Strasmore Research
Deep Dives · Matt ConnorBy Matt Connor · · Updated 2026-07-25

NVDA: 6月逐筆全紀錄

NVIDIA 6月完整回顧：盤前高點 $235，7.4% 個交易日跌 21，美元成交量全美第 fourth 大。

NVIDIA 在 2026 年 6 月以 $215.77 開盤，月底收在 $199.76 — 在 21 個交易日內下跌 -7.4%。股價在 2026-06-02 04:00（美東時間）盤前交易觸及 $235 高點，於 2026-06-02 09:59（美東時間）創下 $232.28 的常規交易時段高點，並在 2026-06-29 10:17（美東時間）跌至 $189.8 低點 — 全部為常規交易時段。總成交量：2.75 億股，成交金額 $571.9 億美元 — 以常規交易時段美元成交額計，為美國市場上第 fourth 大股票（統計基礎：6 月 1 日至 30 日常規交易時段；一檔重複使用代碼的 6 月上市股票因待實體驗證而排除）。此處每個數字均為儲存查詢結果；展開任一區塊即可查看確切 SQL。

查詢單月一列：開盤、收盤、極值、成交量及其收據
每個數據背後的精確 SQL 語法
WITH
    (
        SELECT (toString(argMax(et_date, c)), max(c), argMax(c, et_date))
        FROM (
            SELECT
                toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
                argMax(toFloat64(close), window_start) AS c
            FROM global_markets.delayed_stocks_minute_aggs
            WHERE ticker = 'NVDA'
              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 et_date
        )
    ) AS closes,
    (
        SELECT max(toFloat64(high)) FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'NVDA'
          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 = 'NVDA'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    ) AS lo,
    (
        SELECT maxIf(toFloat64(high), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199)
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'NVDA'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    ) AS rth_hi,
    (
        SELECT minIf(toFloat64(low), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199)
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'NVDA'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
    ) AS rth_lo,
    (
        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
    round(toFloat64(argMin(open, window_start)), 2) AS month_open,
    closes.3 AS month_close,
    round((closes.3 / toFloat64(argMin(open, window_start)) - 1) * 100, 1) AS month_change_pct,
    round((1 - closes.3 / toFloat64(argMin(open, window_start))) * 100, 1) AS month_decline_abs_pct,
    closes.1 AS peak_close_date,
    round(closes.2, 2) AS peak_close,
    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,
    countIf(toFloat64(high) >= hi - 0.011) AS bars_within_cent_of_high,
    argMinIf(transactions, window_start, toFloat64(high) >= hi - 0.011) AS high_minute_trades,
    round(rth_hi, 2) AS rth_month_high,
    formatDateTime(toTimeZone(minIf(window_start, toFloat64(high) >= rth_hi - 0.011 AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 'America/New_York'), '%Y-%m-%d %H:%i') AS rth_high_first_bar_et,
    countIf(toFloat64(high) >= rth_hi - 0.011 AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS rth_bars_near_high,
    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_bar_et,
    countIf(toFloat64(low) <= lo + 0.011) AS bars_within_cent_of_low,
    argMin(transactions, toFloat64(low)) AS low_minute_trades,
    round(rth_lo, 2) AS rth_month_low,
    round(rth_lo - lo, 2) AS rth_minus_extended_low,
    round(toFloat64(sum(volume)) / 1e9, 2) AS month_shares_bn,
    round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 1) AS month_dollar_bn,
    round(sumIf(toFloat64(close) * toFloat64(volume), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / 1e9, 1) AS rth_dollar_bn,
    round(sumIf(toFloat64(volume), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / 1e9, 2) AS rth_shares_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 = 'NVDA'
  AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')

