- 전직 헤지펀드 매니저
- 세상을 변화시키는 핵심 사건, 핵심 기업을 공부하고 주관적 생각과 투자방향을 적는 노트
- 터무니없이 틀릴 수도 있으니 주의
- 매수와 매도 의사결정의 책임은 투자자 본인에게 귀속
- 본인은 채널에서 언급한 종목이나 섹터를 예고없이 매수/매도할 수 있음
- 투자의 결과에 따른 책임을 지지 않음
Created
Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
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 10 August 2026 and assigned it the closest of 31 fixed categories, at 92% 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 (1 of the pairs behind the counts below)
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 1 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 4 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 @triple_stock. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
35 measurements spanning 51 days, net +981. 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 21,377–22,652 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
25 Sept 2026, 18:02
22,505
+22
19 Sept 2026, 05:37
22,483
+67
16 Sept 2026, 16:58
22,416
+8
14 Sept 2026, 17:20
22,408
+13
13 Sept 2026, 03:20
22,395
-4
11 Sept 2026, 03:15
22,399
+61
8 Sept 2026, 03:17
22,338
+36
4 Sept 2026, 23:57
22,302
+15
3 Sept 2026, 08:13
22,287
+11
1 Sept 2026, 23:35
22,276
+8
1 Sept 2026, 02:13
22,268
+12
31 Aug 2026, 03:55
22,256
+37
30 Aug 2026, 06:16
22,219
+31
29 Aug 2026, 03:02
22,188
+5
28 Aug 2026, 03:25
22,183
+50
27 Aug 2026, 06:46
22,133
+4
26 Aug 2026, 06:46
22,129
+18
25 Aug 2026, 05:25
22,111
+17
24 Aug 2026, 07:09
22,094
+32
22 Aug 2026, 18:04
22,062
first reading
Engagement
256 posts held, back to 4 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 59 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
32.7%
avg views ÷ 22,505 subscribers
Avg views / post
7,370
57 posts measured
Reaction rate
0.678%
reactions ÷ views · ER floor
Posts in window
57
of 256 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
Window
Rolling 30 days · latest post in window 27 September 2026
Posts held
256 (4 August 2026 – 27 September 2026)
Views total
420,008
Reactions total
2,847
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
27 Sept 2026, 02:33 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
≈5,210
Videos
≈48
Links
≈3,610
Lifetime counters from Telegram’s own channel header, read 27 September 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
15,653 reactions across 244 posts, in 18 distinct kinds. The most used accounts for 46.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
7,224
46.2%
👍
2,745
17.5%
🔥
1,400
8.94%
🙏
784
5.01%
🤮
637
4.07%
👏
504
3.22%
😱
481
3.07%
🤬
465
2.97%
🤔
426
2.72%
😁
419
2.68%
🤩
142
0.907%
🤯
136
0.869%
😢
82
0.524%
👀
57
0.364%
🕊
53
0.339%
🎉
47
0.3%
😨
30
0.192%
👻
21
0.134%
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 256 of the 256 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 16,363 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 256 most recent posts we hold, published 4 August 2026 to 27 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.
* Boris Power(OpenAI)
OpenAI 연구의 80~90%가 GPT-7, 8 및 그 이후를 목표로 하고 있으며, 거대한 Astra 교사 모델을 작은 Luna 모델로 증류한다고 밝힘
https://x.com/firesidealpha/status/2103821387307651085
* Fran Cardells (Quantoid 수석 과학자, 전 Microsoft CVP of Engineering, Data & AI 시니어 디렉터)
- Expert Call by BofA
- 제목 : KV cache, memory hierarchy & model choice
- 요약
1. 에이전틱 추론(Agentic Inference)이 메모리 수요를 구조적으로 크게 증가시킴
- 컨텍스트 윈도우가 확대되고(약 128K 토큰 → 약 1M 토큰), 여러 에이전트가 공유 작업을 수행하면서 추론 시 메모리 요구량이 급증.
- KV 캐시는 이전 토큰, 기업 컨텍스트, 가드레일, 에이전트 결정 로그를 저장해 에이전트 간 컨텍스트를 재계산 없이 이동시킴.
- 일부 에이전틱 워크로드에서 KV 캐시 크기가 모델 가중치의 최대 약 10배까지 커…
알렉산더 왕, “내가 Muse를 만들고 있는 이유”
대부분의 사람들은 자신이 무엇을 원하는지 말하지 않는다. 원하는 것이 없어서가 아니다. 우리는 끊임없이, 그리고 강렬하게 무언가를 원한다.
잠들기 직전의 순간이나 집으로 돌아가는 차 안에서 멍하니 상상에 잠길 때 그런 생각들이 떠오른다. 가족과 더 많은 시간을 보내고 싶고, 사회적 불안을 극복하고 싶고, 더 건강한 음식을 먹고 싶다. 빵집을 열고 싶거나, 앱을 만들고 싶거나, 그저 정신없이 돌아가는 삶 속에서 잠깐이라도 평온한 시간을 더 갖고 싶을 수도 있다.
