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 65% 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 in near-verbatim form 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 (2 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
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 63 comparable posts for this entry, running 5 July 2026 to 12 November 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).
Views per post sit far above this size band
21,300 average views per post against 22,865 subscribers — an engagement rate of 93.0%. Across the 54,896 registered channels in the same cohort — 10,000–31,622 subscribers — the middle half sit between 4.13% and 19.2%, with a median of 9.47%.
What this was computed from
Window
30 days (6 October 2026 – 5 November 2026)
Posts measured
13 of 13 published in the window (0 exact, 13 rounded by Telegram)
Views totalled
276,520
Mature posts only
93.0% over 13 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the keys clone_source · err_high, last confirmed 12 November 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.
Growth
64 measurements spanning 98 days, net +897. 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 21,837–23,020 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)
Subscribers
Change
11 Nov 2026, 18:30
22,870
+31
9 Nov 2026, 23:17
22,839
-5
8 Nov 2026, 16:39
22,844
-8
7 Nov 2026, 06:50
22,852
-9
6 Nov 2026, 05:37
22,861
-4
5 Nov 2026, 04:08
22,865
-1
4 Nov 2026, 04:30
22,866
-12
3 Nov 2026, 00:37
22,878
+8
1 Nov 2026, 22:27
22,870
-2
1 Nov 2026, 00:09
22,872
+1
30 Oct 2026, 20:44
22,871
-7
29 Oct 2026, 18:20
22,878
+5
28 Oct 2026, 15:28
22,873
-3
27 Oct 2026, 15:00
22,876
+1
26 Oct 2026, 16:27
22,875
+1
25 Oct 2026, 14:31
22,874
-2
24 Oct 2026, 17:06
22,876
-7
23 Oct 2026, 18:59
22,883
+7
22 Oct 2026, 16:50
22,876
+26
21 Oct 2026, 12:44
22,850
first reading
Engagement
70 posts held, back to 5 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 108 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
80.3%
avg views ÷ 22,870 subscribers
Avg views / post
18,400
16 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
16
of 70 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 12 November 2026
Posts held
70 (5 July 2026 – 12 November 2026)
Views total
293,970
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Nov 2026, 03:01 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
≈3,270
Links
≈2,580
Lifetime counters from Telegram’s own channel header, read 13 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.
Recent posts
Telegram’s own ‘edited’ marker: 5 of 16 posts held from the last 30 days (31.3%) 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).
[이그전] 유가 하락이 만든 반등은 유지 가능한가?
안녕하세요. KB증권 자산배분 이은택입니다.
1) 수많은 증시 하락 요인 중 가장 핵심은 ‘자본조달 문제’이고 자금 조달 문제의 근원에는 ‘인플레 우려’가 핵심입니다.
2) 따라서 탑다운 측면에선 ‘인플레’가 향후 시장의 반등과 붕괴를 만들 중요한 카드로 여기고 있습니다.
3) 이런 측면에서 어제 유가하락이 증시를 끌어올린 것은 의미가 있습니다. 다만 더 중요한 것은 근원 물가의 향후 방향입니다.
- URL: https://m.blog.naver.com/egzion/224471368550
[2027년 자산시장 전략] Gravity’s Rabbit Hole
안녕하세요. KB증권 자산배분 이은택입니다.
1) 반년 전 「Gravity Rules」에서 현재 시장을 ‘AI 버블 후반부‘로 진단했습니다. 그리고 실제로 지난 하반기, 버블 후반부의 징후들은 대부분 현실이 됐습니다. 이 자료는 그 후속편입니다.
2) 이제 남은 카드는 ’인플레이션‘입니다. 시장을 살릴 카드도, 끝낼 카드도 모두 인플레이션에 달려있습니다. 그래서 이번 자료는 많은 지면을 인플레이션 분석에 할애했습니다.
