Strasmore Research
市场回顾 Matt Connor作者: Matt Connor · 更新于 2026-10-17 · data as of October 17, 2026 · refreshed weekly

每月派息股票完整名单

根据实际派息记录筛选美国上市月度派息股票,查看哪些股票过去十二个月确实派息十至十四次及当前收益率,按成交额排序。

月度派息股票每月发放现金股息,而不是每季一次。真正符合条件的股票远少于各类榜单文章所暗示的数量。我们直接筛查实际派息记录,而不是依赖数据供应商的标签:在过去十二个月内,1590只在美国上市的ticker完成了十至十四次定期现金派息,其中仅35只具备公司基本面记录。本页所有数据均按Oct 16交易日的收盘价计价。

月度派息股票名单

以下每只股票都来自在美国上市并提交监管文件的公司,过去十二个月内记录了十至十四次定期现金派息,且日均股票成交额至少为一百万美元。排名依据为日均成交额。

查询按月派息股票——每月派息的申报公司,按日交易额排名
31 rows (showing 20)
股票代码月度支付额(美元)年化收益率(%)按月支付年数日均成交额(百万美元)价格截至
O0.27155.8114.3351.5Oct 16
AGNC0.1216.4812294.8Oct 16
DOC0.10176.431.683.1Oct 16
ADC0.2674.775.875.1Oct 16
DX0.1718.637.773.7Oct 16
ARR0.2421.796.353.4Oct 16
ORC0.124.0713.532.1Oct 16
EPR0.316.675.231.4Oct 16
PECO0.1153.615.230.5Oct 16
APLE0.085.584.825.6Oct 16
MAIN0.2655.8714.122.7Oct 16
SMA0.13154.61.419.6Oct 16
LTC0.195.1814.318.9Oct 16
IVR0.1225.920.718.1Oct 16
EFC0.1313.327.416.8Oct 16
TRIN0.1712.60.813.9Oct 16
PSEC0.03526.351411.4Oct 16
CSWC0.193410.031.311.3Oct 16
PFLT0.0814.5614.24.8Oct 16
GOOD0.19.5514.34.3Oct 16
每个数字背后的完整 SQL
SELECT m.ticker AS ticker,
       round(m.latest_payment, 4) AS monthly_payment_usd,
       round(100 * m.latest_payment * 12 / l.last_close, 2) AS annual_yield_pct,
       round(dateDiff('day', s.streak_start, s.last_ex) / 365.25, 1) AS years_paying_monthly,
       round(l.adv_usd / 1e6, 1) AS avg_daily_traded_musd,
       formatDateTime(l.last_session, '%b %e') AS priced_through
FROM (
    SELECT ticker, argMax(cash_amount, ex_dividend_date) AS latest_payment
    FROM global_markets.stocks_dividends
    WHERE ex_dividend_date > today() - 365
      AND ex_dividend_date <= today()
      AND cash_amount > 0
      AND distribution_type = 'recurring'
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','TQQQ','SQQQ','NVDL','NVDS','NVD','TSLL','TSLQ','TSLZ','SPXL','SPXS','UPRO','SPXU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','SOXY','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','BITX','ETHU','MSTX','MSTU','CONL','DUST','JNUG','JDST','NUGT')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN today() - 400 AND today())
    GROUP BY ticker
    HAVING count() BETWEEN 10 AND 14
       AND argMax(frequency, ex_dividend_date) = 12
) AS m
INNER JOIN (
    SELECT ticker,
           maxIf(ed, gap_days > 70) AS streak_start,
           max(ed) AS last_ex
    FROM (
        SELECT ticker, ex_dividend_date AS ed,
               dateDiff('day',
                        lagInFrame(ex_dividend_date) OVER (PARTITION BY ticker ORDER BY ex_dividend_date),
                        ex_dividend_date) AS gap_days
        FROM (
            SELECT ticker, ex_dividend_date
            FROM global_markets.stocks_dividends
            WHERE distribution_type = 'recurring' AND cash_amount > 0 AND ex_dividend_date <= today()
            GROUP BY ticker, ex_dividend_date
        )
    )
    GROUP BY ticker
) AS s ON s.ticker = m.ticker
INNER JOIN (
    SELECT ticker,
           avg(dollar_vol) AS adv_usd,
           argMax(close_px, d) AS last_close,
           max(d) AS last_session,
           count() AS sessions
    FROM (
        SELECT ticker,
               toDate(toTimeZone(window_start, 'America/New_York')) AS d,
               sum(toFloat64(close) * volume) AS dollar_vol,
               argMax(toFloat64(close), window_start) AS close_px
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE window_start >= toDateTime(today() - 32)
          AND toDate(toTimeZone(window_start, 'America/New_York')) < today()
          AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
              + toMinute(toTimeZone(window_start, 'America/New_York')) >= 570
          AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
              + toMinute(toTimeZone(window_start, 'America/New_York')) < 960
        GROUP BY ticker, d
    )
    GROUP BY ticker
    HAVING sessions >= 15 AND adv_usd >= 1000000 AND last_close > 0
) AS l ON l.ticker = m.ticker
INNER JOIN (
    SELECT ticker
    FROM global_markets.stocks_ratios
    GROUP BY ticker
    HAVING argMax(market_cap, date) > 0
) AS f ON f.ticker = m.ticker
ORDER BY l.adv_usd DESC
LIMIT 60
自己运行这个查询

