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Channel

美股·币圈·经济·加密货币·投资笔记

@Showmoney118

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Posts · Citations · Cite this entry

1,809subscribers

+4 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002351485874
TypeChannel
Username@Showmoney118
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/Showmoney118

Topic

Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 61% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@FinanceNewsDaily/4922567 Aug 2026, 12:35 UTC@Showmoney118/73977 · this entry7 Aug 2026, 12:35 UTC1.00under a minute
@FinanceNewsDaily/4922607 Aug 2026, 12:50 UTC@Showmoney118/73981 · this entry7 Aug 2026, 12:50 UTC1.00under a minute
@FinanceNewsDaily/4922627 Aug 2026, 13:00 UTC@Showmoney118/73982 · this entry7 Aug 2026, 13:00 UTC1.00under a minute
@FinanceNewsDaily/4922637 Aug 2026, 13:25 UTC@Showmoney118/73984 · this entry7 Aug 2026, 13:25 UTC1.00under a minute
@FinanceNewsDaily/4922647 Aug 2026, 13:25 UTC@Showmoney118/73985 · this entry7 Aug 2026, 13:25 UTC1.00under a minute
@FinanceNewsDaily/4922657 Aug 2026, 13:30 UTC@Showmoney118/73986 · this entry7 Aug 2026, 13:30 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@FinanceNewsDaily7 (7/7 hand-verifiable sample passed)1.00under a minute@FinanceNewsDaily (70)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 7 of the 7 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 8 comparable posts for this entry, running 7 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 2, the earliest publisher we hold is @FinanceNewsDaily. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

1,8051,8101,807.57 August 2026 — 1,805 subscribers7 August 2026 — 1,805 subscribers10 August 2026 — 1,810 subscribers13 August 2026 — 1,809 subscribers1,8097 August 202613 August 2026
4 measurements spanning 6 days, net +4. 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 1,804–1,811 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 18:141,809-1
10 Aug 2026, 10:441,810+5
7 Aug 2026, 15:471,805no change
7 Aug 2026, 14:011,805first reading

Engagement

20 posts held, back to 7 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
1.10%
avg views ÷ 1,809 subscribers
Avg views / post
19.9
20 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
20
of 20 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held20 (7 August 20267 August 2026)
Views total399
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 15:47 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.

Recent posts

7 Aug 2026, 14:35 UTC19 viewsread 7 August 2026

SpaceX #涨幅 扩大至10%,报126.510 #美元 ,盘中 #市值 1.67万亿美元。

7 Aug 2026, 14:10 UTC23 viewsread 7 August 2026

白宫经济顾问哈塞特: #美国 总统 #特朗普 与 #美联储 主席沃什“时时刻刻”都在谈论经济问题。 我确定特朗普没有向沃什提供政策利率的建议。(彭博电视)

7 Aug 2026, 13:50 UTC26 viewsread 7 August 2026

📊 经济数据汇总 • 白宫国家经济委员会主任哈塞特:剔除政府就业和世界杯因素后, #美国 就业人数增加10万。

7 Aug 2026, 13:35 UTC28 viewsread 7 August 2026

【 #美国 7月非农超预期下降, #美股 三大股指集体高开】 美国7月非农就业人数意外减少,交易员削减对 #美联储 的 #加息 押注,纳指盘初涨0.77%, #标普 500指数涨0.33%, #道指 涨0.10%。存储概念股盘初部分走高,闪迪涨超3%。光通信概念股普涨,光模块制造商AAOI涨超12%,公司预计产能两年扩张10倍,1.6T最快两周获大客户认证;Coherent涨超9%。协作软件开发商Atlassian涨逾32%,业绩指引远超市场预期。爱彼迎涨逾8%,上调全年业绩预期。

7 Aug 2026, 13:30 UTC26 viewsread 7 August 2026

【北京市进一步优化 #调整 房 #地产 政策,优化住房 #限购 政策,完善房屋赠与政策,加大住房公积金支持力度】 一、优化住房限购政策 非本市户籍居民家庭购买五环内商品住房的,在本市缴纳社会 #保险 或个人所得税的年限,调整为购房之日前连续缴纳满1年及以上。 二、完善房屋赠与政策 父母将家庭名下本市商品住房赠与子女的,不核验子女的购房资格。

7 Aug 2026, 13:25 UTC23 viewsread 7 August 2026

【北京:非京籍家庭购房社保个税缴纳年限下调为一年】 北京市住房和城乡建设委员会、北京市规划和自然资源委员会、北京住房公积金管理中心7日晚联合印发《关于进一步优化 #调整 本市 #房 #地产 政策的通知》,明确非京籍家庭购买五环内商品住房的社保或个税缴纳年限由“2年”,调减为“1年”。调整后,非京籍家庭在全市范围内购买商品住房的社保或个税缴纳年限统一为“1年”,购买商品住房的套数保持不变。即:社保或个税缴纳满1年的非京籍家庭,在五环内可购买1套商品住房,多子女家庭可再多购买1套;在五环外,不 #限购 买套数。 《通知》自8日起实施。(央视)