3) 2027년 자산시장에선 장기 국채와 우량 기업의 중단기 크레딧을 선호합니다. 지역별로는 유로존을 여전히 경계합니다.
- URL: https://bit.ly/3WybQYf
■ "2027년 자산시장 전망" 2차 웨비나 공지
안녕하세요. 이은택입니다. "2027년 자산시장 전망" 웨비나를 진행합니다.
이번 웨비나는 '11/9 (월), 애널리스트 데이' 이후로 미루느라 좀 늦어졌습니다.
주제: [2027년 자산시장 전망] Gravity's Rabbit Hole
일시: 2026년 11월 10일 오전 10:00
1. Gravity Rules: 대부분 모습을 드러낸 버블 후반 시그널
2. 주식: 남아 있는 기회와 붕괴의 퍼즐, 인플레 경로에 대한 전망
3. 채권/대체: 펀딩은 유로화, 투자는 장기국채, 부동산은 하반기 이후 신중
본 세미나는 KB증권 거래 기관고객을 대상으로 합니다.
운용역 성함과 회사를 기입해야 초대장이 발송됩니다.
https://us02web.zoom.us/webinar/register/WN_…
[이그전] 오늘 밤 발표되는 ‘ISM제조업지수’에서 꼭 체크할 것들
안녕하세요. KB증권 자산배분 이은택입니다.
1) ISM제조업지수는 주식시장 특히 시크리컬 업종인 반도체 사이클에 강한 선행성을 가진 지표입니다.
2) 일반적으로 ISM제조업지수는 50 후반부에 정점을 보이는데, 이번엔 지난 7월 55 기록 이후 주춤하고 있습니다.
3) 이것 역시 인플레에 의해 정점이 결정될 것으로 보는데, 단기엔 압력이 추가될 가능성과 이후 완화되는 흐름 정도를 예상할 수 있습니다.
- URL: https://m.blog.naver.com/egzion/224461927319
[이그전] 한꺼번에 몰려 온 인플레 완화 재료들
안녕하세요. KB증권 자산배분 이은택입니다.
1) 최근 인플레 완화와 관련된 뉴스들이 집중되고 있습니다. 특히 정제유 측면에서 그렇습니다.
2) 러시아 디젤 수출 재개, 한국 디젤 수출 재개, 이란협상 기대 등입니다. 또한 중동 원유 수출이 정상화된 것의 효과도 나타나고 있습니다.
3) 정치적으론 이스라엘 총선과 브라질 대선이 불러오는 나비효과에 대한 기대도 있습니다.
- URL: https://m.blog.naver.com/egzion/224456637627
[KB증권 리서치 RA 채용]
KB증권에서 RA릉 채용합니다. 제 RA도 뽑습니다~ 주변에 많은 홍보 부탁드립니다^^
■ 채용 직무 : 리서치본부 연구원(RA)
■ 모집 분야 : 기업분석 | 자산배분 | 주식전략 | 멀티에셋 | 글로벌기업/ETF분석
■ 전형 일정
서류 접수 : 2026. 10. 21(수) ~ 2026. 11. 8(일)
1차 면접전형 : 2026. 11. 17(화) 예정
2차 면접전형 : 2026. 11. 24(화) ~ 11. 26(목) 중 예정
- 지원 사이트: http://kbsec.career.greetinghr.com/o/241147
https://www.kofia.or.kr/brd/m_96/view.do?seq=42788&srchFr=&srchTo=&srchWord=&srchTp=&multi_itm_seq…
Showing the 12 most recent of 70 posts we hold for @egzion. 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
@egzion 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
7 October 2026
Most recent edit
7 October 2026
Posts recorded as deleted after publishing
We recorded 1 post on @egzion as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
26 August 2026
Most recent seen missing
26 August 2026
Median time before seen missing
15 hours
Seen missing in the last 30 days
0
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 2 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.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“이그전 (이은택의 그림 전략)” (@egzion), 22,870 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/egzion.
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.
