By 2026年第2季是復甦的一季：在經歷負成長的第1季後，所有主要指數ETF均出現兩位數漲幅，其中以QQQ 26.5% 領先。下方各面板呈現該季的走勢型態、月度階梯圖、利率背景、行事曆，以及兩項資料注意事項（均已內文揭露）。每個數字皆為儲存查詢結果；展開任一面板即可查看對應的SQL語法。
本季表現一覽
第1季到第2季的波動幅度有多大？本表以單一查詢同時計算兩季報酬率，第1季的參考數據是根據相同定義即時重新計算，而非從別處讀取。
每個數據背後的精確 SQL 語法
SELECT ticker,
round((argMaxIf(toFloat64(close), window_start, toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30') AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
/ argMinIf(toFloat64(open), window_start, toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-04-01') AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) - 1) * 100, 1) AS q2_return_pct,
round((argMaxIf(toFloat64(close), window_start, toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-03-31') AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959)
/ argMinIf(toFloat64(open), window_start, toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-01-01') AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) - 1) * 100, 1) AS q1_return_pct,
round(argMaxIf(toFloat64(close), window_start, toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30') AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959), 2) AS q2_close
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
AND window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY ticker
ORDER BY tickerQQQ 本季上漲 26.5%，而第1季為 -6.9%；SPY 本季 14.1%，第1季 -5.2%；IWM 本季 20.2%。所有在第1季下跌的指數，都在第2季收復失土。這四檔指數呈現三種不同走勢：成長型指數在第1季跌幅最深，反彈幅度也最大；DIA 這檔價格加權的工業指數，從 -3.9% 轉為 12.1%；而 IWM 在第1季從未真正下跌（0.1%），因此其 20.2% 的季度表現只是將平淡的起點放大，而非修復跌幅。在單季報酬率欄位中，反彈與動能看起來完全相同；第1季的數據才是區分兩者的關鍵。
本季與歷年第二季的比較
身處復甦季度之中，往往會覺得它深具歷史意義；而數據本身能告訴我們，這一季是否確實如此。本表以同一套運算邏輯，計算出歷史上每一年的四月至六月報酬率（每年計算方式完全相同），再將本季與其他年份進行排名。
每個數據背後的精確 SQL 語法
SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS y,
ticker,
uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions,
round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 1) AS q2_return_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ')
AND window_start >= toDateTime('2003-01-01 00:00:00')
AND window_start < toDateTime('2026-07-01 00:00:00')
AND toMonth(toTimeZone(window_start, 'America/New_York')) BETWEEN 4 AND 6
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY y, ticker
HAVING sessions >= 50
ORDER BY y ASC, ticker ASC每個數據背後的精確 SQL 語法
SELECT ticker,
round(anyIf(ret, y = 2026), 1) AS q2_2026_pct,
arrayCount(x -> x > anyIf(ret, y = 2026), groupArrayIf(ret, y != 2026)) + 1 AS rank_best,
count() AS q2s_compared,
min(y) AS first_year,
anyIf(sessions, y = 2026) AS sessions_2026
FROM (
SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS y,
ticker,
uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions,
(argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS ret
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ')
AND window_start >= toDateTime('2003-01-01 00:00:00')
AND window_start < toDateTime('2026-07-01 00:00:00')