7 Aug 2026, 13:25 UTC17 viewsread 7 August 2026

【周五 #美股 盘前你需要了解的全球 #要闻 】 爆冷! #美国 7月非农就业人数意外减少2.3万,前两月就业下修10.3万人。 #特朗普 谈 #降息 :希望利率下调,但这不完全取决于沃什一人。 #中国 #央行 连续21个月 #增持 #黄金 ,7月购金力度提速。 股市 #大涨 拉动, #日本 GPIF一季度收益24.1 万亿 #日元 创纪录。 美国绕开 #欧洲 央行售 #欧元 撑日元,欧洲人感到“遭背叛”。 380亿 #美元 !SK海力士新建两座存储 #芯片 工厂,产能将按客户需求逐步扩大。 美国光模块龙头AAOI盘前涨超15%,公司预计产能两年扩张10倍,1.6T最快两周获大客户认证。 #苹果 上调多款设备以旧换新回收价,幅度最高近30%。 日经225指数收跌0.1%, #沪指 收涨1.02%, #恒生 指数收涨0.54%。

7 Aug 2026, 13:01 UTC20 viewsread 7 August 2026

【快讯】金色晚报 | 8月7日晚间重要动态一览 【金色晚报 | 8月7日晚间重要动态一览】12:00-21:00关键词:7月非农、SK海力士、字节跳动、宇树科技 1.中国央行连续第21个月增持黄金 2.特朗普:数据中心可能会比石油更重要 3.美国7月非农就业人数减少2.3万人 不及市场预期 4.美国监管部门系统性审查中国 AI 企业第三国算力租赁 5.SK海力士:将投资384亿美元在韩国本土扩张芯片业务 6.美国利率期货市场对美联储9月加息的预期概率有所下降 7.字节10万亿参数模型已开训,规模逼近Anthropic Mythos5 8.宇树科技王兴兴:公司与DeepSeek将在AGI、高性能通用机器人、AI大模型三方面开展重点合作 #财经快讯

7 Aug 2026, 13:00 UTC19 viewsread 7 August 2026

📰 #见闻日报 · 2026/08/07 🌍 宏观经济 • 中国7月出口同比增23.9%,进口增27.5%,贸易顺差1125亿美元 • 美国7月非农意外减少2.3万人,失业率降至4.1%,加息预期降温 • 央行连续21个月增持黄金,外汇储备升至34187.8亿美元 • 德国6月工业产出环比增0.2%,符合预期 📈 市场行情 • A股三大指数涨超1%,创新药、PCB概念股爆发,创业板指涨1.35% • 现货黄金突破4300美元,白银涨超5%,原油涨超4%因霍尔木兹海峡事件 • 美国非农数据后美股期货拉升,10年期美债收益率下行 🏢 公司动态 • SK海力士宣布投资19.1万亿韩元建设M17芯片工厂 • 宇树科技科创板IPO定价609.9亿元,具身智能赛道迎估值锚 • 寒武纪上半年净利润23.11亿元,同比增122.61% • 药明康德港股创历史新高,国泰君安国际拟私有化退市 💡 今日洞察 美国非农意外负增长强化降息预期,

7 Aug 2026, 12:50 UTC14 viewsread 7 August 2026

【 #美国 7月非农数据速评】 美国雇主在7月意外 #裁员 ,且前几个月的数据也被下修,表明劳动力市场在今年早些时候出人意料的强劲之后正面临挑战。数据显示,在对前两个月进行大幅下修之后,7月非农就业人数减少23,000人。由于劳动参与率持续下降, #失业率 降至4.1%。在物价上涨和 #伊朗 战争带来的不确定性背景下,劳动力市场可能开始出现疲软迹象,尽管 #消费 需求的韧性迄今仍鼓励部分雇主继续推进招聘计划。该数据也可能促使 #美联储 推迟 #加息 ,因为政策制定者需要在权衡通胀 #风险 与就业风险之间做出决策。投资者降低了对美联储9月加息的押注。

7 Aug 2026, 12:40 UTC17 viewsread 7 August 2026

#日本 财务大臣片山皋月:将持续与市场沟通,以维护信任。 已与 #美国 财长 #贝森特 达成共识,认为近期外汇市场受到非真实需求驱动的波动的影响。 一直与美国保持密切沟通,双方在必要时都不会犹豫进行干预。

7 Aug 2026, 12:35 UTC17 viewsread 7 August 2026

交易员下调对 #美联储 2026年 #加息 的押注。

Showing the 12 most recent of 20 posts we hold for @Showmoney118. 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.

Citation-graph rank

Citation-graph rank — 584,412 of 1,480,688entries 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.

Mentions

Named by 3 registered channels — 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.

Names

Channels on the register whose handles appear in this channel's posts.

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.

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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“美股·币圈·经济·加密货币·投资笔记” (@Showmoney118), 1,809 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/Showmoney118.

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.