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Channel

【华尔街见闻】- 财经时讯 | AI 实时互动

@FinanceNewsDaily

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

59,124subscribers

+5,302 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001132332373
TypeChannel
Username@FinanceNewsDaily
Description中国领先的金融信息平台,7×24 覆盖全球股市、外汇、债券、商品动态。 ✨ 频道特色 • 📊 AI 自动解读:每条新闻实时生成投资参考 • ❓ 智能问答:使用 /ask 命令深入了解任意资讯 • ⚡ 秒级推送:重要信息第一时间触达 专业 + 智能,让投资决策更高效。 请通过频道左下角的「Direct Message」联系管理
CreatedBetween 1 June 2017 and 30 September 2020 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live5 November 2026
Measurements held61
Confirmed unchanged1 time, most recently 5 November 2026
On Telegramt.me/FinanceNewsDaily

Topic

Technology — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 58% 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 the other topics.

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/492256 · this entry7 Aug 2026, 12:35 UTC@Showmoney118/739777 Aug 2026, 12:35 UTC1.00under a minute
@FinanceNewsDaily/492260 · this entry7 Aug 2026, 12:50 UTC@Showmoney118/739817 Aug 2026, 12:50 UTC1.00under a minute
@FinanceNewsDaily/492262 · this entry7 Aug 2026, 13:00 UTC@Showmoney118/739827 Aug 2026, 13:00 UTC1.00under a minute
@FinanceNewsDaily/492263 · this entry7 Aug 2026, 13:25 UTC@Showmoney118/739847 Aug 2026, 13:25 UTC1.00under a minute
@FinanceNewsDaily/492264 · this entry7 Aug 2026, 13:25 UTC@Showmoney118/739857 Aug 2026, 13:25 UTC1.00under a minute
@FinanceNewsDaily/492265 · this entry7 Aug 2026, 13:30 UTC@Showmoney118/739867 Aug 2026, 13:30 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@Showmoney1187 (7/7 hand-verifiable sample passed)1.00under a minutethis entry (7–0)

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. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 30 comparable posts for this entry, running 6 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 — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 8 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

53,82259,12456,4736 August 20265 November 2026
61 measurements spanning 91 days, net +5,302. 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 53,027–59,919 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
5 Nov 2026, 19:5759,124+66
4 Nov 2026, 19:1759,058+64
3 Nov 2026, 19:5958,994+31
2 Nov 2026, 16:4658,963+57
1 Nov 2026, 14:2958,906+53
31 Oct 2026, 13:5858,853+22
30 Oct 2026, 13:0458,831+7
29 Oct 2026, 11:0858,824+15
28 Oct 2026, 11:0558,809+8
27 Oct 2026, 11:0958,801+23
26 Oct 2026, 11:3058,778+20
25 Oct 2026, 08:2758,758+54
24 Oct 2026, 09:5058,704+23
23 Oct 2026, 10:4958,681+26
22 Oct 2026, 12:5058,655+54
21 Oct 2026, 03:4758,601+27
20 Oct 2026, 01:4658,574+9
19 Oct 2026, 04:3958,565+30
18 Oct 2026, 03:5158,535+33
17 Oct 2026, 06:4858,502first reading

Engagement

2,670 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 184 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.87%
avg views ÷ 59,124 subscribers
Avg views / post
1,100
920 posts measured
Reaction rate
0.297%
reactions ÷ views · ER floor
Posts in window
920
of 2,670 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 261 of 920 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 5 November 2026
Posts held2,670 (6 August 2026 – 5 November 2026)
Views total1,015,039
Reactions total1,000
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken5 Nov 2026, 22:48 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.

What this channel posts

Photos
≈7,070
Videos
≈10
Links
≈3,290

Lifetime counters from Telegram’s own channel header, read 5 November 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.

