Channel
@causmoney
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
8,423subscribers
+30 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001725573417 |
|---|---|
| Type | Channel |
| Username | @causmoney |
| Description | 加美财经是中文小众政经商业媒体，重点关注财富、科技、创业、人文、科学等领域，为全球华人提供来自主流媒体的报道和分析，适合愿意拓展全球视野的华语用户。 深度内容全文请见 www.caus.com 请关注加美财经蓝天号: @causmoney.bsky.social 加美财经官方推特: @CausMoney |
| Created | Between 1 December 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/causmoney |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 01:45 | 8,423 | +27 |
| 7 Aug 2026, 16:28 | 8,396 | +3 |
| 6 Aug 2026, 22:02 | 8,393 | first reading |
103 posts held, back to 6 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 13 pagesof Telegram’s post history, 20 posts per page.
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 75 of 102 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 103 (6 August 2026 – 12 August 2026) |
| Views total | 38,311 |
| Reactions total | 359 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 17:35 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.
Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 28 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
359 reactions across 73 posts, in 29 distinct kinds. The most used accounts for 32.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🤡 | 115 | 32.0% | |
| 👍 | 37 | 10.3% | |
| 👏 | 34 | 9.47% | |
| ❤ | 26 | 7.24% | |
| 🤣 | 25 | 6.96% | |
| 😁 | 23 | 6.41% | |
| 🤮 | 22 | 6.13% | |
| 💊 | 15 | 4.18% | |
| 😱 | 8 | 2.23% | |
| 🤔 | 7 | 1.95% | |
| 🥰 | 7 | 1.95% | |
| 🤪 | 6 | 1.67% | |
| 👎 | 5 | 1.39% | |
| 💩 | 5 | 1.39% | |
| 🤷♀ | 4 | 1.11% | |
| 🎉 | 3 | 0.836% | |
| 😈 | 3 | 0.836% | |
| 🤬 | 2 | 0.557% | |
| 🤯 | 2 | 0.557% | |
| ✍ | 1 | 0.279% | |
| 9 further kinds | 9 | 2.51% |
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 75 of the 103 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 359reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 103 most recent posts we hold, published 6 August 2026 to 12 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.
城堡证券此前预判了美股调整，现在公司认为市场可能很快重新进入加杠杆阶段，但有人怀疑 不过，社交媒体对城堡证券的乐观看法明显更加谨慎。 鲁布纳近期多次谈到股市可能继续上涨，在X平台上引发了一些质疑。部分投资者暗示，城堡证券可能有自己的利益考虑，因为这家公司上个月刚刚在一场低价抛售中买下了利奥波德·阿申布伦纳旗下人工智能主题对冲基金Situational Awareness的大部分资产。 据报道，这笔交易已经为城堡证券带来了可观收益。 👉 阅读全文： https://www.caus.com/all-articles/finance/429530/
科学家仿照“海王星球”设计新材料，可同时捕获大小不同的微塑料 研究人员受到一种天然海草球的启发，设计出一种能够同时捕获不同尺寸微塑料的新型材料，有望为清理海洋和淡水中的微塑料污染提供新方法。 人们熟知的“太平洋垃圾带”并不完全由大片漂浮塑料组成。科学家估计，其中多达90%的塑料实际上是直径小于5毫米的微塑料。放眼全球海洋，微塑料颗粒的数量更以万亿计。 研究团队的灵感来自所谓“海王星球”。这种由海草自然缠结形成的致密球状结构，能够在水中截留微塑料。研究人员在实验室中利用海藻和甲壳类动物外壳提取的生物聚合物，制造出类似的球状网状结构。 这种材料采用内外两层不同结构。内部的致密网格可以捕获直径超过1毫米的塑料颗粒，外层则覆盖细小的绒毛状纤维，能够吸附尺寸只有几十纳米的微塑料。研究人员称，以往一些清理方法往往只能针对极小或较大的微塑料，而这种设计能够覆盖更宽的粒径范围。 实验室测试显示，这种结构在淡水和海水中都可以发挥作用。研…
