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Channel

加密货币知识库

@jmhbzsk

On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

12,541subscribers

+747 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002276973739
TypeChannel
Username@jmhbzsk
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live19 September 2026
Measurements held34
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/jmhbzsk

Topic

Crypto & trading — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 91% 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.

Growth

11,79412,54112,167.56 August 2026 — 11,794 subscribers6 August 2026 — 11,796 subscribers7 August 2026 — 11,812 subscribers8 August 2026 — 11,815 subscribers9 August 2026 — 11,834 subscribers10 August 2026 — 11,851 subscribers11 August 2026 — 11,863 subscribers12 August 2026 — 11,882 subscribers13 August 2026 — 11,905 subscribers15 August 2026 — 11,927 subscribers16 August 2026 — 11,953 subscribers17 August 2026 — 11,972 subscribers18 August 2026 — 11,981 subscribers19 August 2026 — 11,989 subscribers20 August 2026 — 11,999 subscribers22 August 2026 — 12,020 subscribers23 August 2026 — 12,041 subscribers25 August 2026 — 12,074 subscribers26 August 2026 — 12,093 subscribers27 August 2026 — 12,108 subscribers28 August 2026 — 12,128 subscribers29 August 2026 — 12,151 subscribers30 August 2026 — 12,198 subscribers31 August 2026 — 12,227 subscribers1 September 2026 — 12,244 subscribers2 September 2026 — 12,259 subscribers3 September 2026 — 12,282 subscribers5 September 2026 — 12,314 subscribers8 September 2026 — 12,378 subscribers11 September 2026 — 12,413 subscribers13 September 2026 — 12,438 subscribers15 September 2026 — 12,459 subscribers17 September 2026 — 12,503 subscribers19 September 2026 — 12,541 subscribers6 August 202619 September 2026
34 measurements spanning 44 days, net +747. 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 11,682–12,653 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)SubscribersChange
19 Sept 2026, 12:5612,541+38
17 Sept 2026, 00:2112,503+44
15 Sept 2026, 00:3712,459+21
13 Sept 2026, 08:3912,438+25
11 Sept 2026, 11:5712,413+35
8 Sept 2026, 20:1812,378+64
5 Sept 2026, 11:1512,314+32
3 Sept 2026, 15:1912,282+23
2 Sept 2026, 07:1612,259+15
1 Sept 2026, 10:2512,244+17
31 Aug 2026, 08:1612,227+29
30 Aug 2026, 09:2512,198+47
29 Aug 2026, 06:5312,151+23
28 Aug 2026, 03:5612,128+20
27 Aug 2026, 04:1812,108+15
26 Aug 2026, 07:4412,093+19
25 Aug 2026, 04:1412,074+33
23 Aug 2026, 23:0712,041+21
22 Aug 2026, 05:5412,020+21
20 Aug 2026, 23:0211,999first reading

Engagement

39 posts held, back to 19 July 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 51 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
10.2%
avg views ÷ 12,541 subscribers
Avg views / post
1,280
7 posts measured
Reaction rate
0.29%
reactions ÷ views · ER floor
Posts in window
7
of 39 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 2 September 2026
Posts held39 (19 July 2026 – 2 September 2026)
Views total8,953
Reactions total26
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Sept 2026, 22:40 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

91 reactions across 29 posts, in 7 distinct kinds. The most used accounts for 72.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤6672.5%
👍1213.2%
😱66.59%
🤣33.30%
👏22.20%
😐11.10%
🤯11.10%

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 31 of the 39 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 91 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 39 most recent posts we hold, published 19 July 2026 to 2 September 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

2 Sept 2026, 14:34 UTC243 views1 reactionsread 2 September 2026
Photo

⏺ 加密货币知识之—— 触发价与委托价 在币安的条件委托(如限价止损/止盈单)中,触发价是“开关”,委托价是“实际挂单价格”。两者的核心区别在于它们在交易流程中扮演的角色不同。 核心区别对比 触发价 (Trigger Price): 这是一个监控条件。当市场最新成交价(或标记价格)达到这个数值时,系统才会被“唤醒”,去执行下达订单的动作。它本身不参与市场撮合,订单在触发前也不会显示在买卖盘口(Order Book)中。 委托价 (Order Price/Limit Price): 这是触发条件满足后,系统真正送入市场盘口的限价单价格。这是你希望实际成交的目标价格。 具体运作场景 在管理高杠杆(例如50倍杠杆)的仓位时,保证金率对价格波动极其敏感,精准区分这两个价格是避免意外爆仓的关键。假设你持有一笔均价在 $65,266 的比特币(BTC)多单,为了控制风险,你决定设置一个限价止损单: 设置触发价: $63,200…