Reaction mix

1,035 reactions across 267 posts, in 8 distinct kinds. The most used accounts for 44.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🤡45944.3%
👍33031.9%
👎14814.3%
👏403.86%
🤯292.80%
💯222.13%
🤔60.58%
🤷‍♂10.097%

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 276 of the 1,000 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 1,035 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 2 October 2026 to 5 November 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

Telegram’s own ‘edited’ marker: 0 of 920 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

5 Nov 2026, 22:20 UTC205 viewsread 5 November 2026

💱 外汇数据汇总 • #布伦特 #原油 日内 #涨幅 达5.0%,报99.47 #美元 /桶; #WTI 原油日内涨幅达3.5%,报91.22美元/桶。

5 Nov 2026, 21:25 UTC376 viewsread 5 November 2026

📈 ETF 数据汇总 • 周四(11月5日), #美股 行业ETF全线溃败, #半导体 ETF收跌11.21%,全球 #科技股 指数ETF、科技行业ETF至少跌8%,网络股指数ETF跌4... --- 本条新闻由树洞赞助 树洞 一个匿名分享秘密和诉说心事的地方 树洞入口 @TheTreeHoleBot

5 Nov 2026, 21:25 UTC376 viewsread 5 November 2026

# #标普 500 指数的11个板块中,信息技术/科技板块收跌7.3%。

5 Nov 2026, 21:05 UTC458 viewsread 5 November 2026

#英伟达 收跌9.3%, #市值 单日蒸发4470亿 #美元 。

5 Nov 2026, 21:05 UTC485 viewsread 5 November 2026

#美股 存储 #芯片 指数跌约15%,盘初持续下跌,大部分时间低位持稳;费城 #半导体 指数跌超10%, #AI 软件先驱指数跌5.1%、AI赢家指数跌9.7%, #科技股 七巨头指数跌4%,超大规模云服务商指数跌3.1%。 #标普 500指数初步收跌4.3%,科技板块重挫7%,工业、可选 #消费 、金融、能源等板块至少跌超%。 #纳斯达克 100指数初步收跌6.4%,成分股中,闪迪初步收盘 #暴跌 22.3%,Astera Labs跌20%,Lumentum跌18.7%,美光、西部数据、AMD、希捷科技等至少跌超16%,汤森路透涨0.7%, #拼多多 涨2.1%,Applovin涨30.7%。

5 Nov 2026, 19:35 UTC564 viewsread 5 November 2026

💱 外汇数据汇总 • #WTI 12月 #原油 #期货 收涨2.40 #美元 , #涨幅 超过2.72%,报90.52美元/桶,脱离10月7日以来最低收盘位88.12美元,亚太午...

5 Nov 2026, 19:30 UTC608 viewsread 5 November 2026

#美国 国务卿鲁比奥考虑退出总统 #特朗普 的政府,此前特朗普所属共和党在中期选举中败落。

5 Nov 2026, 19:05 UTC600 viewsread 5 November 2026

#墨西哥 #央行 #降息 25个基点,至6.25%,预期按兵不动。

5 Nov 2026, 18:05 UTC740 viewsread 5 November 2026

💱 外汇数据汇总 • #标普 500指数 #跌幅 扩大至4%, #纳斯达克 100指数跌6%, #道指 跌3.1%,纳指跌5.3%, #半导体 指数跌11%, #美元 兑 #日元 跌...

5 Nov 2026, 17:50 UTC801 viewsread 5 November 2026

#美国 国防部长赫格塞思最快下周可能就会面临弹劾。(福克斯新闻)

5 Nov 2026, 17:05 UTC932 viewsread 5 November 2026

#谷歌 公司在 #美国 Wyoming打造自家第一个数据中心,将投资170亿 #美元 。

5 Nov 2026, 17:05 UTC881 viewsread 5 November 2026

【Open #AI 推出GPT-6 Cyber,其网络安全评级为“关键”级】 #OpenAI 向一小部分经过审核的客户发布了GPT-6 Cyber——一款专为发现和利用安全漏洞而设计的模型,并根据其安全框架将其在网络安全方面的 #风险 评级定为“关键”。 OpenAI表示,鉴于恶意网络攻击者滥用AI的企图日益增多,该模型旨在帮助安全研究人员发现漏洞、测试其可被利用的方式,并在攻击者得手之前修复这些缺陷。 --- 本条新闻由树洞赞助 树洞 一个匿名分享秘密和诉说心事的地方 树洞入口 @TheTreeHoleBot