하지만 우리는 이런 꿈을 말로 꺼내볼 기회조차 좀처럼 갖지 못한다. 그리고 그 꿈이 실제로 이루어지는 경우는 더욱 드물다.
우리가 자신의 꿈을 명확히 말할 수 없다면, 대부분 그 꿈에 도달할 수도 없다. 세상은 수많은 서류와 문…
* Nebius CRO, Marc Boroditsky
- "현재 들어오는 수요의 75%를 거절하고 있다"
“현재 저희 파이프라인을 보면, GPU 한 개마다 바로 계약할 준비가 된 고객이 있습니다. 정확히 말하면 GPU 한 개당 계약할 준비가 된 고객이 4명 있습니다. 이게 어떤 의미인지 잠시 생각해보시면 됩니다.
지금 저희는 수요의 75%에 ‘안 된다’고 말하고 있는 상황입니다. 이것이 현재의 상황입니다.”
“그렇다면 이런 상황이 앞으로도 계속될까요? 고객들이 저희와 공유하고 있는 계획, 그리고 고객들이 저희에게 요구하는 장기적인 공급 약정을 보면, 이런 수요는 실제로 내년까지 상당히 강하게 이어지고 있습니다.
특히 고객들이 내년 중반 시점에 수만 개 규모의 GPU를 확보하기 위해 지금 계약을 체결하려는 의향이 매우 강합니다.”
…
메타 뮤즈에 대한 증권사 시각 비교 (GS, JPM, MS, Bofa)
1. 뮤즈 파트너십 및 커넥터 확대에 대한 시각
• 4개사 모두 월마트, 베스트바이, 딕스스포팅굿즈, 세포라, 웨이페어 등 대형 리테일러와의 신규 커넥터 파트너십을 핵심 긍정 요인으로 공통 언급
• 모건스탠리는 이를 $30조 규모의 소비자 에이전틱 지출 시장을 여는 열쇠로 해석하며, 수수료율이 낮게 유지되는 것이 오히려 경쟁사(구글 등)를 압박하는 전략이라고 평가
• JP모건은 뮤즈 커넥터가 이미 2,000개 이상의 애플리케이션과 연동되었다는 구체적 수치를 제시하며, 향후 수백만 비즈니스가 에이전트 대 에이전트 방식으로 상호작용할 것으로 전망
• 골드만삭스는 뮤즈의 차별점이 단순한 모델 지능이 아니라 메타의 글로벌 유통망, 퍼스트파티 데이터, 컴퓨트, 서드파티 커…
속보: 전직 앤트로픽 연구원 제이컵 콕슨이 AI가 인류의 존립을 위협할 수 있다고 경고하는 캠페인을 시작해 온라인에서 큰 반향을 일으키는 과정에서, 이른바 ‘AI 파멸론 진영의 홍보회사’와 협력했다는 탐사보도가 나왔다.
https://x.com/Polymarket/status/2103259306372276381
골드만삭스는 현재 2030년 전 세계 데이터센터 용량이 217GW에 이를 것으로 전망(이는 기존 전망치 168GW에서 대폭 상향된 수치)
또한 다음 전망도 상향 조정했습니다.
2025~2030년 데이터센터 전력 수요 증가율: 기존 +117% → +170%
2030년 BTM(Behind-the-Meter·계량기 후단/자가발전) 전력 용량: 기존 40GW → 67GW
AI 데이터센터 증설 속도와 이에 필요한 전력 수요를 기존 예상보다 훨씬 강하게 보고 있으며, 특히 전력망을 거치지 않고 데이터센터 현장에서 직접 공급하는 자가발전·분산전원 수요 전망을 67.5% 상향
빌 애크먼(Bill Ackman)
연준이 단기 금리를 인상하면 인플레이션이 낮아진다는 전제는, 높은 금리가 수요와 투자를 줄인다는 믿음에 기반하고 있습니다.
하지만 만약 금리가 올라가도 수요와 투자가 줄어들지 않는다면 어떨까요?
초지능 경쟁에서 승리했을 때 얻는 투자수익률(ROI)이 사실상 무한대에 가깝기 때문에, 지능과 에너지에 대한 수요는 높은 금리에도 영향을 받지 않고, 컴퓨팅 수요 역시 계산하기 어려울 정도로 계속 커질 수 있습니다.
그렇다면 역사적으로 매우 특수한 지금 이 시점에서는, 금리 인상이 오히려 더 높은 인플레이션을 초래할 수도 있지 않을까요?
금리 비용이 사실상 모든 상품과 서비스의 비용에 반영되기 때문입니다.
그리고 문제는 더 복잡해집니다.
