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Channel

실버만삭스의 루틴

@silvermansachs_routine

2 usernames

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

7,884subscribers

-229 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001649043417
TypeChannel
Usernames@silver_mansachs @silvermansachs_routine
Description롱·숏 모두에게 균형잡힌 시각을 제공합니다. ※본 채널은 매수·매도를 권하지 않습니다.
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live7 November 2026
Measurements held27
On Telegramt.me/silvermansachs_routine

Topic

Other / unclassifiable — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 95% 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.

Growth

28,2344,1186 August 2026 — 8,113 subscribers6 August 2026 — 8,113 subscribers6 August 2026 — 8,112 subscribers9 August 2026 — 8,117 subscribers12 August 2026 — 8,101 subscribers16 August 2026 — 8,082 subscribers19 August 2026 — 8,077 subscribers23 August 2026 — 8,076 subscribers26 August 2026 — 8,073 subscribers29 August 2026 — 8,062 subscribers1 September 2026 — 8,061 subscribers5 September 2026 — 8,057 subscribers10 September 2026 — 8,052 subscribers14 September 2026 — 8,040 subscribers18 September 2026 — 8,026 subscribers28 September 2026 — 8,044 subscribers5 October 2026 — 8,166 subscribers12 October 2026 — 8,189 subscribers15 October 2026 — 8,230 subscribers18 October 2026 — 8,234 subscribers21 October 2026 — 8,229 subscribers24 October 2026 — 8,220 subscribers27 October 2026 — 8,212 subscribers30 October 2026 — 8,179 subscribers2 November 2026 — 2 subscribers7 November 2026 — 7,884 subscribers7 November 2026 — 7,884 subscribers7,8846 August 20267 November 2026
27 measurements spanning 94 days, net -229. 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”.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)SubscribersChange
7 Nov 2026, 17:227,884no change
7 Nov 2026, 16:477,884+7,882
2 Nov 2026, 00:382-8,177
30 Oct 2026, 03:368,179-33
27 Oct 2026, 00:448,212-8
24 Oct 2026, 05:208,220-9
21 Oct 2026, 06:278,229-5
18 Oct 2026, 13:468,234+4
15 Oct 2026, 17:418,230+41
12 Oct 2026, 12:118,189+23
5 Oct 2026, 19:408,166+122
28 Sept 2026, 12:408,044+18
18 Sept 2026, 12:378,026-14
14 Sept 2026, 06:158,040-12
10 Sept 2026, 15:178,052-5
5 Sept 2026, 16:018,057-4
1 Sept 2026, 15:358,061-1
29 Aug 2026, 20:428,062-11
26 Aug 2026, 18:058,073-3
23 Aug 2026, 17:058,076first reading

Engagement

251 posts held, back to 5 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 20 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
14.4%
avg views ÷ 7,884 subscribers
Avg views / post
1,130
20 posts measured
Reaction rate
0.24%
reactions ÷ views · ER floor
Posts in window
20
of 251 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 17 of 20 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 7 November 2026
Posts held251 (5 August 2026 – 7 November 2026)
Views total22,679
Reactions total48
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Nov 2026, 17:22 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
18
Links
1

Lifetime counters from Telegram’s own channel header, read 7 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
33s
Average length
33s

Measured directly from 1 video 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.

Reaction mix

266 reactions across 57 posts, in 9 distinct kinds. The most used accounts for 82.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
custom 540487043393992290821882.0%
❤228.27%
🔥93.38%
🤷41.50%
🤷‍♂41.50%
😁31.13%
🤣31.13%
🥱20.752%
🤮10.376%

Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.

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 69 of the 251 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 280 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 251 most recent posts we hold, published 5 August 2026 to 7 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: 3 of 20 posts held from the last 30 days (15.0%) 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).