挪威主权财富基金CEO：人工智能短期推高通胀，长期将成为抑制通胀力量 挪威2.3万亿美元主权财富基金首席执行官尼古拉·唐根表示，人工智能目前仍可能带来通胀压力，但随着知识获取成本下降、劳动效率提高，以及机器人技术逐步普及，未来几年人工智能有望成为一股重要的抑制通胀力量。 唐根在接受采访时说，人工智能已经显著改变了基金自身的运营方式。过去一年左右，基金的生产率提高了约20%，并帮助降低了交易成本。他形容，人工智能对基金工作方式产生的影响“令人惊叹”。 在被问到这是否令他更加看好人工智能相关企业以及整个市场的投资回报时，唐根表示肯定。他说，基金自身的使用经验使其更加了解这项技术的实际能力，也更容易理解为什么一些人工智能企业能够取得如此强劲的表现。 唐根认为，目前社会中仍有很大一部分人和企业尚未真正开始人工智能转型，因此生产率提升的潜力远未完全释放。“这无疑令人非常乐观。”他说。 不过，他也承认，人工智能在现阶段确实可能推高…
进步派的纽约市长佐赫兰·曼达尼在纽约市的好感度继续上升。锡耶纳研究最新民调显示，69%的纽约市受访者对曼达尼持好感，24%持负面看法。与4月相比，好感度上升13个百分点，负面评价下降10个百分点。 这是曼达尼在锡耶纳研究纽约市民调中取得的最高好感度。相关调查于8月3日至8日进行，数据来自纽约市受访者样本。 曼达尼在年轻纽约人中的支持尤其明显。在18至34岁受访者中，72%对他持好感，21%持负面看法，净好感度达到51个百分点，创下这一年龄组的新高。 年轻选民对曼达尼的评价今年持续改善。1月时，他在18至34岁人群中的好感度为55%，负面评价为20%，净好感度35个百分点；6月升至61%对22%，净好感度39个百分点；到8月进一步扩大至72%对21%，净好感度升至51个百分点。 曼达尼引入注目的一点是，非常善于通过年轻人喜欢的方式宣扬他自己的理念，视频为他宣布他支持《配送保护法》。 这个法律法案针对亚马逊等大公司通过分包…
大规模水母入侵迫使法国三座核反应堆停运 由于水母大规模涌入，法国电力公司被迫关闭了位于诺尔省的格拉维林核电站（西欧最大核电站）六座反应堆中的三座。 这个地区经常能看到水母，但最近大规模水母群的报告日益增多，主要归因于全球变暖导致的海水温度上升。（法新）
加美财经causmoney pinned a photo
加美财经解释：朱镕基是如何压制中国高达25%的通胀的 1990年代初，中国经济高速增长，但也出现严重过热。银行大量向地方政府和亏损国企放贷，各地竞相投资上项目，货币供应快速增加，物价随之失控。到1993年前后，中国通胀率一度达到25%左右。 朱镕基接手宏观经济工作后，选择了一套力度很大的紧缩政策，目标是让经济降温，同时尽量避免陷入衰退。 最重要的一步，是收紧银行信贷。朱镕基加强中央对金融体系的控制，限制银行继续向亏损国企和地方投资项目大量放贷，同时压低货币供应增速。 由于当时中国经济扩张很大程度依赖银行贷款，这相当于直接踩下了经济的刹车。 与此同时，政府开始压缩财政支出，叫停和削减大量地方投资项目，以遏制各地不断扩张的建设热潮。对于粮食等关系居民生活的基本商品，政府还一度采取价格控制，防止价格上涨进一步强化通胀预期。 朱镕基也试图解决居民在高通胀时期“拿到钱就赶快花”的心理。政府推出与通胀挂钩的储蓄产品，让存款能够获…
👍6
美国股市周三开盘后走高。7月通胀数据符合预期并较前一个月小幅降温，强化了市场对美联储9月维持利率不变的预期。人工智能相关公司强劲业绩也继续推动科技股上涨。 截至最新，道琼斯工业平均指数报53775.41点，下跌0.03%；标普500指数报7748.94点，上涨0.27%；纳斯达克综合指数报26623.64点，上涨0.67%。 美国7月消费者价格指数环比上涨0.1%，同比上涨3.4%，均符合市场预期，同比涨幅低于6月的3.5%。剔除食品和能源价格的核心CPI环比上涨0.2%，同比上涨2.5%，同比涨幅同样较6月小幅回落。 通胀数据公布后，市场进一步提高了对美联储9月按兵不动的预期。 根据芝加哥商品交易所FedWatch工具，美联储基金期货显示，美联储下月将基准利率维持在3.50%至3.75%区间的概率升至约58%，高于一周前的45%以上。 摩根士丹利财富管理首席经济策略师埃伦·曾特纳表示，符合预期的通胀数据将延续上周就业…
❤1
加拿大6月建筑许可总值环比激增18.5%至149亿加元，远超预期的0.8%，前值修正为下降3.0%。非住宅和住宅许可分别增长38.7%和6.3%，显示建筑投资意向回升，但增量集中于大型机构项目，持续性仍待观察。
中国改革工程师，奠定市场经济基础的前总理朱镕基逝世 朱镕基把国际市场经济原则与中国国内现实结合起来，形成中国官员所称的“中国特色社会主义市场经济”。 这套制度为中国后来持续数十年的高速增长奠定了基础。中国由此实现了主要经济体中持续时间最长的一轮经济增长，而领导国家的仍然是一个长期受到毛泽东时代封闭思想影响的共产党。 通过集中金融监管权力，朱镕基也为中国此后建立全球规模最大的银行体系之一，以及庞大的股票、债券和大宗商品市场创造了条件。 与此同时，中国形成了一套受到严格控制、但又获得国际认可的货币体系。人民币纸币上的毛泽东头像，或许也会让毛泽东本人感到自豪。 1999年接受《华尔街日报》采访时，这位身材高大的技术官僚露出略带顽皮的笑容，把自己形容为“一个脾气不好的普通中国人”。 在中国最高权力层，个人魅力通常十分罕见，官员讲话更多是平淡的政治语言和模糊表态，但朱镕基是明显的例外。经历过“朱老板”掌权年代的许多中国人，至今…
👍1
中国官方8月12日发布讣告，国务院原总理朱镕基当天11时06分在北京因病医治无效逝世，享年98岁。 朱镕基1928年出生于湖南长沙，1998年至2003年任国务院总理。在任期间，他推动国有企业、金融、住房等领域改革，并参与推进中国加入世界贸易组织，被视为中国上世纪90年代经济改革的重要推动者之一。
🕊1
美国7月通胀同比增速降至3.4%，核心CPI 上涨幅度继续回落，专家认为9月加息仍未定局 市场的第一反应也显示，这份报告并没有带来决定性的政策信号。《华尔街日报》报道，数据公布后美国国债收益率变化不大，市场对美联储9月维持利率不变的预期略有增强，但投资者对最终结果仍然存在明显分歧。 这也是7月CPI最重要的政策含义：没有给美联储提供新的加息理由，但也没有把加息选项从桌面上拿掉。 👉 阅读全文： https://www.caus.com/all-articles/news/429518/
Showing the 12 most recent of 103 posts we hold for @causmoney. 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.
@causmoney edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
Citation-graph rank — 1,032,701 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“加美财经causmoney” (@causmoney), 8,423 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/causmoney.
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.