O 是此名单中成交最活跃的月度派息股票:每月派息为 0.2715 美元,已有 14.3 年连续按月派息记录;按其 Oct 16 收盘价计算,年化收益率为 5.81%。其日均股票成交额为 351.5 百万美元。筛选结果包含 31 只股票。收益率一栏将最新单次派息按每年十二次进行年化,再除以该收盘价,因此会随股价变动。它不是对未来十二个月现金派息的预测。

在除息日前持有股票,才能获得下一笔股息。即将到来的除息日日历列出下一批进入除息交易的股票;除息日释义介绍决定买方能否获得股息的截止时间。

如何识别按月分配的产品

股息数据流会标注分配频率,但仅依赖这一标签会在两个方向上都得出错误结论。这里的测试统计某个 ticker 实际完成的分配次数,并同时设置最低和最高门槛。

查询过去一年各股票的定期现金派付——月度区间所在位置
分组股票代码标记为月度公司申报文件
One a year33876234
Two a year29944136
Three to six a year45381891483
Seven to nine a year1571533
Ten to fourteen a year1590158135
Fifteen to thirty-nine a year6400
Forty or more a year12200
每个数字背后的完整 SQL
WITH payers AS (
    SELECT ticker,
           count() AS payments_12m,
           argMax(frequency, ex_dividend_date) AS freq_flag
    FROM global_markets.stocks_dividends
    WHERE ex_dividend_date > today() - 365
      AND ex_dividend_date <= today()
      AND cash_amount > 0
      AND distribution_type = 'recurring'
      AND ticker NOT IN ('SPCX')
    GROUP BY ticker
),
filers AS (
    SELECT ticker
    FROM global_markets.stocks_ratios
    GROUP BY ticker
    HAVING argMax(market_cap, date) > 0
)
SELECT multiIf(payments_12m = 1, 'One a year',
               payments_12m = 2, 'Two a year',
               payments_12m BETWEEN 3 AND 6, 'Three to six a year',
               payments_12m BETWEEN 7 AND 9, 'Seven to nine a year',
               payments_12m BETWEEN 10 AND 14, 'Ten to fourteen a year',
               payments_12m BETWEEN 15 AND 39, 'Fifteen to thirty-nine a year',
               'Forty or more a year') AS bucket,
       count() AS tickers,
       countIf(freq_flag = 12) AS labelled_monthly,
       countIf(ticker IN (SELECT ticker FROM filers)) AS company_filings
FROM payers
GROUP BY bucket
ORDER BY min(payments_12m)
自己运行这个查询

122 个 ticker 在过去一年中实际完成了四十次或以上的定期现金分配,另有 64 个完成了十五至三十九次。这些产品按周或按日分配,属于基金市场中增长迅速的细分领域。若筛选条件只有“十次或以上分配”,它们都会被纳入按月分配名单。将次数上限设为十四次即可排除这些产品。

仅看标签同样不够可靠。标注为按月分配频率的 ticker 中,有 62 个在过去一年中恰好只分配了一次,另有 189 个分配了三至六次。在十至十四次的区间内,标签与实际记录有 1581 次一致,占 1590 次中的相应比例,因此本页面要求同时满足两项条件。