❤1

31 Aug 2026, 00:02 UTC≈1,040 views7 reactionsread 2 September 2026
Photo

🆔 网站名称:全天候金融洞察 ⭐ 网站功能:金融新闻 📁 网站简介:一个AI驱动的全球市场简报平台,提供全球市场的最新动态和简报,涵盖资产动态和行业趋势。 可以自动从各种金融数据源(如交易所、新闻网站、社交媒体等)收集大量的市场数据,包括价格、交易量、宏观经济指标、公司公告、新闻情绪等。 利用机器学习(ML)和深度学习(DL)算法,AI能够分析历史和实时的市场数据,识别其中的隐藏模式、趋势、相关性和非线性关系。 🔗 网站网址:点击打开

❤4👍3

30 Aug 2026, 14:20 UTC≈1,050 views2 reactionsread 2 September 2026
Photo

⏺ 加密货币知识之—— 派发与再吸筹 比特币在高位横盘停滞时,区分派发还是再吸筹,最有效的方法是结合威科夫量价结构、衍生品市场数据以及链上筹码指标进行交叉验证。 一、 核心特征对比 1. 派发(主力高位出货) • 量价关系:上涨缩量或严重滞涨,下跌伴随大成交量,反弹无力。 • 假突破方向:向上假突破(UT / UTAD 诱多突破前高后迅速放量跌回)。 • 持仓量与价格:价格停滞但合约持仓量(OI)暴增,多头杠杆严重堆积。 • 资金费率:费率持续处于偏高正值(多头持续付费但推不动现货价格)。 • 交易所净流量:大额 BTC 持续净流入中心化交易所(准备变现)。 • 筹码转移特征:长期持有者(LTH)加速减持获利,短期持有者(STH)持仓激增。 2. 再吸筹(主力中继换手) • 量价关系:回调时成交量显著萎缩(抛压枯竭),反弹或回踩支撑时放量。 • 假突破方向:向下假跌破(Spring 弹簧效应,刺穿区间低点扫掉止损后快速收回)…

❤2

30 Aug 2026, 04:00 UTC≈1,070 views2 reactionsread 2 September 2026

#频道互推 #群组推荐 枫叶の破解软件分享 财联社VIP文章分享 熊猫资源分享—破解软件/影视分享 奇趣吃瓜 资源分享 - 软件|网站|工具|破解 分享社_破解软件/公益机场VPN 【离港一二线机场收录&测评】 零度资源分享-破解软件/游戏分享 软件/节点/网站资源分享 电报频道&群组索引

👍2

29 Aug 2026, 13:36 UTC≈1,280 views3 reactionsread 2 September 2026
Photo

⏺ 加密货币知识之—— 威科夫派发 威科夫派发是市场周期中“聪明钱”(机构或大资金)在价格顶部区间将筹码转手分发给公众的过程。其核心逻辑是利用散户的看多情绪和突破买入,提供足够的流动性来完成大级别的出货,随后通常伴随着价格的快速下跌或确立长期的空头趋势。 派发区间的五个核心阶段 Phase A:停止先前的上涨 出现初次供应(PSY)和买入高潮(BC)。上涨动能耗尽,随后发生自动回落(AR)和二次测试(ST),确立震荡区间的上下边界。 Phase B:构建下跌原因 主力在区间内来回洗盘。价格在支撑与阻力之间波动,测试需求并消耗买盘,通常伴随成交量的逐渐萎缩或异常的放量滞涨。 Phase C:测试与诱多 经常出现派发后上冲(UTAD)。价格短暂突破区间顶部阻力,制造多头突破的假象,随后迅速跌回区间内。 Phase D:跌破区间内支撑 需求彻底衰竭。出现弱势信号(SOW),价格跌破区间内支撑,反弹仅能形成最后的供应点(LP…