AND toMonth(toTimeZone(window_start, 'America/New_York')) BETWEEN 4 AND 6
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY y, ticker
HAVING sessions >= 50
)
GROUP BY ticker
ORDER BY ticker ASC結果顯示本季接近歷史水準：QQQ的26.5%在17個可比較的第二季中排名第2（第1名為最佳），僅有一個過去的第二季表現更高，上方的年度表格列出了詳細數據。SPY的14.1%在2004年以來的23個第二季中排名第3。有兩點附帶說明：QQQ的歷史資料較短（該基金曾有一段時間以不同的代碼交易，本表以交易日數門檻排除那些年份，並在表格中列出每年的交易日數）；此外，每筆歷史查詢都將時間上限鎖定在本季結束時，因此未來年份加入後，比較範圍不會在無聲中擴大。本頁所有排名的計算基礎：常規交易時段內，開盤至收盤的報酬率。
月度階梯走勢
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, ticker,
round((argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) / argMinIf(toFloat64(open), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) - 1) * 100, 1) AS month_return_pct,
round(argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199), 2) AS month_close
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ')
AND window_start >= toDateTime('2026-04-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')
GROUP BY period_start, ticker
ORDER BY period_start, ticker本季走勢集中於前期：4月貢獻最大漲幅（SPY 9.9%，QQQ 14.8%），5月進一步上揚（4.9% 與 10.3%），6月則小幅回吐，SPY -1.2%。6月回顧詳細記錄了該月表現，包括其下方的漲跌家數分布。
盤面領先者，季度規模
每個數據背後的精確 SQL 語法
SELECT ticker,
round(sum(toFloat64(close) * toFloat64(volume)) / 1e9, 1) AS dollar_bn,
round(100 * sum(toFloat64(close) * toFloat64(volume)) / max(sum(toFloat64(close) * toFloat64(volume))) OVER (), 1) AS pct_of_leader
FROM global_markets.delayed_stocks_minute_aggs
WHERE window_start >= toDateTime('2026-04-01 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 dollar_bn DESC
LIMIT 8就整個季度而言，MU（2047.5億美元）以些微差距超越SPY（2032億美元）位居盤面頂端，這是一檔個股在三個月期間的交易量超過了旗艦指數型基金，差距為該領先者總量的99.2%。其後依序為：QQQ（1658.5億美元），再來是交易量達1591.8億美元的NVDA，其六月交易細節已在此處逐筆解析，以及交易量為1198.8億美元的TSLA。請注意這份清單的性質：這是常規交易時段的成交值，而非績效表現；即便在下跌的月份中，某一檔股票仍可能主導整個盤面。該領先者的六月交易細節已在專題深度分析中逐筆解析。基準期間：4月1日至6月30日常規交易時段；六月清單中有一筆重複代碼的掛牌項目，在實體驗證完成前予以排除（其憑證）。
廣度：每日的市場紋理
每個數據背後的精確 SQL 語法
SELECT countIf(day_ret > 0) AS up_sessions,
countIf(day_ret < 0) AS down_sessions,
countIf(day_ret = 0) AS flat_sessions,
count() AS sessions_total
FROM (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 2) AS day_ret
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime('2026-04-01 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 d
)36 本季共 62 個交易日中，有 26 個交易日收盤時 SPY 上漲，下跌交易日則為 26 個，上漲日佔主導地位，符合兩位數漲幅的季度表現。個股層級的漲跌家數（包含所有上漲與下跌標的）在季度尺度上受到限制：單次全市場掃描所耗用的查詢量，已超出本頁面在（撰寫時測量）所產生的查詢預算。因此，等權重的漲跌家數統計僅限於月度尺度。六月上漲與下跌家數的分佈（其中下跌家數多於上漲家數）收錄於 六月回顧，此處直接揭露此限制，而非默默縮小統計範圍。
選擇權交易量，逐月檢視
本季的市場微觀結構故事，唯有透過涵蓋整個上市選擇權交易量的逐月數據才能完整呈現。交易量在季末攀升：從4月的1386.9百萬口合約，增至6月的1477.9百萬口，後者為本季最繁忙的月份。同日到期（0DTE）合約的佔比也同步上升，從30.3%增至34.3%。6月的佔比是上半年最高，而1月以來的演變詳見上半年回顧。
每個數據背後的精確 SQL 語法
SELECT round(sum(toFloat64(volume)) / 1e6, 1) AS contracts_mm,
round(100.0 * sumIf(toFloat64(volume), toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))) / sum(toFloat64(volume)), 1) AS zero_dte_pct,
uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime('2026-04-01 00:00:00')