大多数月度分配标的是基金,而非经营性公司

这是其他榜单文章通常略过的部分。该数据库没有基金、ETF或REIT类型标签,因此月度分配标的列表无法按标签筛选出经营性公司。但数据库包含公司基本面数据,可为其覆盖的经营性公司提供市值。交易所交易基金和封闭式基金不在该数据覆盖范围内。因此,在本页中,是否存在市值记录,是判断标的是否为经营性公司的实际替代指标。在月度分配区间的1590个ticker中,35个有市值记录。其余标的没有此类记录。它们大多是交易所交易基金、封闭式基金和区间基金,此外还包括一些该数据源未覆盖的份额类产品、信托和规模较小的发行人。

少数提交基本面数据的标的,主要是房地产投资信托、抵押贷款REIT、商业发展公司和特许权使用费信托。月度收入标的的真实构成就是如此:能够每月派发现金的企业形式,本身就被设计为将现金直接向投资者分配。普通经营性企业通常按季派息,因此,类似持续两十年增长股息的标杆公司的月度版本几乎不存在。美国为何最初形成按季派息的惯例,以及哪些企业结构打破了这一惯例,详见月度股息股票详解。

月度分红股票的收益率

月度分红股票的收益率差异远大于整个市场。该表将所有达到流动性门槛、且拥有完整一年价格历史的月度分红股票分组,并增加了收益率筛选通常不会展示的一列:过去十二个月股价的表现。

查询高流动性按月派息股票的收益率分布,以及各区间12个月价格变动中位数
分组支付方收益率中位数(%)过去12个月价格变动中位数(%)公司申报文件
Under 3%772.44-1.11
From 3% to 5%3164.2-4.43
From 5% to 8%2416.2-4.89
From 8% to 12%1289.22-7.23
Above 12%9314.73-15.115
每个数字背后的完整 SQL
WITH monthly AS (
    SELECT ticker, argMax(cash_amount, ex_dividend_date) AS latest_payment
    FROM global_markets.stocks_dividends
    WHERE ex_dividend_date > today() - 365
      AND ex_dividend_date <= today()
      AND cash_amount > 0
      AND distribution_type = 'recurring'
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','TQQQ','SQQQ','NVDL','NVDS','NVD','TSLL','TSLQ','TSLZ','SPXL','SPXS','UPRO','SPXU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','SOXY','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','BITX','ETHU','MSTX','MSTU','CONL','DUST','JNUG','JDST','NUGT')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN today() - 400 AND today())
    GROUP BY ticker
    HAVING count() BETWEEN 10 AND 14
       AND argMax(frequency, ex_dividend_date) = 12
),
filers AS (
    SELECT ticker
    FROM global_markets.stocks_ratios
    GROUP BY ticker
    HAVING argMax(market_cap, date) > 0
),
tape AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           sum(toFloat64(close) * volume) AS dollar_vol,
           argMax(toFloat64(close), window_start) AS close_px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN (SELECT ticker FROM monthly)
      AND (window_start >= toDateTime(today() - 32)
           OR (window_start >= toDateTime(today() - 378) AND window_start < toDateTime(today() - 358)))
      AND toDate(toTimeZone(window_start, 'America/New_York')) < today()
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
          + toMinute(toTimeZone(window_start, 'America/New_York')) >= 570
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
          + toMinute(toTimeZone(window_start, 'America/New_York')) < 960
    GROUP BY ticker, d
),
px AS (
    SELECT ticker,
           avgIf(dollar_vol, d > today() - 32) AS adv_usd,
           argMaxIf(close_px, d, d > today() - 32) AS last_close,
           argMaxIf(close_px, d, d <= today() - 358) AS close_year_ago,
           countIf(d > today() - 32) AS recent_sessions,
           countIf(d <= today() - 358) AS old_sessions
    FROM tape
    GROUP BY ticker
    HAVING recent_sessions >= 15
       AND old_sessions > 0
       AND adv_usd >= 1000000
       AND last_close > 0
       AND close_year_ago > 0
),
named AS (
    SELECT m.ticker AS ticker,
           100 * m.latest_payment * 12 / p.last_close AS yld,
           100 * (p.last_close - p.close_year_ago) / p.close_year_ago AS price_change,
           m.ticker IN (SELECT ticker FROM filers) AS is_filer
    FROM monthly m
    INNER JOIN px p ON p.ticker = m.ticker
)
SELECT multiIf(yld < 3, 'Under 3%',
               yld < 5, 'From 3% to 5%',
               yld < 8, 'From 5% to 8%',
               yld < 12, 'From 8% to 12%',
               'Above 12%') AS bucket,
       count() AS payers,
       round(quantileDeterministic(0.5)(yld, cityHash64(ticker)), 2) AS median_yield_pct,
       round(quantileDeterministic(0.5)(price_change, cityHash64(ticker)), 1) AS median_price_change_12m_pct,
       countIf(is_filer) AS company_filings
FROM named
GROUP BY bucket
ORDER BY median_yield_pct
自己运行这个查询