7 Nov 2026, 15:14 UTC362 views1 reactionsread 7 November 2026
Photo

📊 모건스탠리|미 중간선거 결과가 코스피에 주는 의미 ━━━━━━━━━━━━ 📝 세줄요약 1️⃣ 민주당이 상·하원 모두 장악하고 텍사스·오하이오·조지아·아이오와 주지사도 가져감 → 미국 데이터센터 인허가 속도**가 AI 심리의 변수로 부상 2️⃣ 선거·중동 같은 외부 변수로 관망하던 자금이 있음. 변수가 걷히면 **11월 코스피 변곡 가능. 관건은 AI 심리 3️⃣ 업종 차별화 예상: 금융·AI 외 설비투자·퀄리티 소비재 유리. 반도체·발전·방산은 블루웨이브를 상당 부분 이미 반영했지만 단기 흐름은 미지근 ━━━━━━━━━━━━ 📉 시장 반응 (11/3) • 미국 S&P·나스닥 각 +1.7%. 다만 AI를 쓰는 기업(adopter)은 강세, AI 인프라 기업(enabler)은 약세 • 코스피 5,683.80 (+0.62%), 오전 약세 후…

❤1

7 Nov 2026, 15:06 UTC375 views2 reactionsread 7 November 2026
Photo

#중국 # 모건스탠리 중국 주식전략: 미 중간선거 영향 ## 세줄요약 1. 민주당이 의회를 장악해도 미·중 갈등의 방향은 그대로이고, 형태만 바뀐다. 정책이 급변할 가능성은 줄지만 대중 강경 기조는 초당적이다. 2. 전달 경로는 4개다: AI 차별화, 무역 안정, 유가·금리 하락, 녹색에너지 복귀. 지수 전체가 재평가되기보다는 업종 안에서 선별적 로테이션**이 일어날 것으로 본다. 3. 밸류는 역사적 저점 대비 10% 위에 있고, 심리는 과매도이며, 국가대 매수와 자사주 매입 대출 같은 안정화 장치가 있다. 그래서 **시장 전체에 공격적으로 베팅하기보다 여러 업종에서 고르는 종목 선별**을 권한다. --- ## 핵심 논리: "방향이 아니라 형태" - 민주당 의회는 행정부를 재정·외교·내정 전반에서 견제한다. 2025년처럼 행정명령으로 …

❤2

6 Nov 2026, 07:22 UTC553 views2 reactionsread 7 November 2026
Forwarded from @easobi

공매도 금지시 일어나는일 1/ 주말에 공매도 금지 발표 2/ 채널장들 공매도 잔고 많은 순서대로 나래비 세워서 올림 3/ 개장과 함께 숏 많은 애들만 불꽃 슈팅 4/ 개인들 그거 먹으려고 홀딩하던 주식 던지고 저퀄리티 주식에 달려듬 5/ 외국인 롱숏 청산으로 퀄리티 주식 초과 하락 6/ 지수 횡보에 잡주 전성시대

🔥2

6 Nov 2026, 05:38 UTC≈2,270 views4 reactionsread 7 November 2026
Photo

$APP 앱러빈 +31.3% 마감 | 3Q26: "고쳤다"던 말을 숫자로 증명했습니다 (회사소개) 앱러빈은 모바일 게임 광고 시장의 1위 회사입니다. 게임사가 "우리 게임을 깔아줄 유저"를 찾을 때, 앱러빈의 AI 광고 엔진 액손(Axon)이 수많은 게임 안 광고 자리 중 어디에 어떤 광고를 띄워야 설치하고 결제까지 할지 예측해 연결해주는데요. 이 엔진이 워낙 잘 맞혀서 매출의 80% 넘게 이익으로 남기는, 광고 회사 중에서도 손꼽히게 마진이 높은 회사입니다. 최근엔 같은 엔진으로 게임이 아닌 쇼핑몰(이커머스) 광고주까지 끌어들이며 두 번째 성장축을 만들고 있습니다. 배경부터 보면, 2분기에 앱러빈은 모델 개선이 없어 실적이 기대에 못 미쳤고 주가는 연초 대비 약 -40%까지 빠졌습니다. 당시 회사는 "경쟁 탓이 아니라 우리 실수(foot…