走勢呈現穩步下跌趨勢，並在最後一週出現一次明顯的跳空下跌。NVDA 僅在 2026-06-01（當月第一個交易日）這一天收在 $224.43 之上。當月低點出現在 2026-06-29 10:17（美東時間）的常規交易時段，該分鐘內 1 根 K 棒價位差距在一美分之內，並有 43131 筆成交。2026-06-02 04:00（美東時間）的盤前 $235 高點為延長交易時段數據；常規交易時段高點 $232.28 則出現在 2026-06-02 09:59（美東時間）。6 月 19 日全市場休市（當日 SPY 有 0 根 K 棒），因此 NVDA 共有 21 個交易日。

逐日交易

查詢21個交易日：常規交易時段收盤價、收盤變動、全日成交量
每個數據背後的精確 SQL 語法
SELECT
    et_date,
    close_usd,
    round(if(prev_close = 0, NULL, (close_usd / prev_close - 1) * 100), 1) AS change_pct,
    shares_m,
    dollar_bn
FROM (
    SELECT et_date, close_usd, shares_m, dollar_bn,
           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,
            round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 2) AS dollar_bn
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'NVDA'
          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

逐日交易表呈現持續下滑的走勢。首次收盤價高於 $224.43 是在 2026-06-01，創下當月高點。單日最大跌幅為 -6.2%，發生在 2026-06-05（週五），當日成交量也是本月最高，達 187.3 百萬股。最顯著的走勢是連續 5 個交易日下跌，從 2026-06-22 到 2026-06-26，最終收於本月最低收盤價 $191.72；最後兩個交易日則分別回升了 1.7% 和 2.5%。成交量集中在前半段：首日為 185.5 百萬股，最後一日為 119.6 百萬股。

查詢五日跌勢，附邊界：逐句斷言皆為勾選欄位
每個數據背後的精確 SQL 語法
WITH per_session AS (
    SELECT et_date, close_usd,
           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
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'NVDA'
          AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
        GROUP BY et_date
    )
)
SELECT
    toString(minIf(et_date, et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26'))) AS run_start,
    toString(maxIf(et_date, et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26'))) AS run_end,
    countIf(et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26')) AS sessions_in_run,
    countIf(et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26') AND close_usd < prev_close) AS declining_sessions,
    round(minIf(close_usd, et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26')), 2) AS run_low_close,
    toUInt8(min(close_usd) = minIf(close_usd, et_date >= toDate('2026-06-22') AND et_date <= toDate('2026-06-26'))) AS run_holds_month_low_close
FROM per_session

六月對比過去六個月

對 NVDA 而言，這樣的月份是異常還是常態？下方面板一次性重新計算過去六個月每個月的相同三項數據——六月這一列，與前五個月來自完全相同的查詢，在生成當下直接從資料庫提取。

查詢回溯六個月，即時重算：成交額、股數、月報酬
每個數據背後的精確 SQL 語法
SELECT
    toString(toStartOfMonth(toDate(toTimeZone(window_start, 'America/New_York')))) AS period_start,
    round(sumIf(toFloat64(close) * toFloat64(volume), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / 1e9, 1) AS rth_dollar_bn,
    round(toFloat64(sum(volume)) / 1e9, 2) AS shares_bn,
    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
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'NVDA'
  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

以成交額來看，六月屬於常態：一般交易時段成交 $523 億美元，落在這段期間的中間水準，低於五月的 $557.5 億美元與三月的 $572.5 億美元。報酬率這一欄則是六月最突出的地方：-7.4% 是這六個月以來最大的單月跌幅，對比二月的 -4.8%，以及四月和五月的正報酬。

全市場成交量第 fourth 大的股票

查詢全美市場依2026年6月常規交易時段成交額排名
每個數據背後的精確 SQL 語法
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,
    toUInt8(ticker = 'NVDA') AS is_nvda
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 12

以一般交易時段美元成交金額計，NVDA 在全美股市排名第 fourth：$523 億，比緊接其後的 SNDK 高出 $141.5 億，僅次於 MU（$995.7 億）、SPY（$771.5 億）與 QQQ（$672.8 億）。統計基礎：6 月 1 日至 30 日一般交易時段，其中一檔因代碼重複使用的 6 月掛牌標的，待實體查核完成前暫不納入——其相關數據請見該標的專題分析。在 NVDA 之上的三個名字中，1 是單一個股——MU，另一檔半導體股；其餘兩者則是大型指數 ETF。