最大的一组是 From 3% to 5%,包含 316只股票;相比之下,From 5% to 8%组包含 241只,Under 3%组包含 77只。收益率中位数从最低组的 2.44% 稳步升至最高组的 14.73%。

现在看旁边的股价列。最低收益率组的十二个月股价变化中位数为 -1.1%,From 3% to 5%组为 -4.4%,随后在 Above 12%组变为 -15.1%。收益率的分母是股价,因此股票即使分红金额不变,也可能因股价下跌而进入最高收益率组。极高的收益率通常反映的是股价下跌带来的算术结果,而不是分红方慷慨。股息收益率与国债收益率的比较说明了高收益率需要满足哪些条件。

收益率超过12%的标的

任何月度派息、收益率大致超过12%的标的,都值得进一步研究。以下是申报公司中达到这一标准的标的,以及过去一年股价和月度派息的变化。

查询收益率超过12%的按月派息股票——股价变动与派息变动共同揭示这一数字
股票代码年化收益率(%)过去12个月价格变动(%)过去12个月支付变动(%)日均成交额(百万美元)
OXSQ31.84-28.501.5
EARN27.46-33.801.6
PSEC26.35-41.7-22.211.6
IVR25.92-24.6-64.718
ORC24.07-33-16.732.1
ARR21.79-17.1053.7
SAR19.93-33.502.4
DX18.63-17.2074.1
CION18.22-30.6-72.21.8
HRZN16.69-27.4-45.51.6
AGNC16.48-13.30296.2
PNNT15.69-52.8-501.4
PFLT14.56-26.4-224.8
EFC13.32-13.1017
TRIN12.68.1-66.714
每个数字背后的完整 SQL
WITH monthly AS (
    SELECT ticker,
           argMax(cash_amount, ex_dividend_date) AS latest_payment,
           argMin(cash_amount, ex_dividend_date) AS oldest_payment
    FROM global_markets.stocks_dividends
    WHERE ex_dividend_date > today() - 400
      AND ex_dividend_date <= today()
      AND cash_amount > 0
      AND distribution_type = 'recurring'
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','TQQQ','SQQQ','NVDL','NVDS','NVD','TSLL','TSLQ','TSLZ','SPXL','SPXS','UPRO','SPXU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','SOXY','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','BITX','ETHU','MSTX','MSTU','CONL','DUST','JNUG','JDST','NUGT')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN today() - 400 AND today())
    GROUP BY ticker
    HAVING countIf(ex_dividend_date > today() - 365) BETWEEN 10 AND 14
       AND argMax(frequency, ex_dividend_date) = 12
       AND oldest_payment > 0
),
filers AS (
    SELECT ticker
    FROM global_markets.stocks_ratios
    GROUP BY ticker
    HAVING argMax(market_cap, date) > 0
),
tape AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           sum(toFloat64(close) * volume) AS dollar_vol,
           argMax(toFloat64(close), window_start) AS close_px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN (SELECT ticker FROM monthly)
      AND (window_start >= toDateTime(today() - 32)
           OR (window_start >= toDateTime(today() - 378) AND window_start < toDateTime(today() - 358)))
      AND toDate(toTimeZone(window_start, 'America/New_York')) < today()
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
          + toMinute(toTimeZone(window_start, 'America/New_York')) >= 570
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60
          + toMinute(toTimeZone(window_start, 'America/New_York')) < 960
    GROUP BY ticker, d
),
px AS (
    SELECT ticker,
           avgIf(dollar_vol, d > today() - 32) AS adv_usd,
           argMaxIf(close_px, d, d > today() - 32) AS last_close,
           argMaxIf(close_px, d, d <= today() - 358) AS close_year_ago,
           countIf(d > today() - 32) AS recent_sessions,
           countIf(d <= today() - 358) AS old_sessions
    FROM tape
    GROUP BY ticker
    HAVING recent_sessions >= 15
       AND old_sessions > 0
       AND adv_usd >= 1000000
       AND last_close > 0
       AND close_year_ago > 0
)
SELECT m.ticker AS ticker,
       round(100 * m.latest_payment * 12 / p.last_close, 2) AS annual_yield_pct,
       round(100 * (p.last_close - p.close_year_ago) / p.close_year_ago, 1) AS price_change_12m_pct,
       round(100 * (m.latest_payment - m.oldest_payment) / m.oldest_payment, 1) AS payment_change_12m_pct,
       round(p.adv_usd / 1e6, 1) AS avg_daily_traded_musd
FROM monthly m
INNER JOIN px p ON p.ticker = m.ticker
INNER JOIN filers f ON f.ticker = m.ticker
WHERE 100 * m.latest_payment * 12 / p.last_close >= 12
ORDER BY annual_yield_pct DESC
LIMIT 25
自己运行这个查询