Showing the 12 most recent of 2,670 posts we hold for @FinanceNewsDaily. 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 6 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.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

财经慢报
@Financial_Express · 36,976
#1
Telo News 简体中文 - 加密货币|DeFi |Web3
@telonews_cn · 80,252
#2
竹新社
@tnews365 · 166,183
#3
风向旗参考快讯
@xhqcankao · 167,046
#4
在花🎗️科技圈
@zaihuapd · 288,975
#5
东南亚大事件 @svip
@bx666 · 462,518
#6
LoopDNS资讯播报
@DNSPODT · 73,228
#7
财经快讯
@fnnew · 8,643
#8
金十数据
@jin10data · 11,256
#9
每日消费电子观察
@CE_Observe · 77,211
#10
Solidot
@solidot · 48,385
#11
金色财经/币圈快讯7*24小时
@jinseBTC · 23,937
#12
Yummy 😋
@GodlyNews1 · 70,867
#13
金色财经新闻频道
@jinse2017 · 22,592
#14
💯【佳佳】美食素材圈💯
@sucai177 · 97,834
#15
cnBeta.COM中文业界资讯站 - 总频道(精选新闻)
@cnbeta_com · 27,447
#16
经济信息联播
@eco_cn · 11,921
#17
币圈新闻即时快讯🅥
@ppbbb · 21,799
#18
Global Macro View
@Marcoview666 · 5,469
#19
加美财经causmoney
@causmoney · 9,013
#20
聚焦全球
@InsightGlobal · 834
#21
PANews Web3丨加密货币丨区块链新闻频道
@ChannelPANews · 23,574
#22
Newlearnerの自留地
@NewlearnerChannel · 68,109
#23
大河马中文财经新闻分享
@chinesecaixin · 7,679
#24
东南亚大事件-聚焦时事
@pp854 · 61,158
#25
科技&趣闻&杂记
@kejiqu · 36,752
#26
雪球7X24快讯
@xueqiu7x24 · 843
#27
敏感经济信息分享
@pelosi3 · 72,384
#28
WikiFX 外汇天眼官方频道 (中文)
@wikifxzhcn · 4,592
#29
蓝点网订阅频道
@landiansub · 46,879
#30
金十数据 闪电资讯
@jin10light · 22,056
#31
分叉财经(crypto news)
@fenchacaij · 232,102
#32
纽约时报 全文 实时推送
@niuyueshibao_rss · 34,312
#33
💬 60秒早间阅读
@NEWSPJAPK · 18,435
#34
Readhub
@readhub_cn · 8,600
#35
英为财情 Investing
@ywcq233 · 1,024
#36
股市信息差小作文 A股票
@hejrb2333 · 21,745
#37
校长读报
@XiaoZhangDuBao · 9,505
#38
电报时报
@times001 · 84,412
#39
华尔街日报 股票财经新闻
@hejrb233 · 10,673
#40
彭博中文 股票财经新闻
@BloombergZh · 12,441
#41
财联社
@caijing_news · 1,265 (as read 24 August 2026)
#42
VPS信号旗播报
@vps_xhq · 50,678
#43
财经资讯7x24
@livenews_7x24 · 1,927
#44
≋財≋經≋殘≋酷≋史≋
@CruelsHistoryOfFinancial · 9,808
#45
看鉴中国 OutsightChina
@OutsightChina · 41,835
#46
华尔街日报 RSS
@wsj_rss · 17,589
#47
每日沙雕墙
@woshadiao · 114,545
#48
海外大事件-USD1
@usd1 · 253,955 (as read 24 August 2026)
#49
币圈财经新闻
@Btc_789 · 3,896
#50
ahhhhfs|A姐分享
@abskoop · 303,975
#51
少数派sspai
@sspai · 38,979
#52
吴哥时报
@wgsb · 197,148 (as read 24 August 2026)
#53
「DJ十七音乐私人订制」金富德州 @JFDZ 冠名
@dj17 · 71,956
#54
汉城DJ歌单(78.com 冠名 )
@gedan · 10,450
#55
纽约时报双语新闻
@nyt_bilingual · 10,168
#56
0
@lookworld88888 · 3,818
#57
BlockBeats
@theblockbeats · 37,874
#58
中国数字时代
@cdtchinesefeed · 51,923
#59
 Apple Nuts
@AppleNuts · 37,646
#60

Read from Telegram’s recommendation API, most recently 24 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

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.