❤3

27 Aug 2026, 14:03 UTC≈2,070 views10 reactionsread 2 September 2026
Forwarded from @biquan321Photo

孙宇晨?!景甜?! 卧槽,这特喵的是什么惊天世纪大瓜?! 3000万、5000万美元、代孕、富豪男友……这几个关键词居然全凑到一起了! 孙宇晨自己推特曝出,跟景甜谈恋爱。孙宇晨支付景甜3000万,女方同意取卵做代孕。 结果最后一刻,景甜临时加价,要5000万美元! 孙宇晨没给,景甜拿着3000万跑路,拉黑孙宇晨。 孙哥这暴脾气哪咽得下这口气,“得不到就毁掉”,直接推特实锤大揭秘,把内幕全盘托出,女方口碑瞬间全网崩塌! 这剧情,电视剧编剧都不敢这么写,真是惊呆我了...

😱6❤3🤯1

23 Aug 2026, 14:56 UTC≈2,690 views3 reactionsread 2 September 2026
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⏺ 加密货币知识之—— 行情是跌出来的 “加密货币行情是跌出来的”是交易市场(尤其是高波动、高杠杆的加密市场)中一句非常经典且深刻的经验之谈。 这句话的核心逻辑是:大牛市的起飞、强劲的涨幅,往往是在前一轮彻底的暴跌与阴跌中完成筹码洗牌、出清杠杆、挤掉泡沫后,才孕育出来的。 一、 挤掉“杠杆泡沫”,为上涨腾出流动性空间 加密货币市场天然具备极高的杠杆属性(合约、借贷、质押衍生品等)。 上涨末期的隐患: 在牛市高位,市场充满了追高多头与高倍杠杆。此时价格虽然看起来很高,但“非常脆”,稍微一点风吹草动就会引发连环爆仓。 下跌的作用: 暴跌(甚至闪崩)能最快速、最彻底地爆掉高杠杆多头,清理掉市场上的虚假流动性和未平仓合约(OI)。只有把杠杆多头清算干净,盘子变轻了,主力资金和机构后续推升价格的成本才会大幅降低。 二、 筹码换手:不坚定的手 to 坚定的手 散户与追风者的割肉: 价格长期的阴跌或剧烈暴跌,会导致高位套牢盘产生极…

❤3

23 Aug 2026, 04:01 UTC≈1,960 viewsread 2 September 2026

#频道互推 #群组推荐 严选君综合福利社 极客分享2.0 [震撼回归] 全能搜书·福利书库 白嫖小仓库 丨 抽奖福利之家 机场分享交流频道 频道藏馆 Galgame分享频道 叮当喵喵-今天你也很可爱 SCP || 每日免费节点 电报频道&群组索引

22 Aug 2026, 12:37 UTC≈2,040 views4 reactionsread 2 September 2026
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⏺ 加密货币知识之—— 比特币Ahr999指标 Ahr999指标(又称“比特币囤币指标”)是加密货币领域非常著名的一个宏观估值模型,由早期比特币布道者、知名博主 ahr999(《囤比特币》作者)创立。 该指标的核心目的是寻找比特币的最佳定投和抄底时机。它通过结合短期定投成本与长期价格趋势,将抽象的市场情绪量化为一个具体的数值,帮助交易者在狂热时保持冷静,在恐慌时敢于建仓。 指标的计算逻辑 Ahr999指标的底层逻辑是将比特币的当前价格与两个基准价格进行对比。其计算公式如下: Ahr999 = (当前价格 / 200日定投成本) × (当前价格 / 拟合指数增长估值) 公式分为两个乘数部分,分别衡量了不同维度的价格偏离度: 短期偏离度(200日定投成本): 反映了当前价格与过去200天定投买入者的平均持仓成本之间的关系。 长期偏离度(拟合指数增长估值): 根据比特币的历史币龄数据,拟合出一条长期指数级增长的趋势线。这…

👍3❤1

21 Aug 2026, 23:55 UTC≈1,690 viewsread 2 September 2026
Photo

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Showing the 12 most recent of 39 posts we hold for @jmhbzsk. 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.

Posts edited after publishing

@jmhbzsk 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.

First edit seen
8 August 2026
Most recent edit
8 August 2026

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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 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.

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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“加密货币知识库” (@jmhbzsk), 12,541 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/jmhbzsk.

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.