15只标的达到这一门槛。OXSQ的年化收益率最高,为31.84%;其股价在过去十二个月上涨-28.5%,月度派息变动0%。EARN紧随其后,收益率为27.46%;股价变动-33.8%,派息变动0%。派息削减和股价下跌经常同时出现在同一标的上,收益率也会因此同步上升。

单独看收益率并不完整,这正是什么是股息收益率一文要全面解释的内容。

Realty Income月度股息逐年变化

Realty Income是这一类别的参考标的,也是读者了解月度股息时通常首先关注的公司。下表列出其已宣布的月度股息率、每个自然年度内宣布的最高派息额、较前一年的增幅,以及该年度内上调股息率的次数:

查询Realty Income按日历年度公布的月度派息率、较上年的增幅及各年度内的上调步骤
年份月度支付额(美元)年度加息百分比加息次数最小年度加息百分比
20140.18340.6940.69
20150.1914.1350.69
20160.20256.0260.69
20170.21254.9450.69
20180.221450.69
20190.22752.9450.69
20200.23453.0850.69
20210.24655.1250.69
20220.24850.8140.69
20230.25653.2250.69
20240.26352.7340.69
20250.272.4760.69
每个数字背后的完整 SQL
WITH steps AS (
    SELECT ed, amt,
           lagInFrame(amt) OVER (ORDER BY ed ASC) AS prior_amt
    FROM (
        SELECT ex_dividend_date AS ed, max(cash_amount) AS amt
        FROM global_markets.stocks_dividends
        WHERE ticker = 'O'
          AND distribution_type = 'recurring'
          AND cash_amount > 0
          AND ex_dividend_date >= '2013-01-01'
          AND ex_dividend_date < toStartOfYear(today())
        GROUP BY ed
    )
),
yearly AS (
    SELECT toYear(ed) AS year,
           max(amt) AS monthly_rate,
           countIf(prior_amt > 0 AND amt > prior_amt) AS raise_count
    FROM steps
    GROUP BY year
),
seq AS (
    SELECT year, monthly_rate, raise_count,
           lagInFrame(monthly_rate) OVER (ORDER BY year ASC) AS prior_rate
    FROM yearly
),
panel AS (
    SELECT year, monthly_rate, raise_count,
           100 * (monthly_rate - prior_rate) / prior_rate AS raise_pct
    FROM seq
    WHERE prior_rate > 0 AND year >= 2014
)
SELECT year,
       round(monthly_rate, 4) AS monthly_payment_usd,
       round(raise_pct, 2) AS annual_raise_pct,
       raise_count,
       round(min(raise_pct) OVER (), 2) AS smallest_annual_raise_pct
FROM panel
ORDER BY year
自己运行这个查询

月度股息率从2014年的$0.1834升至2025年的$0.27。表中最小的年度增幅为0.69%,因此所列每一年股息率均有所上升。最近一个完整年度的增幅为2.47%,而2014年的增幅为0.69%。旁边的上调次数显示了股息率如何达到该水平:仅在2025年内,就有6次单独上调。按月派息的公司通常会在一年内分数次小幅上调股息率,而不是一次性完成上调。完整的测算数据见Realty Income股息页面。

月度派发记录可以追溯多久

本页的每项连续记录,均从股息记录开始计算,而不是从公司首次按月派发股息的年份开始计算。因此,该记录的时间跨度短于最早开始按月派发股息的公司。统计每个完整日历年中拥有十至十四个定期除息日的 ticker 数量:

