07-01') AS splits_executed,
    (SELECT count() FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-01') AS ipos_listed,
    (SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS sec_filings,
    (SELECT uniqExactIf(accession_number, form_type = '4') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS insider_form4_filings,
    (SELECT uniqExactIf(accession_number, form_type = '8-K') FROM global_markets.stocks_sec_edgar_index WHERE filing_date = '2026-07-01') AS filings_8k,
    (SELECT arrayStringConcat(groupArray(concat(ticker, ' — ', issuer_name)), '; ') FROM (
        SELECT ticker, issuer_name FROM global_markets.stocks_ipos WHERE listing_date = '2026-07-01' 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

季度轉折在此達到高峰：745 檔除息標的 進入除息日——正是六月回顧所觀察到的那股浪潮——同時還有 9 檔股票分割與 3 檔新掛牌（BSP — Bending Spoons S.p.A.; ITG — ITG Inc.; LIME — Neutron Holdings Inc.）。申報資訊流也重新活躍起來：4282 份申報文件，其中 1072 份為Form 4 申報，248 份為 8-K 申報，一掃 6 月 30 日近乎空白的指數日（月底缺口筆記）的沉寂。我們的資訊流共刊出 201 篇文章，涵蓋度最高的 MSFT 則有 16 篇。

但數量本身並不能說明資金流向。若以實際交易金額來排序，盤面上最活躍的標的根本不是公司股票：

查詢7月1日除息之主要個股，依當日成交金額排序
每個數據背後的精確 SQL 語法
WITH divs AS (
    SELECT ticker, max(toFloat64(cash_amount)) AS cash, max(frequency) AS freq
    FROM global_markets.stocks_dividends
    WHERE ex_dividend_date = '2026-07-01' AND distribution_type = 'recurring'
    GROUP BY ticker
),
tape AS (
    SELECT ticker,
           sum(toFloat64(close) * toFloat64(volume)) AS dollar_volume,
           toFloat64(argMax(close, (window_start, close))) AS day_close
    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'
      AND ticker NOT IN ('SPCX')
    GROUP BY ticker
)
SELECT
    d.ticker AS ticker,
    round(d.cash, 4) AS cash_per_share,
    d.freq AS payments_per_year,
    round(t.day_close, 2) AS day_close,
    round(100 * d.cash / t.day_close, 2) AS pct_of_price,
    round(100 * d.cash * d.freq / t.day_close, 2) AS annualized_yield_pct,
    round(t.dollar_volume / 1e9, 2) AS day_dollar_bn
FROM divs d JOIN tape t ON d.ticker = t.ticker
WHERE t.dollar_volume > 0 AND d.cash > 0
ORDER BY t.dollar_volume DESC
LIMIT 8

交易最熱絡的八檔除息標的，每一檔都是每年配息 12 次的基金：SGOV，一檔國庫券基金，除息金額為每股 $0.2958（佔價格的 0.29%，年化 3.54%），交易金額達 $3.5 億；HYG，一檔高收益債券基金，除息金額為 $0.3688。這正是月初的典型浪潮：當天 745 筆除息紀錄中的 572（佔 76.8%）都是月配息標的——也就是分配利息的基金——對比之下，季配息標的僅有 123 筆。除息日的價格下跌純屬機制性調整，並非實質損失。

每季的第一天，真的只是平凡的一天嗎？

故事總是這樣寫：新一季、新資金、新的配置布局。但數據庫並不這麼認為。

查詢自2004年以來每一季開盤日：SPY開盤至收盤走勢，並列入7月1日排名
每個數據背後的精確 SQL 語法
SELECT
    count() AS quarter_opens_measured,
    round(quantileExact(0.5)(oc_pct), 2) AS median_quarter_open_pct,
    countIf(oc_pct > 0) AS quarter_opens_green,
    countIf(oc_pct <= 0) AS quarter_opens_red,
    round(anyIf(oc_pct, first_day = toDate('2026-07-01')), 2) AS jul1_oc_pct,
    arrayCount(x -> x < anyIf(oc_pct, first_day = toDate('2026-07-01')), groupArrayIf(oc_pct, first_day != toDate('2026-07-01'))) + 1 AS jul1_rank_worst_to_best,
    round(min(oc_pct), 2) AS worst_quarter_open_pct,
    round(max(oc_pct), 2) AS best_quarter_open_pct,
    concat(monthName(min(first_day)), ' ', toString(toYear(min(first_day)))) AS first_measured
FROM (
    SELECT f.first_day AS first_day, d.oc_pct AS oc_pct
    FROM (
        SELECT toStartOfQuarter(d) AS q, min(d) AS first_day
        FROM (
            SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
            FROM global_markets.delayed_stocks_minute_aggs
            WHERE ticker = 'SPY'
              AND window_start >= toDateTime('2004-01-01 00:00:00')
              AND window_start < toDateTime('2026-07-02 00:00:00')
              AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
            GROUP BY d
        )
        GROUP BY q
    ) f
    INNER JOIN (
        SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
               (argMax(toFloat64(close), (window_start, close)) / argMin(toFloat64(open), (window_start, open)) - 1) * 100 AS oc_pct
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= toDateTime('2004-01-01 00:00:00')
          AND window_start < toDateTime('2026-07-02 00:00:00')
          AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
        GROUP BY d
    ) d ON d.d = f.first_day
)

