Strasmore Research
Deep Dives · Matt ConnorBy Matt Connor · · Updated 2026-07-23

NVDA: NVIDIA 2026年6月行情

2026年6月行情回顾：盘前触及 $235，7.4% 个交易日内下跌 21，成交额达 fourth 级规模。

NVIDIA 在 2026 年 6 月开盘价为 $215.77，收盘价为 $199.76 —— 在 21 个交易日内下跌了 -7.4%。该股在 2026-06-02 04:00 ET 的盘前交易中达到 $235 的峰值；在 2026-06-02 09:59 ET 达到常规交易时段高点 $232.28；并在 2026-06-29 10:17 ET 跌至 $189.8 —— 以上均为常规交易时段数据。总成交量为 2.75 十亿股，成交金额为 $571.9 十亿美元 —— 按常规交易时段成交金额计算，这是美国股市中 fourth 最大的个股（基准：6 月 1 日至 30 日常规交易时段；排除一个待核实实体的重复代码 6 月上市个股）。此处所有数据均为存储查询结果；如需查看确切 SQL，请展开相关面板。

查询单月数据：开盘、收盘、极值、成交量及汇总
每个数字背后的完整 SQL
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')

走势呈现持续下跌趋势，并在最后一周出现一次剧烈的跳空下跌。NVDA 仅有一次收盘价高于 $224.43 —— 即 2026-06-01 的首个交易日。常规交易时段的月内低点出现在 2026-06-29 10:17 ET，该分钟内波动幅度仅为 1，成交量为 43131。2026-06-02 04:00 ET 的盘前峰值 $235 为盘外交易数据；常规交易时段高点 $232.28 出现在 2026-06-02 09:59 ET。由于 6 月 19 日全市场休市（当日 SPY 仅有 0 个 K 线），NVDA 共经历了 21 个交易日。

交易时段回顾

查询21个交易时段：常规时段收盘、环比变化、全天成交量
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,
    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

交易走势呈现持续下滑态势。首个收盘价突破 $224.43，并于 2026-06-01 创下历史新高。2026-06-05（周五）出现单日最大跌幅，跌幅达 -6.2%，且当日成交量达到本月最高的 187.3 百万股。关键的下跌区间为 2026-06-22 至 2026-06-26，连续 5 个交易日下跌，最终收于本月最低点 $191.72；随后两个交易日分别反弹了 1.7% 和 2.5%。成交量集中在前期：首日成交 185.5 百万股，最后一天成交 119.6 百万股。

查询五日跌幅区间：连续下跌趋势中的各项指标
每个数字背后的完整 SQL
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

6月表现与过去六个月对比

对于 NVDA 而言，这样的月份表现属于异常还是常态？下表对过去六个月的各项指标进行了统一计算。6 月的数据是通过与前五个月完全相同的查询指令，在生成时直接从数据仓库获取的。

查询滚动六个月实时数据：成交额、股数及月收益率
每个数字背后的完整 SQL
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

从成交额来看，6 月表现平平：常规交易时段的成交额为 $523 十亿，处于该时间段的中等水平，低于 5 月的 $557.5 十亿和 3 月的 $572.5 十亿。收益率列则是 6 月的异常点：-7.4% 是这六个月中单月跌幅最大的，相比之下，2 月的跌幅为 -4.8%，而 4 月和 5 月则实现了增长。

fourth 交易额最大的股票

查询全美市场排名（按2026年6月常规时段成交额计）
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,
    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

按常规交易时段美元成交额计算，NVDA 在全美股市中排名第 fourth：$523 十亿。它领先排名第 SNDK 的股票 $141.5 十亿。仅次于 MU ($995.7 十亿)、SPY ($771.5 十亿) 和 QQQ ($672.8 十亿)。统计基准为 6 月 1 日至 30 日的常规交易时段，已排除一项待身份核实的重复代码股票——详情请参阅 深度分析报告。在排名高于 NVDA 的三只股票中，1 为个股，MU 为另一家半导体公司，其余两只为大型指数 ETF。

查询排名详情：NVDA排名、领先优势及依据
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 = '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
)

交易行情分析

查询NVDA成交明细：成交笔数、单笔规模及报价统计
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 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)