查询股息记录中的按月派息股票,按已完成日历年度统计
21 rows (showing 20)
年份月度付款人数月度占比
200500
200670.25
2007692.32
2008401.2
2009471.32
2010611.53
2011601.44
20121351.88
201373010.2
201483111.12
201585711.5
201683910.92
201786910.98
20189348.76
20199838.94
20209719.44
202110049.49
202210949.88
2023116910.44
2024129911.35
每个数字背后的完整 SQL
WITH per_year AS (
    SELECT ticker,
           toYear(ex_dividend_date) AS year,
           count(DISTINCT ex_dividend_date) AS payments
    FROM global_markets.stocks_dividends
    WHERE distribution_type = 'recurring'
      AND cash_amount > 0
      AND ex_dividend_date >= '2005-01-01'
      AND ex_dividend_date < toStartOfYear(today())
    GROUP BY ticker, year
)
SELECT year,
       countIf(payments BETWEEN 10 AND 14) AS monthly_payers,
       round(100 * countIf(payments BETWEEN 10 AND 14) / count(), 2) AS monthly_share_pct
FROM per_year
GROUP BY year
ORDER BY year
自己运行这个查询

该记录显示,60个月度派发者在2011,135在2012;随后,730在2013,1481在2025。占比列显示,这一变化并非数据源中整体增长造成:月度派发者占所有定期派发者的比例从1.44%升至10.2%。一家公司即使早在这一变化之前就开始按月派发股息,其连续记录年数也不可能超过该记录本身的时间跨度。

如何衡量这份名单

用通俗语言说明每项门槛和排除条件。

  • 发放频率。 若某个 ticker 在过去365天内记录了十至十四笔定期现金分配,且最新频率标签为月度,则符合月度发放标准。上下限都很重要:下限允许偶尔缺失一笔记录,上限则排除按周和按日分配的产品。
  • 分配类型。 只计算数据源标记为定期的分配。特别分配、额外分配和不定期的一次性分配,既不计入频率测试,也不计入收益率。
  • 连续记录。 连续按月分配年数,是指连续的定期除息日之间没有超过七十天空档的年数。数据源偶尔会缺少某家公司实际支付过的某个月记录,因此要求每年必须有十二条准确记录,会低估所有连续分配记录。若频率切换为季度,空档会接近三个月,连续记录也会正确终止。记录本身决定了连续年数的上限,正如上方覆盖情况面板所示。
  • 流动性门槛。 在过去一个月内,至少十五个正常交易时段的日均股票成交额须达到一百万美元。低于这一水平时,报价价差会使收益率缺乏实际参考价值。
  • 定价。 收益率采用已完成交易时段的最后收盘价。页面重建时仍在进行的交易时段不计入,因此日期标记可能比日历日期晚一到两天。
  • 公司筛选。 主名单只保留带有公司基本面记录的 ticker。收益率分布面板则保留所有按月分配的标的,包括基金。
  • 排除条件。 按名称排除杠杆型和反向交易所交易产品;过去一年内发生过股票拆分的 ticker 也会被排除,因为拆分会制造虚假的价格变动,并破坏每股数据的可比性。同一代码被两家发行人重复使用的标的,在所有位置均会排除。
  • 未包含的内容。 本数据不包含基金费用率,也不包含分配的税务属性(返还资本还是收入)。一些高收益月度分配基金返还的是资本,而非收益;这一点不会反映在收益率中。

常见问题

哪些股票每月派发股息?

按过去十二个月的派息记录统计,1590只美国上市股票每月派息,但其中只有35只拥有公司基本面记录。其余几乎都是基金。在提交相关记录的股票中,交易最活跃的是O;达到流动性门槛的股票共有31只。

每月派息股票安全吗?

按月派息并不保证安全。这类股票主要集中在抵押贷款REIT和期权收益基金,其分配会随信贷环境和利率变化。在本页面统计的每月派息标的中,年化收益率高于12%的股票,过去十二个月价格变动的中位数为-15.1%;收益率低于3%的股票则为-1.1%。

哪只股票的月度股息收益率最高?

在达到流动性门槛的每月派息上市公司中,OXSQ的年化收益率最高。截至Oct 16收盘,该收益率为31.84%。其股价在此前十二个月变动了-28.5%,这也是多数两位数收益率的计算基础。

本页面的月度收益率如何计算?

将最新公布的月度派息乘以十二,再除以上一个完整交易日的收盘价。该方法将当前派息率年化,而不是汇总过去十二个月的现金派息。因此,年中上调派息的股票,其页面显示的收益率可能高于过去十二个月收益率。


上方每张表均为基于已公布股息记录和真实分钟线数据的存储型、版本化查询。展开任一面板下方的 SQL,或在 Strasmore terminal 上自行创建每月派息股票筛选条件。