查詢排名收據：NVDA 名次、對次名領先幅度及計算基礎——皆為勾選欄位
每個數據背後的精確 SQL 語法
WITH (
    SELECT sum(toFloat64(volume) * toFloat64(close))
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'NVDA'
      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 nvda_d
SELECT
    countIf(d > nvda_d AND ticker != 'NVDA') + 1 AS nvda_rank,
    round(nvda_d / 1e9, 1) AS nvda_dollar_bn,
    round((nvda_d - maxIf(d, d < nvda_d AND ticker != 'NVDA')) / 1e9, 1) AS lead_over_next_bn,
    countIf(d > nvda_d AND ticker NOT IN ('SPY', 'QQQ', 'NVDA')) AS single_stocks_above_nvda,
    round(100 * nvda_d / max(d), 1) AS pct_of_leader
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
)

這卷磁帶是由什麼構成的

查詢NVDA 完整報價帶一列：成交筆數、每筆股數、報價普查
每個數據背後的精確 SQL 語法
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 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 = 'NVDA'
          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 locked_updates,
    quote_census.4 AS crossed_updates,
    quote_census.5 AS one_sided_or_empty_updates
FROM global_markets.stocks_trades
WHERE ticker = 'NVDA'
  AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)

質地是小字體且報價密集：55.64 百萬筆成交，中位數為 5 股（平均 72.9 股——機構大宗交易拉高了平均值），84.6% 筆畸零股（低於 100 股），32.91% 筆零股——這與散戶應用程式將訂單分割送入造市商庫存的情況一致。報價方面：55.7 百萬次 NBBO 更新，99.35% 次為乾淨的雙邊報價；33941 次短暫交叉（買價高於賣價），329679 次鎖定（買價等於賣價），63 次為單邊或空白。一檔大型股在一個月內產生的報價，比許多股票十年產生的還多。

價差保持狹窄

像 NVDA 這樣的巨型股，其買賣價差在本質上就很狹窄——問題在於，在股價震盪 20 點的一個月裡，這種狹窄的穩定性如何。上方的報價普查顯示的是月度中位數；此面板則衡量逐個交易日的表現。

查詢逐日價差：常規交易時段中位數與時間加權平均（基點）
每個數據背後的精確 SQL 語法
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 = 'NVDA'
  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

價差整月都維持在一個狹窄的區間內：1.34，2026-06-01 個基點，以及 1.01，2026-06-30 個基點——在股價下跌 20 點的過程中，這種巨型股的價差幾乎紋風不動。價差最大的一個交易日是 2026-06-05，為 0.97 個基點（當天跌幅為 -6.2%），最窄的則是 2026-06-15，為 0.95 個基點。若要與交易清淡的股票進行規模對比，請參閱6月29日微觀結構深度分析，其中單一股票的價差面板涵蓋了同一個交易日。