自 January 2004 年以來，在 91 個季度的首個交易日中，SPY 在季度第一天的開盤至收盤漲跌幅中位數為 0.01%——上漲 46 次，下跌 45 次，漲跌幅範圍介於 -2.28% 至 3.18% 之間：這就像擲硬幣，只是附帶了一點四捨五入的誤差。7 月 1 日的漲幅為 0.09%，在表現最差到最佳的 91 個交易日中排名第 50——正好落在正中間。計算基礎：數據庫中每個季度第一個交易日的 SPY 常規交易時段開盤至收盤漲跌幅。

這一天留給讀者什麼

指數變動 0.09%；八檔成分股橫跨 -10.45% 到 8.88%；避險成本幾乎沒有重新定價。這就是集中市場的尋常算術——一個板塊的損失，被 7 個 11 板塊的漲幅抵銷，正是指數結算出來的結果。從指數層面看，這裡什麼都沒發生；從持倉層面看，一天之內十分之一的部位就蒸發了。

已驗證的交易時段

查詢交易時段檢查：SPY觀察到的一分鐘K線跨度
每個數據背後的精確 SQL 語法
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 >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00') AS regular_session_bars,
    uniqExactIf(toDate(toTimeZone(window_start, 'America/New_York')), window_start >= '2026-07-01 13:30:00' AND window_start < '2026-07-01 20:00:00') AS day_sessions,
    (SELECT count() FROM global_markets.stocks_market_holidays WHERE date = '2026-07-01') AS jul1_holiday_rows
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2026-07-01 00:00:00' AND window_start < '2026-07-02 00:00:00'

SPY 的 K 棒涵蓋紐約時間 04:00 至 19:59，包含 390 根常規交易時段 K 棒，以及當日 0 個假日列 — 經由逐筆成交資料驗證，為一完整交易時段。

常見問題

2026年7月1日股市是漲還是跌？

看你從哪個角度觀察。SPY收盤-0.08%，DIA0.02%，QQQ-1.44%；3465檔流動性較高的個股下跌，2928檔上漲——然而11檔板塊型基金中有7檔收紅，科技股是當中的異類。

為什麼美光、SanDisk、Western Digital與Seagate在2026年7月1日全面下跌？

這份數據呈現的是同步走勢，而非因果關係：這四檔股票跌幅介於-5.11%到-10.45%之間。Motley Fool當天針對美光的報導（位於本頁新聞面板，14:11美東時間），標題為「Why Micron Stock Is Plummeting Today」。那是該媒體的詮釋框架，並非來自交易數據的結論。

為什麼META在2026年7月1日上漲？

META收盤上漲8.88%，日內低點就落在開盤第一根K線。Motley Fool的報導將此走勢歸因於消息指出，該公司計劃將多餘的AI運算能力以雲端業務形式對外銷售：這是該媒體的歸因，並非我們的判斷。

每季的第一個交易日通常表現強勁嗎？

沒有明顯的統計證據。自January 2004年以來，共計91個季度首日，SPY開盤到收盤的漲跌幅中位數為0.01%：46次收紅，45次收黑——就像擲硬幣一樣；7月1日的表現落在中間水準。

2026年7月1日當天，選擇權市場有在避險這波拋售嗎？

就指數層面來看並沒有：全市場賣權對買權比率為0.71，而SPY的賣權成交量中，僅有11.6%的履約價落在低於收盤價超過百分之二的位置。

資料說明

  • 成交金額為每分鐘估算值 — 收盤價 × 成交量，以每分鐘K棒加總，僅計算一般交易時段。顯示的極端值已與相鄰K棒交叉比對；若出現相同數值，則取最早發生者。
  • 此處不存在現貨VIX指數。 波動率面板所列為掛牌交易的VIX期貨基金，這些基金持有並轉倉期貨 — 與指數相關，但從不完全相同。
  • 季度新高／新低 是將7月1日一般交易時段的極端值，與各標的4月1日至6月30日的區間進行比較，僅納入流動性充足且具備完整季度K棒資料的標的；下架標的則列於面板中。
  • 類股面板為精選組合（十一檔SPDR ETF，非廠商提供的欄位）；新聞面板來自單一授權資訊源（12篇文章，兩家發布商）；一檔重複使用代碼的掛牌標的已從排行榜中排除（其相關記錄）。

方法說明

  • 單一交易時段（1 時段，由觀察到的 K 棒與假日表驗證——絕非假設）。時間戳記以 UTC 儲存，在查詢內部轉換為紐約時間；「收盤」指常規交易時段最後一分鐘的 K 棒，日變動以 6 月 30 日為基準。
  • 小數在進行比率運算前會先轉換為 64 位元浮點數；選擇權到期日則從 OCC 代碼重新解析。各面板在撰寫當下透過受控的唯讀路徑執行一次。資料倉儲狀態截至 2026 年 7 月 13 日；本版新增產業、波動率、新聞、股利與季度歷史面板。

每個面板都是一個已儲存的查詢結果——圖表、表格與 SQL 為同一物件。可將任一查詢貼入 Strasmore 終端機。下一篇：7 月 2 日；本週回顧：假期週。

#recap#daily#spy#qqq#market structure