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Channel

大河马中文财经新闻分享

@chinesecaixin

On this record: Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry

7,095subscribers

+288 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001176496987
TypeChannel
Username@chinesecaixin
CreatedBetween 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live10 September 2026
Measurements held12
Confirmed unchanged1 time, most recently 10 September 2026
On Telegramt.me/chinesecaixin

Growth

6,8077,0956,9517 August 2026 — 6,807 subscribers7 August 2026 — 6,810 subscribers10 August 2026 — 6,824 subscribers13 August 2026 — 6,842 subscribers16 August 2026 — 6,875 subscribers19 August 2026 — 6,900 subscribers22 August 2026 — 6,940 subscribers26 August 2026 — 6,969 subscribers28 August 2026 — 7,002 subscribers1 September 2026 — 7,033 subscribers5 September 2026 — 7,060 subscribers10 September 2026 — 7,095 subscribers7 August 202610 September 2026
12 measurements spanning 34 days, net +288. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 6,764–7,138 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Sept 2026, 06:197,095+35
5 Sept 2026, 05:417,060+27
1 Sept 2026, 03:087,033+31
28 Aug 2026, 18:287,002+33
26 Aug 2026, 00:246,969+29
22 Aug 2026, 17:476,940+40
19 Aug 2026, 13:046,900+25
16 Aug 2026, 22:046,875+33
13 Aug 2026, 09:486,842+18
10 Aug 2026, 16:366,824+14
7 Aug 2026, 12:306,810+3
7 Aug 2026, 00:156,807first reading

Engagement

124 posts held, back to 5 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 12 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.88%
avg views ÷ 7,095 subscribers
Avg views / post
133
40 posts measured
Reaction rate
0%
reactions ÷ views · ER floor
Posts in window
40
of 124 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 1 of 40 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 20 August 2026
Posts held124 (5 August 202620 August 2026)
Views total5,322
Reactions total0
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken20 Aug 2026, 04:00 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

5 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 80.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
💩480.0%
👍120.0%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 3 of the 124 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 5 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 124 most recent posts we hold, published 5 August 2026 to 20 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

20 Aug 2026, 03:39 UTC22 viewsread 20 August 2026

低生育率会让劳动者更富有吗 新闻来源: FT 中文网 关键词: #宏观经济 #就业 #人工智能 💡What you need to know 📊 MIT 教授阿西莫格鲁与奥托等四位学者 6 月发布工作论文《生育低谷与增长繁荣》,基于 1950 至 2020 年跨国面板与美国 722 个通勤区两套数据,提出更低出生率对应更高劳动年龄人口人均 GDP 增速,出生率下降并未显著压低一国总 GDP。 🏭 论文认为核心机制并非教育提升或女性就业增加,而是年轻劳动力稀缺内生诱发节约劳动力的技术创新。佐证显示低出生率国家节约劳动专利更多、高科技出口占比提升,美国低生育率通勤区高技术就业扩张更快。 ⚖️ 为应对反向因果,研究改用几十年前的历史出生率,并以二战平民与军人死亡作工具变量:军人死亡集中于年轻男性,此类国家后续人均劳动 GDP 更高,而单纯平民死亡无此效果。作者据此排除索洛资本稀释、女性就业、人力资本与产业转移四种竞争解释。

20 Aug 2026, 03:33 UTC26 viewsread 20 August 2026

阿联酋暂停对伊金融往来 迪拜成施压关键 新闻来源: WSJ 中文 关键词: #国际贸易 #金融监管 #能源 💡What you need to know 🌍 阿联酋周二晚间宣布暂停与伊朗之间的金融和经济交易,此前特朗普政府已连续数周敦促阿方打击在其境内运作的伊朗金融网络,重点针对与伊朗伊斯兰革命卫队相关的资金流动。 💰 美国财政部数据显示,2024 年约 90 亿美元经由美国银行机构维护的代理账户流转、疑与伊朗秘密金融活动有关,其中 62% 流入阿联酋注册公司,多数位于迪拜。 🏛️ 战争爆发前阿联酋是伊朗最大进口来源国,排在中国之前。世贸组织数据显示,2024 年阿联酋供应了伊朗进口总额的 30% 以上,价值约 210 亿美元。 ⚡ 伊朗依靠迪拜的空壳公司、汇兑行以及由老旧油轮组成的影子船队维持石油出口与外汇回流,交易中往往不出现伊朗名称,许多涉伊油轮由阿联酋注册公司拥有或管理。 📉 知情人士称,阿联酋将措施视为