選擇權：64.64 百萬口合約，每個交易時段均為買權領先

查詢NVDA 選擇權市場一列：總量、到期結構、主力合約
每個數據背後的精確 SQL 語法
WITH
    (
        SELECT (round(sum(toFloat64(price) * size) * 100 / 1e9, 2), round(sum(size) / 1e6, 1))
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:AAPL') AND length(ticker) = 21
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
    ) AS aapl,
    (
        SELECT (round(sum(toFloat64(price) * size) * 100 / 1e9, 2), round(sum(size) / 1e6, 1))
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:TSLA') AND length(ticker) = 21
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
    ) AS tsla,
    (
        SELECT concat('$', toString(round(toFloat64(toUInt32OrZero(substring(ticker, 14, 8))) / 1000, 2)),
               if(substring(ticker, 13, 1) = 'P', ' put', ' call'),
               ', expiry 20', substring(ticker, 7, 2), '-', substring(ticker, 9, 2), '-', substring(ticker, 11, 2))
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
        GROUP BY ticker ORDER BY sum(size) DESC LIMIT 1
    ) AS busiest_name,
    (
        SELECT concat('$', toString(round(toFloat64(toUInt32OrZero(substring(ticker, 14, 8))) / 1000, 2)),
               if(substring(ticker, 13, 1) = 'P', ' put', ' call'),
               ', expiry 20', substring(ticker, 7, 2), '-', substring(ticker, 9, 2), '-', substring(ticker, 11, 2))
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
        GROUP BY ticker ORDER BY sum(toFloat64(price) * size) DESC LIMIT 1
    ) AS premium_name,
    (
        SELECT round(toFloat64(toUInt32OrZero(substring(ticker, 14, 8))) / 1000, 2)
        FROM global_markets.options_trades
        WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
          AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
        GROUP BY ticker ORDER BY sum(toFloat64(price) * size) DESC LIMIT 1
    ) AS premium_strike,
    (
        SELECT max(pc)
        FROM (
            SELECT round(toFloat64(sumIf(size, substring(ticker, 13, 1) = 'P')) / toFloat64(sumIf(size, substring(ticker, 13, 1) = 'C')), 3) AS pc
            FROM global_markets.options_trades
            WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
              AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
            GROUP BY toDate(sip_timestamp)
        )
    ) AS max_daily_pc
SELECT
    formatDateTime(toTimeZone(min(sip_timestamp), 'America/New_York'), '%Y-%m-%d %H:%i:%S') AS first_print_et,
    uniqExact(toDate(sip_timestamp)) AS option_sessions,
    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, 13, 1) = 'P')) / toFloat64(sumIf(size, substring(ticker, 13, 1) = 'C')), 2) AS month_put_call_ratio,
    max_daily_pc AS max_session_put_call_ratio,
    uniqExact(substring(ticker, 7, 6)) AS expiries_traded,
    concat('20', substring(max(substring(ticker, 7, 6)), 1, 2), '-', substring(max(substring(ticker, 7, 6)), 3, 2), '-', substring(max(substring(ticker, 7, 6)), 5, 2)) AS longest_expiry,
    round(100 * toFloat64(sumIf(size, substring(ticker, 7, 6) = '260618')) / toFloat64(sum(size)), 1) AS jun18_expiry_share_pct,
    busiest_name AS busiest_contract,
    premium_name AS top_premium_contract,
    premium_strike AS top_premium_strike_usd,
    aapl.1 AS aapl_premium_bn,
    aapl.2 AS aapl_contracts_m,
    tsla.1 AS tsla_premium_bn,
    tsla.2 AS tsla_contracts_m
FROM global_markets.options_trades
WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
  AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)

在 21 個選擇權交易時段中：8.9 百萬筆成交，涵蓋 5163 檔不同合約，64.64 百萬口合約及$24.43 十億權利金（價格乘以 100 股乘數）。當月賣權/買權比率為 0.55——買權在每個交易時段成交量均超越賣權；單日比率最高達 0.782，且從未觸及 1.0。共有 38 個到期日進行交易，範圍自 6 月 18 日當周到期的週選擇權，至 2028-12-15 的 LEAPS；僅 6 月 18 日到期的選擇權即佔當月成交量的 10.5%。最活躍合約：$210 call, expiry 2026-06-18。權利金磁吸合約：$0.5 call, expiry 2026-12-18——一檔深度價內、履約價 $0.5 的合約。作為對比，AAPL 選擇權在 6 月以 27 百萬口合約收取了 $8.84 十億權利金；TSLA 則以 58 百萬口合約收取了 $33.68 十億。