华尔街日报
@HuaErJie1 · 60,834
Telegram ranks this channel #5 of 80 here — alongside 79 others — read 20 August 2026
美国之音
@voachinese · 42,194
Telegram ranks this channel #6 of 63 here — alongside 62 others — read 3 September 2026
外滩读书会-最新报纸、杂志、财经报告及流行电子书分享
@readingclubus · 28,809
Telegram ranks this channel #8 of 41 here — alongside 40 others — read 8 September 2026
股市宏观策略行业研报 A股票
@hgclhyyb · 19,836
Telegram ranks this channel #9 of 54 here — alongside 53 others — read 1 October 2026
敏感经济信息分享
@pelosi3 · 72,384
Telegram ranks this channel #10 of 51 here — alongside 50 others — read 20 August 2026
Telo News 简体中文 - 加密货币|DeFi |Web3
@telonews_cn · 80,252
Telegram ranks this channel #10 of 65 here — alongside 64 others — read 18 August 2026
即刻精选
@jike_collection · 35,851
Telegram ranks this channel #12 of 48 here — alongside 47 others — read 2 September 2026
竹新社
@tnews365 · 166,183
Telegram ranks this channel #14 of 59 here — alongside 58 others — read 12 August 2026
金十数据 闪电资讯
@jin10light · 22,056
Telegram ranks this channel #17 of 78 here — alongside 77 others — read 3 September 2026
FREE 中文
@freechinese · 27,747
Telegram ranks this channel #19 of 55 here — alongside 54 others — read 10 September 2026
看鉴中国 OutsightChina
@OutsightChina · 41,835
Telegram ranks this channel #21 of 58 here — alongside 57 others — read 29 August 2026
分叉财经(crypto news)
@fenchacaij · 232,102
Telegram ranks this channel #21 of 83 here — alongside 82 others — read 17 August 2026
zaobao.sg 早报
@zaobaosg · 46,704
Telegram ranks this channel #22 of 59 here — alongside 58 others — read 1 September 2026
金色财经新闻频道
@jinse2017 · 22,592
Telegram ranks this channel #24 of 60 here — alongside 59 others — read 20 September 2026
科技&趣闻&杂记
@kejiqu · 36,752
Telegram ranks this channel #24 of 48 here — alongside 47 others — read 1 September 2026
电报时报
@times001 · 84,412
Telegram ranks this channel #25 of 66 here — alongside 65 others — read 18 August 2026
观水谭 A股市日记 🅥
@Guanshuitan · 33,885
Telegram ranks this channel #32 of 58 here — alongside 57 others — read 1 October 2026
PANews Web3丨加密货币丨区块链新闻频道
@ChannelPANews · 23,574
Telegram ranks this channel #42 of 96 here — alongside 95 others — read 17 September 2026
Time经济观察
@TimeHorizonX · 21,038
Telegram ranks this channel #45 of 54 here — alongside 53 others — read 25 September 2026
金色财经/币圈快讯7*24小时
@jinseBTC · 23,937
Telegram ranks this channel #46 of 72 here — alongside 71 others — read 17 September 2026
定錨產業筆記
@investanchors · 19,819
Telegram ranks this channel #50 of 80 here — alongside 79 others — read 29 September 2026
金色财经
@jinsecaijinpingdao · 218,888
Telegram ranks this channel #51 of 90 here — alongside 89 others — read 17 August 2026
中国数字时代
@cdtchinesefeed · 51,923
Telegram ranks this channel #56 of 60 here — alongside 59 others — read 29 August 2026

This channel appears in 23 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 5 November 2026 — this entry's latest reading, not the date you are reading this.

“【华尔街见闻】- 财经时讯 | AI 实时互动” (@FinanceNewsDaily), 59,124 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/FinanceNewsDaily.

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.