中東戰事推升通膨疑慮!美債重挫 Fed今年升息機率逼近五成
❤3🎉1

Channel
@LibaoFinanceSchool
On this record: Topic · Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry
2,926subscribers
-16 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001759244418 |
|---|---|
| Type | Channel |
| Username | @LibaoFinanceSchool |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 15 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/LibaoFinanceSchool |
National news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 15 September 2026 and assigned it the closest of 31 fixed categories, at 60% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 04:36 | 2,926 | -3 |
| 13 Sept 2026, 08:18 | 2,929 | -2 |
| 9 Sept 2026, 19:21 | 2,931 | -2 |
| 4 Sept 2026, 11:17 | 2,933 | +8 |
| 1 Sept 2026, 07:06 | 2,925 | +2 |
| 29 Aug 2026, 08:53 | 2,923 | -5 |
| 26 Aug 2026, 12:46 | 2,928 | +2 |
| 23 Aug 2026, 03:37 | 2,926 | -4 |
| 19 Aug 2026, 14:26 | 2,930 | -4 |
| 16 Aug 2026, 17:36 | 2,934 | -6 |
| 13 Aug 2026, 02:53 | 2,940 | -4 |
| 10 Aug 2026, 08:41 | 2,944 | +1 |
| 7 Aug 2026, 16:54 | 2,943 | +1 |
| 7 Aug 2026, 13:32 | 2,942 | no change |
| 7 Aug 2026, 12:53 | 2,942 | first reading |
20 posts held, back to 20 March 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 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 20 March 2026. An engagement rate over an empty window would be a number about nothing.
7 reactions across 4 posts, in 2 distinct kinds. The most used accounts for 57.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 4 | 57.1% | |
| 🎉 | 3 | 42.9% |
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 4 of the 20 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 7 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 20 March 2026 to 20 March 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.
中東戰事推升通膨疑慮!美債重挫 Fed今年升息機率逼近五成
❤3🎉1
盤中速報 - 費城半導體大跌2%,報7705.7點
🎉1
川普推全國AI監管框架強化競爭力並防堵州法分歧
🎉1
Fed華勒對油價影響轉趨審慎 仍看今年稍晚降息
❤1
盤中速報 - 費城半導體大跌1.01%,報7783.54點
鉅亨速報 - Factset 最新調查:聯邦快遞FDX-US的目標價調升至425元,幅度約3.66%
鉅亨速報 - Factset 最新調查:杭庭頓(HBAN-US)EPS預估上修至1.48元,預估目標價為21.00元
盤中速報 - Crowdstrike控股(CRWD-US)大跌5%,報406.75美元
盤中速報 - 連貫(COHR-US)大跌5.04%,報261.68美元
Fed利率路徑分歧 鮑曼仍估今年三次降息
盤中速報 - 超微電腦(SMCI-US)大跌27.38%,報22.36美元
盤中速報 - 安謀控股公司(ARM-US)大漲5.76%,報137.3美元
Showing the 12 most recent of 20 posts we hold for @LibaoFinanceSchool. 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.
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.
This channel appears in 4 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“⚡️58財經新聞&卷商報告📰” (@LibaoFinanceSchool), 2,926 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/LibaoFinanceSchool.
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.