查詢逐日選擇權：合約量、買權／賣權分佈、賣權／買權比率
每個數據背後的精確 SQL 語法
SELECT
    toDate(sip_timestamp) AS session,
    count() AS prints,
    toUInt64(sum(size)) AS contracts_traded,
    toUInt64(sumIf(size, substring(ticker, 13, 1) = 'C')) AS call_contracts,
    toUInt64(sumIf(size, substring(ticker, 13, 1) = 'P')) AS put_contracts,
    round(toFloat64(sumIf(size, substring(ticker, 13, 1) = 'P')) / toFloat64(sumIf(size, substring(ticker, 13, 1) = 'C')), 2) AS put_call_ratio,
    round(100 * toFloat64(sum(size)) / max(toFloat64(sum(size))) OVER (), 1) AS pct_of_busiest_session
FROM global_markets.options_trades
WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
  AND sip_timestamp >= toDateTime64('2026-06-01 00:00:00', 9) AND sip_timestamp < toDateTime64('2026-07-01 00:00:00', 9)
GROUP BY session
ORDER BY session

最繁忙的選擇權交易時段為 2026-06-05——5298529 口合約，佔當月峰值的 100%——與創下最高現股成交量的 -6.2% 下跌日為同一日。賣權/買權比率隨價格下跌而上升：該比率在 2026-06-02 觸底於 0.33（接近價格高峰），並在 2026-06-12（該股首次收於 $205.14 以下的交易時段）攀升至 0.61。賣權成交量隨價格下跌而增長——無論是避險活動或方向性押注；數據顯示了兩者的共移關係，而非意圖。

查詢合約落點：依履約價區間之買權與賣權成交量
每個數據背後的精確 SQL 語法
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,
    round(100 * (call_contracts + put_contracts) / max(call_contracts + put_contracts) OVER (), 1) AS pct_of_biggest_bucket
FROM (
    SELECT
        least(floor(toFloat64(toUInt32OrZero(substring(ticker, 14, 8))) / 1000 / 25) * 25, 450) AS bucket,
        toUInt64(sumIf(size, substring(ticker, 13, 1) = 'C')) AS call_contracts,
        toUInt64(sumIf(size, substring(ticker, 13, 1) = 'P')) AS put_contracts
    FROM global_markets.options_trades
    WHERE startsWith(ticker, 'O:NVDA') AND length(ticker) = 21
      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))

履約價分佈圖呈現以 $200 交易區間為中心的槓鈴型態。$200 區間——價平——吸納了最大成交量，賣權佔比 32.7%（雙向交易）。在該區間以下，賣權佔主導地位（$150 區間中佔 88.3%）；在該區間以上，買權則主導盤面（$225 區間賣權佔比 6.3%，$450 上限區間有 120039 口合約）。此結構堪稱教科書範例：下方為保護性賣權，上方為投機性買權，價平區域則為雙向市場。

新聞流量

查詢資訊流一列：量、組成、共同標籤
每個數據背後的精確 SQL 語法
WITH
    (
        SELECT (toString(d), n)
        FROM (
            SELECT toDate(toTimeZone(published_utc, 'America/New_York')) AS d, count() AS n
            FROM global_markets.stocks_news
            WHERE has(tickers, 'NVDA')
              AND published_utc >= toDateTime('2026-06-01 00:00:00')
              AND published_utc < toDateTime('2026-07-01 04:00:00')
            GROUP BY d ORDER BY n DESC, d ASC LIMIT 1
        )
    ) AS peak_day,
    (
        SELECT (JSONExtractString(any(publisher), 'name'), count())
        FROM global_markets.stocks_news
        WHERE has(tickers, 'NVDA')
          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,
    toString(min(toDate(toTimeZone(published_utc, 'America/New_York')))) AS first_tagged_day,
    peak_day.1 AS peak_day_date,
    peak_day.2 AS peak_day_articles,
    top_pub.1 AS top_publisher,
    top_pub.2 AS top_publisher_articles,
    round(100.0 * top_pub.2 / count(), 0) AS top_publisher_pct,
    countIf(has(tickers, 'TSLA')) AS tsla_co_articles,
    countIf(has(tickers, 'AMD')) AS amd_co_articles,
    countIf(has(tickers, 'MSFT')) AS msft_co_articles,
    countIf(has(tickers, 'AAPL')) AS aapl_co_articles
FROM global_markets.stocks_news
WHERE has(tickers, 'NVDA')
  AND published_utc >= toDateTime('2026-06-01 00:00:00')
  AND published_utc < toDateTime('2026-07-01 04:00:00')