20 Aug 2026, 02:38 UTC56 viewsread 20 August 2026

贝森特为何在美债市场做文章 新闻来源: WSJ 中文 关键词: #国债 #财政政策 #人工智能 💡What you need to know 📉 美国财政部长贝森特周三宣布将最长期限国债回购规模翻倍至 40 亿美元,推动 30 年期美国国债收益率单日急跌 0.1 个百分点,创一年来最大单日跌幅,股市中杠杆较高的板块随之活跃。 📊 长期收益率此前持续攀升,30 年期收益率周一升至全球金融危机前以来最高水平;五年后起算的五年期通胀调整后「实际」收益率今年已升至 2009 年以来最高,而盈亏平衡通胀率仍接近美联储 2% 的目标,显示抛售并非源于通胀担忧。 🏛️ IMF 预计包括州和地方政府在内的美国政府今年举债规模相当于 GDP 的 7.5%,为 G7 发达经济体中最高,此前只有严重衰退期才达到该水平;欧洲和亚洲同样面临国防与社会支出双重扩张带来的举债压力。 🤖 AI 企业已从轻资本软件公司转为需要巨额资本的数据中心运营

20 Aug 2026, 02:32 UTC57 viewsread 20 August 2026

今日开盘:两市双双高开 沪指涨幅 0.33% 新闻来源: 财新网 关键词: #A 股 #宏观经济 #金融监管 💡What you need to know 📊 8 月 20 日 A 股两市双双高开,沪指开盘报 3907.21 点,涨幅 0.33%;深成指报 14032.97 点,涨 1.03%;创业板指涨 1.27%,中小板指涨 0.79%。 📈 盘面上医药生物板块领涨,有色金属、汽车、美容护理、电子、传媒等板块涨幅居前,资金偏向成长与消费方向。 📉 煤炭板块领跌,银行、石油石化、农林牧渔、食品饮料、公用事业等走弱,周期与防御性板块表现疲软。 🌍 美国财政部出手护盘,美债收益率走低,金银价格拉升;美联储纪要显示鹰派情绪更浓,沃什提及将议息会议次数减少至每年 6 次。 🏛️ 央行连续三个月动用隔夜逆回购操作;全民医疗保障「十五五」规划正式发布;宇树科技 IPO 造富效应显现,长江存储完成 IPO 辅导验收。 (P

20 Aug 2026, 01:34 UTC68 viewsread 20 August 2026

贝森特扩大回购力度 力压美债长端收益率 新闻来源: WSJ 中文 关键词: #国债 #美联储 #宏观经济 💡What you need to know 🏛️ 美国财政部长贝森特周三宣布,作为现有回购计划的一部分大幅增加政府债券购买规模。市场反应迅速,股市上涨、美国国债收益率大幅回落,这是他此前几次出招均未能引发的反应。 📈 美债收益率近几个月持续上行,本周 30 年期收益率升破 5.3%,创近 20 年新高;平均房贷利率回升至逼近 7%,财政赤字徘徊在 GDP 的 6% 左右,远高于贝森特设定的 3% 较长期目标。 💰 财政部表示,从 9 月 9 日起至少持续到 11 月 4 日,单次操作中可购买的 10 年期至 30 年期国债最高金额,将从 20 亿美元提高至至少 40 亿美元,按此节奏年回购规模约 1280 亿美元。 📊 法国外贸银行估算,该回购规模相当于此类债券预期发行量的近 30%,但仅占相应期限未偿债务余

20 Aug 2026, 00:31 UTC91 viewsread 20 August 2026

​ 全球市场速览 |8 月 20 日 新闻来源: 彭博 / 路透 / CNBC / 经济学人 / 日经 (X 官方账号 · 中文编译) 关键词: #美债干预 #美联储纪要 #加密政策 💡What you need to know 📉 美国财政部意外大幅增加长期国债回购规模,在 30 年期国债收益率触及金融危机以来高位、市场压力加剧之际,此举推动收益率回落。(CNBC) 🏦 美联储会议纪要显示,官员们认为如果通胀未能冷却,可能需要加息,这一信号影响了市场对未来利率路径的预期。(CNBC) 💻 英伟达人工智能芯片领先优势正被 AMD 和谷歌等竞争者蚕食,公司正利用其庞大资本储备来维持市场地位。(CNBC) ₿ 特朗普在白宫会见加密业高管期间,敦促国会通过数字资产市场结构立法,将其列为行业发展首要任务。(彭博) 🇨🇦 特朗普政府推迟敲定避免对加拿大出口商品征收 50% 关税的协议期限至周五,加剧制造商面临的经济不确定性