AND window_start < toDateTime('2026-05-01 00:00:00')每個數據背後的精確 SQL 語法
SELECT round(sum(toFloat64(volume)) / 1e6, 1) AS contracts_mm,
round(100.0 * sumIf(toFloat64(volume), toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))) / sum(toFloat64(volume)), 1) AS zero_dte_pct,
uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime('2026-05-01 00:00:00')
AND window_start < toDateTime('2026-06-01 00:00:00')每個數據背後的精確 SQL 語法
SELECT round(sum(toFloat64(volume)) / 1e6, 1) AS contracts_mm,
round(100.0 * sumIf(toFloat64(volume), toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))) / sum(toFloat64(volume)), 1) AS zero_dte_pct,
uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS sessions
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime('2026-06-01 00:00:00')
AND window_start < toDateTime('2026-07-01 00:00:00')交易成本，按月抽樣
每個數據背後的精確 SQL 語法
SELECT toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS session,
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), 3) AS med_spread_bps,
round(count() / 1e6, 2) AS quote_updates_m,
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 = 'SPY'
AND ((sip_timestamp >= toDateTime64('2026-04-15 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-04-15 20:00:00', 9))
OR (sip_timestamp >= toDateTime64('2026-05-13 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-05-13 20:00:00', 9))
OR (sip_timestamp >= toDateTime64('2026-06-10 13:30:00', 9) AND sip_timestamp < toDateTime64('2026-06-10 20:00:00', 9)))
GROUP BY session
ORDER BY session ASCSPY在本季每月抽樣交易時段的中位報價價差：4月樣本為0.286個基點，5月為0.27，6月為0.409，6月樣本為最寬。基礎說明：採用單一標示的抽樣交易時段（每月第二個星期三），而非全月中位數；無效報價計入樣本組，不予以剔除。
利率：殖利率曲線趨平的季度
每個數據背後的精確 SQL 語法
SELECT toString(date) AS d,
round(yield_10_year, 2) AS y10,
round((yield_10_year - yield_2_year) * 100, 0) AS spread_2s10s_bp
FROM global_markets.treasury_yields
WHERE date >= toDate('2026-04-01') AND date <= toDate('2026-06-30')
AND isNotNull(yield_10_year) AND isNotNull(yield_2_year)
ORDER BY date2年期與10年期公債利差在本季初為52個基點，季末收在30，呈現趨平格局，10年期殖利率最終落在4.44%。關於這六個月的完整敘述，請參閱上半年回顧。從機制上來說，趨平意味著短天期利率縮小了與長天期利率的差距；至於此趨勢是否延續，這張表格無法提供答案，本頁面也不試圖探討。
行事曆，季度規模
每個數據背後的精確 SQL 語法
SELECT
(SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date >= toDate('2026-04-01') AND ex_dividend_date <= toDate('2026-06-30')) AS ex_div_events,
(SELECT count() FROM global_markets.stocks_splits WHERE execution_date >= toDate('2026-04-01') AND execution_date <= toDate('2026-06-30')) AS splits,
(SELECT count() FROM global_markets.stocks_ipos WHERE listing_date >= toDate('2026-04-01') AND listing_date <= toDate('2026-06-30')) AS ipos,
(SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date >= toDate('2026-04-01') AND filing_date <= toDate('2026-06-30')) AS q2_filings,
(SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = toDate('2026-04-30')) AS filings_apr30,