6月共有 642 篇標記NVDA的文章，來自 4 家發布者。請謹慎解讀這些數字：光是 The Motley Fool 就貢獻了 63% 篇——這只反映單一資訊源的關注度，而非全球媒體的報導量。文章數量最高的一天是 2026-06-01，共 45 篇。共同標籤顯示了報導框架：MSFT出現 169 次，AAPL 134 次，AMD 101 次，TSLA 69 次——該資訊源將NVDA視為巨型科技股題材，而非半導體題材。

空方部位

查詢FINRA 場外逐日放空量：標記放空股數與申報成交量
每個數據背後的精確 SQL 語法
SELECT
    date,
    round(toFloat64(any(short_volume)) / 1e6, 2) AS short_shares_m,
    round(toFloat64(any(total_volume)) / 1e6, 2) AS offexchange_total_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 = 'NVDA' AND date >= toDate('2026-06-01') AND date <= toDate('2026-06-30')
GROUP BY date
ORDER BY date

場外短線成交量，指的是FINRA所通報、標記為短線的成交量佔比；其中大部分是造市商為滿足客戶買單而進行的放空——這屬於常規的市場運作機制，並非空單餘額。NVDA 的標記短線佔比，範圍從 29.3%（2026-06-01）到 48.1%（2026-06-30）。在存檔的 20 個交易日中，場外通報成交量於 2026-06-02 達到峰值 86.77 百萬股，並於 2026-06-16 觸及谷底 43.31 百萬股。

查詢場外放空高峰與低谷，附邊界（逐日去重）
每個數據背後的精確 SQL 語法
SELECT
    toString(argMax(date, offex_m)) AS peak_date,
    max(offex_m) AS peak_offex_m,
    toString(argMin(date, offex_m)) AS trough_date,
    min(offex_m) AS trough_offex_m,
    round(max(offex_m) - min(offex_m), 2) AS peak_minus_trough_m,
    count() AS sessions_on_file
FROM (
    SELECT date, round(toFloat64(any(total_volume)) / 1e6, 2) AS offex_m
    FROM global_markets.stocks_short_volume
    WHERE ticker = 'NVDA' AND date >= toDate('2026-06-01') AND date <= toDate('2026-06-30')
    GROUP BY date
)
查詢六月中放空餘額數據
每個數據背後的精確 SQL 語法
SELECT
    toString(max(settlement_date)) AS settlement,
    round(toFloat64(argMax(short_interest, settlement_date)) / 1e6, 2) AS shares_short_m,
    round(toFloat64(argMax(avg_daily_volume, settlement_date)) / 1e6, 2) AS avg_daily_volume_m,
    argMax(days_to_cover, settlement_date) AS reported_days_to_cover,
    round(toFloat64(argMax(short_interest, settlement_date)) / toFloat64(argMax(avg_daily_volume, settlement_date)), 2) AS implied_days_to_cover,
    count() AS june_settlements
FROM global_markets.stocks_short_interest
WHERE ticker = 'NVDA'
  AND settlement_date >= toDate('2026-06-01') AND settlement_date <= toDate('2026-06-30')

實際空單餘額數據為 2026-06-30：放空股數達 310.13 百萬股，對比日均成交量 155.99 百萬股。數據供應商提供的回補天數為 1.99；原始比率為 1.99——空方大約需要兩個平均交易日的量才能完成回補。該月份兩次的結算數據均已存檔（2 六月數據）；上述數字採用的是6月30日的月底結算數據。