行情特征表现为成交量小且报价密集：55.64 百万笔成交，中位数为 5 股（均值为 72.9 —— 机构大宗交易推高了均值），84.6% 为零碎股（不足 100 股），32.91% 为碎股——这与零售交易应用将订单拆分至 做市商 库存的行为一致。报价方面：55.7 百万次 NBBO 更新，99.35% 为双向报价；33941 次出现价交叉（买价高于卖价），329679 次出现价锁定（买卖价相等），63 次为单向报价或无报价。大型股单月的报价频率甚至超过许多个股十年的总和。

价差保持稳定

像 NVDA 这样的超大市值股票具有结构性的窄 买卖价差 —— 问题在于，在价格波动达 20 点的月份中，这种紧凑性是否保持稳定。上方的报价统计显示了月度中位数；本图表展示的是每日数据。

查询时段价差：常规时段中位数与时间加权平均值 (bps)
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 = '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

全月价差始终保持在窄幅区间内：1.34 bps（2026-06-01 日）和 1.01 bps（2026-06-30 日）—— 在价格下跌 20 点的过程中，该超大市值股票的价差几乎没有变动。价差最宽的交易日为 0.97 bps（2026-06-05 日，即 -6.2% 下跌日），最窄的为 0.95 bps（2026-06-15 日）。若要对比流动性较低的股票，请参阅 6 月 29 日微观结构深度分析，该报告包含同一交易日的单股价差图表。

Options: 64.64 million contracts, calls every session

查询NVDA期权市场概览：总量、到期结构及核心合约
每个数字背后的完整 SQL
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)

In 21 option sessions: 8.9 million prints across 5163 distinct contracts, 64.64 million contracts and $24.43 billion in premium (price times the 100-share multiplier). The month put/call ratio was 0.55 — calls out-traded puts every single session; the daily ratio peaked at 0.782 and never reached 1.0. 38 expiries traded, from the June 18 weekly out to 2028-12-15 LEAPS; the June 18 expiry alone took 10.5% of month volume. Busiest contract: $210 call, expiry 2026-06-18. Premium magnet: $0.5 call, expiry 2026-12-18 — a deep-in-the-money $0.5 strike. For comparison, AAPL options collected $8.84 billion on 27 million contracts in June; TSLA $33.68 billion on 58 million.

查询期权逐时数据：合约数、看涨/看跌分布及看跌/看涨比率
每个数字背后的完整 SQL
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

The busiest options session was 2026-06-05 — 5298529 contracts, 100% of the month's peak — the same -6.2% decline day that posted the highest equity volume. The put/call ratio rose alongside the price decline: it bottomed at 0.33 on 2026-06-02 (near the price peak) and climbed to 0.61 by 2026-06-12 (the session the stock first closed below $205.14). Put volume grew as the price fell — hedging activity or directional bets; the data shows the co-movement, not the intent.

查询合约分布：各行权价区间的看涨与看跌成交量
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,
    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))

The strike map is a barbell around the $200 trading range. The $200 bucket — at the money — took the most volume, split 32.7% puts (two-way traffic). Below the range puts dominate (88.3% of the $150 bucket); above it calls own the book (6.3% puts at $225, 120039 contracts at the $450 ceiling). The structure is textbook: protective puts below, speculative calls above, a two-way market at the money.

新闻流

查询信息流概览：成交量、构成及关联标签
每个数字背后的完整 SQL
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')

642 6 月份来自 4 的 NVDA 相关文章。请谨慎对待这些数据：仅 The Motley Fool 一家机构就撰写了 63% 的文章——这仅代表该信息源的关注度，而非全球媒体的整体情况。文章发布高峰出现在 2026-06-01，共有 45 篇。共同标签反映了报道侧重点：MSFT 占比 169，AAPL 占比 134，AMD 占比 101，TSLA 占比 69。该信息源将 NVDA 视为大型科技股新闻进行报道，而非单纯的半导体新闻。

空头头寸

查询FINRA场外逐时卖空成交量：卖空股数及报告成交量
每个数字背后的完整 SQL
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