❤4

6 Nov 2026, 05:15 UTC≈1,270 views2 reactionsread 7 November 2026
Photo

$U 유니티 +15.0% 마감 (11/5) | 3Q26: AI에 잡아먹힐 줄 알았던 게임엔진이 광고로 살아났습니다 (회사소개) 유니티는 게임을 만드는 도구인 "게임엔진" 회사입니다. 전 세계 모바일 게임 상당수가 유니티로 만들어지는데요. 사업은 둘로 나뉩니다. 개발자에게 엔진을 구독으로 파는 Create, 그리고 그렇게 만들어진 게임 안에 광고를 붙여 돈을 버는 Grow입니다. Grow의 핵심은 2025년 출시한 AI 광고 엔진 벡터(Vector)로, 어떤 유저에게 어떤 게임 광고를 보여줘야 설치하고 돈을 쓸지 예측합니다. 몇 년 전 광고 사업에서 크게 헛발질하며 앱러빈에 밀렸던 회사라, 벡터가 반격의 무기입니다. 숫자는 기대를 크게 넘었습니다. 벡터가 전 분기 대비 +40% 성장해 회사 가이던스(+20%)의 2배를 냈고, 전체 매출은 +…

❤2

6 Nov 2026, 04:03 UTC≈1,250 views2 reactionsread 7 November 2026
Photo

$IRM 아이언마운틴 -11.4% 마감 (11/5) | 3Q26: 문서 창고가 데이터센터 회사가 되는 중입니다 (회사소개) 아이언마운틴은 원래 기업의 종이 문서를 맡아 보관해주는 "문서 창고" 회사입니다. 은행·병원·정부가 법적으로 오래 보관해야 하는 서류를 맡기는데, 한번 들어오면 잘 안 나가서 38년 연속 보관 매출이 늘어난 안정적인 현금 창출원인데요. 이 현금을 바탕으로 지금은 두 가지 성장 사업을 키우고 있습니다. 하이퍼스케일러에게 임대하는 데이터센터(DC), 그리고 기업·데이터센터에서 나온 서버와 메모리를 회수해 데이터를 지우고 재판매하는 IT 자산 처분(ALM)입니다. 리츠(REIT)라서 배당도 꾸준히 올립니다. 숫자는 좋았습니다. 매출 +13%, 주당 AFFO(리츠의 실질 이익) +16%로 둘 다 자체 전망을 넘었고, 연간 가…

❤2

6 Nov 2026, 01:00 UTC≈2,600 views4 reactionsread 7 November 2026
Photo

$NET 클라우드플레어 +14.7% (11/5 시간외) | 3Q26: AI 에이전트가 늘수록 문지기가 바빠집니다 (회사소개) 클라우드플레어는 인터넷 트래픽이 웹사이트에 도착하기 전에 한 번 거쳐 가는 "관문"을 운영하는 회사입니다. 전 세계 데이터센터에 서버를 깔아두고 웹사이트를 빠르게 전달하고(CDN), 디도스 같은 공격과 악성 봇을 걸러주는데요. 전 세계 웹사이트 상당수가 이 관문 뒤에 있다 보니, 누가 어떤 트래픽을 보내는지 가장 넓게 보는 회사 중 하나입니다. 최근엔 개발자가 이 관문 위에서 직접 앱과 AI 기능을 돌릴 수 있는 Workers 플랫폼까지 키우며 "엣지 클라우드" 회사로 넓혀가고 있습니다. 숫자는 매튜 프린스 CEO 말대로 "역대 최고의 분기"였습니다. 매출 $782.5M으로 +39%, 약 4년 만에 가장 빠른 성장인…

❤4

Showing the 12 most recent of 251 posts we hold for @silvermansachs_routine. 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

Republishes

Channels on the register whose posts this channel has forwarded.

Republishes 57 registered channels. The 48 listed are the ones this channel has forwarded most; the rest are counted here but not each listed.

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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 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.

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 7 November 2026 — this entry's latest reading, not the date you are reading this.

“실버만삭스의 루틴” (@silvermansachs_routine), 7,884 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/silvermansachs_routine.

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.