資料說明

查詢NVDA 基本面普查：資產負債表、損益表、現金流量表
每個數據背後的精確 SQL 語法
SELECT
    (SELECT count() FROM global_markets.stocks_balance_sheets WHERE has(tickers, 'NVDA')) AS balance_sheet_rows,
    (SELECT count() FROM global_markets.stocks_income_statements WHERE has(tickers, 'NVDA')) AS income_statement_rows,
    (SELECT count() FROM global_markets.stocks_cash_flow_statements WHERE has(tickers, 'NVDA')) AS cash_flow_rows
完整資料說明
  • 標的。 NVDA 為 NVIDIA Corporation，CIK 代碼 0001045810，於 Nasdaq 掛牌。無代碼重複使用之歧義；不涉及標的邊界之附帶說明。資料倉儲中載有 NVDA 的 83 列資產負債表項目、152 列損益表項目，以及 152 列現金流量表項目——基本面數據存在，與 6月29日微結構深入探討 案例不同。
  • 當月極端價位。 當月高點 $235 於 2026-06-02 04:00 美東時間在盤前交易（凌晨 4:00）產生；一般交易時段高點 $232.28 則於 2026-06-02 09:59 美東時間產生。當月低點與一般交易時段低點均為 $189.8——此低點是在一般交易時段內產生。
  • 6月19日休市。 資料倉儲中載有 6 月 19 日（六月節）的 0 根 SPY K 線，因此 NVDA 的 6 月份涵蓋 21 個交易日。假日表未回溯至 2026 年 6 月（始於 2026 年 7 月 3 日）；零 K 線的觀察結果即為依據。
  • 成交金額。 以每分鐘收盤價乘以該分鐘成交量後加總——此為以收盤價加權的名目本金近似值。一般交易時段數字（$523 億）不含盤前與盤後 K 線；全日數字（$571.9 億）則包含在內。
  • 選擇權解析。 到期日、類型與履約價係自 OCC 代碼重新解析（表格中的 expiration_date 欄位不可靠）；權利金名目本金假設履約倍數為 100 股。
  • 每次更新之買賣價差統計 係對每次 NBBO 更新賦予相同權重；時間加權統計則置於面板中。中位數採用確定性分位數計算。
  • 未觸發逐筆數據防護。 所有逐筆成交表格查詢均經聚合處理；委託簿質地查詢則將完整成交表格加總為單一列。
  • 6月29日之短倉成交量缺口。 6 月 29 日的 FINRA 場外短倉成交量檔案全市場均遭截斷（原始檔案於字母排序中段終止）；NVDA 排序在截斷點之前，故其資料列缺失。短倉成交量面板載有 20 個交易日；6 月 29 日該列為缺失（全市場檔案截斷所致），而非數值為零。6月29日深入探討 中載有全市場探查依據。

方法論

  • 時間戳記以 UTC 儲存，並以原始 UTC 邊界篩選；2026 年 6 月全程為美東夏令時間，因此常規交易時段為 13:30–20:00 UTC（美東時間上午 9:30 至下午 4:00）。toTimeZone 僅出現在 SELECT 清單中。
  • 一個交易時段收盤價為最後一根常規交易時段分鐘 K 線。美元成交量為分鐘收盤價乘以分鐘成交量，再予以加總。
  • 選擇權到期日、類型與履約價自 OCC 代碼重新解析。權利金名目本金假設為 100 股乘數。
  • 產生作業僅透過管制唯讀路徑進行批次處理；公開頁面絕不查詢即時資料。資料倉儲保留完整逐筆歷史紀錄，無滾動到期機制，因此本分析可隨時從相同資料表重現。資料倉儲狀態截至 2026 年 7 月 4 日。

每個面板都是一個已儲存的物件——圖表、表格與 SQL。可透過 Strasmore 終端機對任何查詢進行延伸分析。

← All NVDA periods
#nvda#nvidia#deepdive#microstructure#options