场外做空成交量是指 FINRA 报告的做空标记成交量；其中大部分是 做市商为满足客户买盘而进行的卖空 —— 这属于常规交易流程，而非做空意图。NVDA 的做空标记占比从 2026-06-01 日的 29.3% 波动至 2026-06-30 日的 48.1。在记录的 20 个交易日中，场外报告成交量在 2026-06-02 日达到 86.77 百万股的峰值，在 2026-06-16 日降至 43.31 百万股的低点。

查询场外卖空峰值与谷值（按交易时段去重）
每个数字背后的完整 SQL
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
)
查询6月中旬卖空头寸数据
每个数字背后的完整 SQL
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')

实际卖空头寸为 2026-06-30：做空 310.13 百万股，对应平均日成交量为 155.99 百万股。供应商报告的平仓天数为 1.99；原始比例为 1.99 —— 做空方大约需要两个平均交易日即可完成平仓。本月两次结算数据均已记录（2 月份数据）；上述数据包含 6 月 30 日月底的结算数据。

数据说明

查询NVDA基本面统计：资产负债表、损益表、现金流量表
每个数字背后的完整 SQL
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
完整数据说明
  • 实体。 NVDA 指 NVIDIA Corporation，CIK 0001045810，在 Nasdaq 上市。不存在代码重用歧义；不适用实体边界限制。数据库包含 NVDA 的 83 行资产负债表、152 行损益表和 152 行现金流量表——基本面数据完整，不同于 6月29日微观结构深度解析 的情况。
  • 月度极值。 月度最高价为 $235，出现在东部时间 2026-06-02 04:00 的盘前交易（凌晨 4:00）；常规交易时段最高价为 $232.28，出现在东部时间 2026-06-02 09:59。月度最低价与常规交易时段最低价均为 $189.8 —— 该低点出现在常规交易时段。
  • 6月19日收盘。 数据库包含 6月19日（六月节）的 0 个 SPY K线，因此 NVDA 的 6月数据跨越 21 个交易日。节假日表未追溯至 2026年6月（其起始日期为 2026年7月3日）；零 K线观测值为接收记录。
  • 成交金额。 将每分钟的收盘价乘以成交量并求和——作为名义成交额的收盘加权代理指标。常规交易时段金额（$523 十亿）不包括盘前和盘后 K线；全天金额（$571.9 十亿）包含这些时段。
  • 期权解析。 到期日、类型和行权价重新从 OCC 代码中解析（表格中的 expiration_date 列不可靠）；权利金名义价值基于 100 股乘数计算。
  • 单次更新价差统计。 每次 NBBO 更新的权重相等；面板中包含时间加权统计数据。中位数采用确定性分位数计算。
  • 未触发 Tick-dump 保护。 所有 Tick 表查询均为聚合计算；交易纹理查询将整个交易表汇总为单行。
  • 6月29日卖空成交量缺口。 6月29日 FINRA 场外卖空成交量文件在全市场范围内被截断（源文件在字母表中间结束）；NVDA 的排序位于截断点之前，因此该行数据缺失。卖空成交量面板包含 20 个交易日；6月29日的数据缺失（由于全市场文件截断），而非为零。6月29日深度解析 包含全市场探测的接收记录。

方法论

  • 时间戳以 UTC 格式存储，并使用原始 UTC 范围进行过滤；2026 年 6 月完全采用 EDT，因此常规交易时间为 13:30–20:00 UTC（美东时间 9:30 am–4:00 pm）。toTimeZone 仅出现在 SELECT 列表中。
  • 会话结束定义为常规交易时间内的最后一根分钟 K 线。成交金额为每分钟收盘价乘以每分钟成交量后的总和。
  • 期权到期日、类型和行权价通过 OCC 代码重新解析。名义权利金基于 100 股乘数计算。
  • 数据仅通过受限的只读路径进行批量生成；公开页面从不查询实时数据。数据仓库保留完整的逐笔历史记录且不进行滚动过期，因此任何时间进行此分析都能重现相同结果。数据仓库状态截至 2026 年 7 月 4 日。

每个面板均为一个存储对象——包含图表、表格和 SQL。如需进一步查询，请使用 Strasmore 终端。

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