19 Aug 2026, 14:05 UTC194 viewsread 20 August 2026

韩国足协被曝「不当招待」中国足协三人 中方展开调查 新闻来源: 财新网 关键词: #足球 #国际交流 #体育反腐 💡What you need to know ⚽ 韩国媒体近日披露,2012 年 1 月韩国足协在接待赴韩进行裁判交流的 3 名中国足协工作人员期间,被指存在「不当招待」行为,此事经报道后引发中国舆论广泛关注。 🏛️ 中国足协于 8 月 19 日通过官方微博发布声明称,协会对此高度重视,已对相关情况展开调查,并承诺将及时对外公布调查结果,回应社会关切。 📉 韩国足协近期因 2026 年美加墨世界杯韩国队小组赛出局、前国家队主教练洪明甫选任过程涉嫌违规等连串事件陷入舆论争议,内部治理问题持续发酵。 ⚖️ 韩国首尔警方已于 8 月 6 日对韩国足协办公场所实施搜查取证,调查足协高层是否在 2024 年违规干预洪明甫出任国家队主教练,相关程序仍在推进中。 (Powered by MiniMax-M3) 链

19 Aug 2026, 13:04 UTC171 viewsread 20 August 2026

跨境人口贩卖集团 17 人被诉王星案提起公诉 新闻来源: 财新网 关键词: #跨境犯罪 #人口贩运 #反电诈 💡What you need to know ⚖️ 上海市检察院第二分院对王某军、张某飞、毋某龙等 17 名犯罪嫌疑人以涉嫌拐卖妇女罪、非法拘禁罪、抢劫罪、绑架罪等向上海二中院提起公诉,案件于 8 月 19 日由检方公号披露。 🌍 该跨境人口贩卖集团盘踞在缅甸妙瓦底地区,以出国务工为诱饵,诱骗中国境内公民至境外后依托武装人员强行押送,并对众多被害人实施抢劫、殴打、非法拘禁及强迫卖淫等犯罪。 🎬 演员王星系该案被害人之一。2025 年 1 月 3 日王星从泰国曼谷乘车上路后失联,定位显示其被带至泰缅边境湄索县,随后进入妙瓦底电诈中心,1 月 7 日被移交泰方。 🏛️ 公安部此前通报已循线深挖出该藏匿于妙瓦底的犯罪集团,自 2024 年 12 月起通过虚假剧组、模特、招聘广告诱骗人员赴泰后转运缅甸贩卖至各电诈园

19 Aug 2026, 12:45 UTC148 viewsread 20 August 2026

​ 全球市场速览 |8 月 19 日 新闻来源: 彭博 / 路透 / CNBC / 经济学人 / 日经 (X 官方账号 · 中文编译) 关键词: #财报季 #医药创新 #AI 投资 💡What you need to know 🧬 Moderna 与 Merck 合作开发的个性化 mRNA 癌症疫苗在大规模三期试验中成功减少黑色素瘤复发,这一突破为相关医药股提供利好。(彭博) 🛍️ Target 公布季度业绩超过预期并上调全年销售与利润指引,显示零售消费需求呈现恢复迹象。(彭博) 🏠 Lowe’s 因住房市场疲软导致季度业绩不及预期,并下调全年展望,影响投资者对家居零售板块的信心。(彭博) 📡 Nebius Group 计划通过可转换债券融资 45 亿美元,用于扩建人工智能数据中心以满足市场需求。(彭博) 🏦 香港交易所第二季度净利润较上年增长 21%,受交易量上升和 IPO 活跃推动,业绩超出市场预期。(彭博)