연준이 금리를 더 올릴수록 인플레이션은 더 높아지고, 그러면 연준은 다…
2026년 이후 5대 하이퍼스케일러 Capex 전망치 상향 추이 (GS)
1. Capex 상향 규모
• 2026~27년 합산 capex 컨센서스 전망치는 연초(2025년 말) 1,138억 달러에서 현재(2026년 9월 23일 기준) 1,892억 달러로 약 66% 상승
2. 기업별 Capex 전망치 변화
• 구글은 2,530억 달러에서 5,070억 달러로 약 2배 수준으로 확대되며 5개사 중 가장 큰 절대 증가폭을 기록
• MS는 2,270억 달러에서 3,730억 달러로, 아마존은 3,010억 달러에서 5,050억 달러로 각각 상승
• 메타는 2,300억 달러에서 3,330억 달러로, 오라클은 1,260억 달러에서 1,740억 달러로 상승
3. 시사점
• 연초 대비 짧은 기간 내 대규모 상향 조정이 이루어진 것으로, 5개사 모두 …
Showing the 12 most recent of 256 posts we hold for @cahier_de_market. 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.
Republished by 91 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.
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 9 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.
Named by
Channels on the register whose posts name this channel's handle.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@cahier_de_market named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@firstadopter named in 1 post, 27 August 2026 – 27 August 2026
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.
Read from Telegram’s recommendation API, most recently 20 September 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.
AWAKE - 52주 신고가 모니터링 @awake_realtimeCheck · 22,632 Telegram ranks this channel #37 of 92 here — alongside 91 others — read 20 September 2026
루팡 @bornlupin · 48,199 Telegram ranks this channel #41 of 91 here — alongside 90 others — read 2 September 2026
키움증권 미국주식 톡톡 @kwusa · 36,480 Telegram ranks this channel #42 of 92 here — alongside 91 others — read 2 September 2026
선수촌 @athletes_village · 21,621 Telegram ranks this channel #45 of 88 here — alongside 87 others — read 23 September 2026
엄브렐라리서치 Jay의 주식투자교실 @Jstockclass · 26,067 Telegram ranks this channel #46 of 90 here — alongside 89 others — read 13 September 2026
도PB의 생존투자 @survival_DoPB · 22,243 Telegram ranks this channel #54 of 90 here — alongside 89 others — read 21 September 2026
TNBfolio @TNBfolio · 24,657 Telegram ranks this channel #56 of 93 here — alongside 92 others — read 15 September 2026
시장 이야기 by 제이슨 @bumgore · 35,352 Telegram ranks this channel #57 of 89 here — alongside 88 others — read 2 September 2026
조기주식회 공부방 @EarlyStock1 · 24,432 Telegram ranks this channel #65 of 91 here — alongside 90 others — read 16 September 2026
YIELD & SPREAD @yieldnspread · 22,018 Telegram ranks this channel #71 of 89 here — alongside 88 others — read 21 September 2026
[메리츠 Tech 김선우, 양승수, 김동관] @merITz_tech · 24,059 Telegram ranks this channel #71 of 92 here — alongside 91 others — read 17 September 2026
에테르의 일본&미국 리서치 @aetherjapanresearch · 34,509 Telegram ranks this channel #72 of 89 here — alongside 88 others — read 3 September 2026
하나 중국/신흥국 전략 김경환 @HANAchina · 35,301 Telegram ranks this channel #75 of 92 here — alongside 91 others — read 2 September 2026
Rafiki research @rafikiresearch · 20,596 Telegram ranks this channel #78 of 88 here — alongside 87 others — read 26 September 2026
서화백의 그림놀이 🚀 @easobi · 23,597 Telegram ranks this channel #79 of 87 here — alongside 86 others — read 18 September 2026
💯똥밭에 굴러도 주식판 @daegurr · 23,375 Telegram ranks this channel #80 of 83 here — alongside 82 others — read 18 September 2026
선진짱 주식공부방 @sunstudy1234 · 54,428 Telegram ranks this channel #82 of 89 here — alongside 88 others — read 2 September 2026
시황맨의 주식이야기 @shmstory · 38,160 Telegram ranks this channel #83 of 89 here — alongside 88 others — read 2 September 2026
타점 읽어주는 여자(타자) @tazastock · 40,320 Telegram ranks this channel #83 of 89 here — alongside 88 others — read 2 September 2026
급등일보 미국주식🇺🇸 속보·매크로·리서치 @FastStockNewsUSA · 40,651 Telegram ranks this channel #85 of 89 here — alongside 88 others — read 2 September 2026
김찰저의 관심과 생각 저장소 @kimcharger · 24,877 Telegram ranks this channel #86 of 88 here — alongside 87 others — read 15 September 2026
그로쓰리서치(Growth Research) [독립리서치] @growthresearch · 40,159 Telegram ranks this channel #88 of 90 here — alongside 89 others — read 2 September 2026
This channel appears in 22 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 25 September 2026 — this
entry's latest reading, not the date you are reading this.
“카이에 de market” (@cahier_de_market), 22,505 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/cahier_de_market.
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.