(SELECT uniqExact(accession_number) FROM global_markets.stocks_sec_edgar_index WHERE filing_date = toDate('2026-06-30')) AS filings_jun30105 家公司在該季度掛牌上市，435 次股票分割執行，以及 15402 次除息事件完成支付。申報數量（235075）反映出已揭露的缺口：該指數在季度最後一天（6月30日）僅持有 31 份申報文件，在4月30日則持有 34 份，相較於鄰近日期的數千份文件，因此季度總數少了兩個月底交易日，在資料回補前會被低估。月底缺口有其專屬的診斷說明。
日曆逐步逼近季末
每個數據背後的精確 SQL 語法
SELECT m, ipos, splits, ex_divs FROM (
SELECT '2026-04' AS m,
(SELECT count() FROM global_markets.stocks_ipos WHERE listing_date >= toDate('2026-04-01') AND listing_date <= toDate('2026-04-30')) AS ipos,
(SELECT count() FROM global_markets.stocks_splits WHERE execution_date >= toDate('2026-04-01') AND execution_date <= toDate('2026-04-30')) AS splits,
(SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date >= toDate('2026-04-01') AND ex_dividend_date <= toDate('2026-04-30')) AS ex_divs, 1 AS o
UNION ALL SELECT '2026-05',
(SELECT count() FROM global_markets.stocks_ipos WHERE listing_date >= toDate('2026-05-01') AND listing_date <= toDate('2026-05-31')),
(SELECT count() FROM global_markets.stocks_splits WHERE execution_date >= toDate('2026-05-01') AND execution_date <= toDate('2026-05-31')),
(SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date >= toDate('2026-05-01') AND ex_dividend_date <= toDate('2026-05-31')), 2
UNION ALL SELECT '2026-06',
(SELECT count() FROM global_markets.stocks_ipos WHERE listing_date >= toDate('2026-06-01') AND listing_date <= toDate('2026-06-30')),
(SELECT count() FROM global_markets.stocks_splits WHERE execution_date >= toDate('2026-06-01') AND execution_date <= toDate('2026-06-30')),
(SELECT count() FROM global_markets.stocks_dividends WHERE ex_dividend_date >= toDate('2026-06-01') AND ex_dividend_date <= toDate('2026-06-30')), 3
) ORDER BY o隨著季度推進，企業行事曆逐漸收緊：除息事件逐月增加，從4月的3947件攀升至6月的6651件；股票分割也同步增加（從129件增至164件）。上市數量在這三個月內保持穩定，所謂的浪潮指的是股息，而非IPO。
盤後收盤摘要
每個數據背後的精確 SQL 語法
SELECT
(SELECT uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-04-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')) AS q2_sessions,
(SELECT uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-04-01 00:00:00') AND window_start < toDateTime('2026-05-01 00:00:00')) AS april_sessions,
(SELECT uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-05-01 00:00:00') AND window_start < toDateTime('2026-06-01 00:00:00')) AS may_sessions,
(SELECT uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= toDateTime('2026-06-01 00:00:00') AND window_start < toDateTime('2026-07-01 00:00:00')) AS june_sessions62 個交易日，係根據實際觀察到的K線確認，而非依行事曆推估：4月21 個、5月20 個（陣亡將士紀念日）、6月21 個（六月節）。各月層級的收盤摘要與休市依據，詳見6月回顧與假日說明。
資料說明
完整資料說明
方法論
- 期間為2026年4月1日至6月30日，共62個交易日，並以實際K線驗證。季度報酬率計算方式為：期間內首個常規交易時段開盤價至最後一個常規交易時段收盤價；第1季對比數據則以相同定義重新計算。
- 時間戳記以UTC儲存，並以原始UTC邊界進行篩選；常規交易時段為UTC 13:30–20:00（對應美東夏令時間季度）。美元成交量計算方式為：常規交易時段內每分鐘收盤價乘以每分鐘成交量。多年歷史區塊則以美東標準時間（依各列轉換，採用跨越數十年的日光節約時間安全慣例）篩選常規交易時段，並將上限鎖定於本季度末；深度驗證（可追溯至2003年9月的分鐘歷史）之方法論詳見上半年回顧。
- 資料生成透過唯讀閘道路徑執行；公開頁面從不查詢即時資料。資料倉儲狀態截至2026年7月5日。