19 Aug 2026, 12:09 UTC136 viewsread 20 August 2026

美韩联合军演提前六天叫停 新闻来源: WSJ 中文 关键词: #国际贸易 #宏观经济 #能源 💡What you need to know 🌍 美韩两国将在计划日程中途叫停正在进行的联合军演。首尔官员表示,为期 11 天的「乙支自由护盾」演习将于本周五结束,比原定计划提前六天。韩国外交部长周三对议员表示,这一突如其来的缩减令韩方措手不及。 🏛️ 就在周一军演开始前一天,特朗普曾斥责该联合训练耗资巨大、不合时宜,且对一直「毫无威胁且充满敬意」的朝鲜具有敌意。平壤方面历来谴责此类演习是战争预演,本周也不例外。有报道称特朗普正敦促助手安排最快于今秋与金正恩会晤。 📊 「乙支自由护盾」旨在强化韩国应对朝鲜军事对抗的能力,汇集了来自美国、韩国及十几个其他国家的约 2.3 万名军事人员。上周简报会上一名高级官员曾表示,今年演习规模将史无前例,并纳入反无人机及反 GPS 干扰等新科目。 ⚖️ 韩国保守派在野党称缩减训练规模损害了

19 Aug 2026, 12:03 UTC121 viewsread 20 August 2026

医保局升级商业医保支持力度 从鼓励到大カ推动 新闻来源: 财新网 关键词: #医疗保障 #商业保险 #政策 💡What you need to know 🏛️ 国家医保局 8 月 19 日印发《全民医疗保障「十五五」规划》, 在健全多层次医疗保障体系方面, 提出要「大カ推动商业医疗保险发展」, 较此前「鼓励」的措辞明显升级。 📊 《规划》明确, 基本医保长期承担医疗保障体系的主要责任, 商业保险需发挥有效补充作用, 以满足群众对医疗服务的多样化需求。 💼 医保局表示, 将积极支持商业医疗保险在多层次医疗保障体系中更好发挥作用, 提升服务保障水平, 推动公共政策与市场经济相互支撑。 🏛️ 商业医疗保险如何填补基本医保之外的保障缺口、如何与公共保障体系协同, 始终是政策层面的重要议题,《规划》为此提供了顶层设计指引。 🏥 业内期待, 在政策明确「大カ推动」后, 商业健康险在产品创新、覆盖面及与基本医保衔接方面将迎来更

19 Aug 2026, 11:04 UTC148 viewsread 20 August 2026

7 月不含在校生青年失业率升至 17.9% 创近三年同期新高 新闻来源: 财新网 关键词: #就业 #宏观经济 #数据统计 💡What you need to know 📊 2026 年 7 月,16—24 岁劳动力 (不含在校生) 失业率录得 17.9%, 较上月上升 3 个百分点, 创近三年同期最高,2024 年和 2025 年 7 月该数据分别为 17.1% 和 17.8%。 📈 7 月全国城镇调查失业率为 5.2%, 较上月回升 0.2 个百分点, 略超季节性规律 (2019—2025 年 7 月平均环比升幅为 0.1 个百分点),25—29 岁失业率 7.2%,30—59 岁失业率降至 3.9%。 📉 国家统计局 2023 年 12 月恢复发布青年失业率时调整口径, 剔除在校学生; 新口径下 2024 年 8 月和 2025 年 8 月 16—24 岁失业率分别达 18.8% 和 18.9%, 为有记录以来

Showing the 12 most recent of 124 posts we hold for @chinesecaixin. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

看鉴中国 OutsightChina
@OutsightChina · 41,254
Telegram ranks this channel #18 of 58 here — alongside 57 others — read 29 August 2026
【华尔街见闻】- 财经时讯 | AI 实时互动
@FinanceNewsDaily · 55,434
Telegram ranks this channel #24 of 60 here — alongside 59 others — read 24 August 2026
科技圈🎗在花频道📮
@zaihuapd · 281,658
Telegram ranks this channel #24 of 40 here — alongside 39 others — read 12 August 2026
FREE 中文
@freechinese · 27,522
Telegram ranks this channel #27 of 55 here — alongside 54 others — read 10 September 2026
敏感经济信息分享
@pelosi3 · 70,632
Telegram ranks this channel #36 of 51 here — alongside 50 others — read 20 August 2026
竹新社
@tnews365 · 159,452
Telegram ranks this channel #54 of 59 here — alongside 58 others — read 12 August 2026

This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 September 2026 — this entry's latest reading, not the date you are reading this.

“大河马中文财经新闻分享” (@chinesecaixin), 7,095 subscribers as measured 10 September 2026. Telegram Register, tgregister.com/channel/chinesecaixin.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.