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 69% 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 2 other registered channels. 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 (6 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. 8 of the 19 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 20 comparable posts for this entry, running 3 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 3, the earliest publisher we hold is @yuantaresearch. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 7 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 2 other registered channels, 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.
5 measurements spanning 7 days, net -13. 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 9,931–9,948 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 17:46
9,933
-5
11 Aug 2026, 01:21
9,938
-6
8 Aug 2026, 00:46
9,944
-2
7 Aug 2026, 09:30
9,946
no change
7 Aug 2026, 09:28
9,946
first reading
Engagement
66 posts held, back to 3 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 18 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
3.35%
avg views ÷ 9,933 subscribers
Avg views / post
333
66 posts measured
Reaction rate
0.331%
reactions ÷ views · ER floor
Posts in window
66
of 66 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 66 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 14 August 2026
Posts held
66 (3 August 2026 – 14 August 2026)
Views total
21,964
Reactions total
20
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
15 Aug 2026, 19:52 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
≈1,920
Links
≈14,200
Lifetime counters from Telegram’s own channel header, read 15 August 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
20 reactions across 17 posts, in 2 distinct kinds. The most used accounts for 95.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
19
95.0%
👍
1
5.00%
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 17 of the 66 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 20reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 66 most recent posts we hold, published 3 August 2026 to 14 August 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.
[국내주식 마감시황] KOSPI·KOSDAQ 월화수목금 모두 상승 (8/14)
🧿유안타 [시황 이재원 (02-3770-5719)]
KOSPI 6,977pt(+2.4%), KOSDAQ 864pt (+0.4%)
① 해외 시황 : 소비자물가에 이어 생산자물가 마저 예상치 하회
-간밤 미국 주식시장 상승(나스닥 +0.8%, S&P500 +0.7%, 필라델피아 반도체지수 +0.5%). 7월 생산자물가가 예상치 하회하고 국제유가가 하락하며 금리인상 우려 완화. 시장금리 하락하며 기술주 중심 상승. 샌디스크, 인베스터 데이에서 잉여현금흐름의 100%를 주주환원 하겠다는 방침 제시하며 13.7% 상승 및 스토리지 동반 상승 견인
② 수급 : KOSPI 외국인 자금 대량 유입, KOSDAQ도 개인 자금 연속 유입 = 양대 지수 상승
-KRX KOS…
유안타 리서치센터
데일리 섹터 News & Comments(08/14)_3
■ 통신/지주 이승웅(02-3770-5597)
▶글로벌 통신 기업 주가
- 상승: Verizon +2.6%, AT&T +1.4%, Deutsche Telekom +1.0%
▶News & Data
독파모에 참여한 4개 모델 가운데, '아티피셜 어낼러시스'의 최신평가에서 SKT 3위
- link: https://tinyurl.com/bdkj8reh
과기정통부, 주파수 재할당 대가 산정체계 손본다
- link: https://tinyurl.com/mwvssybz
SK에코플랜트, AI DC 사업단 신설, AI 인프라 사업 강화
- link: https://tinyurl.com/5n6cdkw9
LG 2Q 영업익 5,330억원, 전자계열 선전에 93% 급증, 매출도 …
🧿유안타 [Economist 김호정(02-3770-3630)]
[8/14 일본 금융시장 15문15답: 국채금리·엔화약세·미일공조, 핵심 쟁점에 답하다]
최근 일본 금융시장에서 장기 JGB 금리 상승과 엔화 약세가 동시에 나타나는 이례적 조합이 이어지고 있습니다.
이번 보고서에서는 이를 둘러싼 핵심 쟁점 15가지를 15문 15답 형식으로 추려, BOJ 정상화·JGB 수급·엔화 약세·미일 공조 개입의 의미를 점검했습니다.
■ 핵심 요약
1. 최근 JGB 금리 상승은 단순한 재정위기성 국채 매도가 아니라, BOJ 정상화와 가격정상화 기능 회복, 기간 프리미엄 상승이 동시에 반영된 결과로 판단.
2. JGB 투자 매력이 높아지고 경상흑자가 확대됐음에도 엔화가 강세로 전환되지 않는 이유는 금리 수준보다 실제 환전·환헤지 구조에 있음.
3. 미·일…
수요를 얼마나 질서 있게 대체할 수 있는지임.
• 단기·중기 구간은 금리 정상화와 함께 투자 매력이 개선되고 있지만, 초장기 구간은 생보사·연기금 등 장기 투자자의 수요 회복이 아직 충분하지 않음.
• 따라서 일본 금리 상승의 핵심은 “국채를 못 사는 위기”라기보다, BOJ 중심 시장에서 민간 중심 시장으로 넘어가는 과정에서 발생하는 가격 재조정으로 해석.
■ 3) 왜 JGB 금리가 올라도 엔화는 강하지 않은가
• JGB 투자 매력이 높아지고 경상수지 흑자가 확대됐음에도 엔화가 강세로 전환되지 않는 이유는 금리의 절대 수준보다 실제 자금의 환전·환헤지 구조에 있음.
• 일본의 단기 실질금리는 여전히 마이너스이고, 가계와 기관이 과거 축적한 대규모 해외자산도 빠르게 환류되지 않고 있음.
• 경상흑자 역시 상품수출보다 해외자산에서 발생하는 본원…
주주환원 재원과 연계하고 있는 만큼 실적 개선은 배당과 자사주 매입 여력 확대로 이어질 가능성이 높습니다. 대규모 설비투자와 적정 현금 수준을 감안하면 구체적인 방식과 규모는 불확실하지만, 예상보다 강한 환원책이 발표될 경우 최근 조정 받은 대형주의 추가 반등을 이끌 촉매로 작용할 수 있습니다.
-결국 KOSPI 상승 추세 연장을 위해서는 외국인의 추세적 순매수 복귀가 중요합니다. 개인은 최근 고객예탁금 감소와 신용융자 재증가로 상반기와 같은 매수 주도력을 기대하기 어려운 가운데, 강한 상승일에는 외국인 순매수·개인 순매도, 하락일에는 반대 흐름이 반복되고 있습니다. 물가 안정에 따른 금리 부담 완화와 최근 VKOSPI 하락은 외국인 복귀에 우호적인 환경입니다. 기존 ‘KOSPI 대형주 : KOSDAQ’ 전략에서는 KOSDAQ 비중을 축소하…
[주간:知] 코스닥에 잠깐 돌렸던 시선, 코스피로 복귀할 때 (8월 3주)
🧿유안타 [시황 이재원 (02-3770-5719)]
■[Summary]
-주간(8/7~8/13) KOSPI, KOSDAQ은 각각 8.2%, 7.5% 상승했습니다. 비농가고용 부진에 이어 소비자물가는 예상치에 부합하고 생산자물가는 예상을 하회하면서 금리 불확실성이 완화됐습니다. 여기에 AI 인프라 기업들의 호실적까지 더해지며 외국인은 KOSPI에서 주간 5.1조원을 순매수했고, KOSPI는 120일 이동평균선을 재차 회복했습니다.
-8월 초 KOSDAQ 비중 확대 전략은 개인 수급 복귀와 대형주 쏠림 완화에 힘입어 유효했습니다. 다만 2024년 이후 국내 모멘텀 스타일은 KOSDAQ보다 KOSPI와 높은 동조화를 보이고 있습니다. 최근에도 KOSPI 이익추정치는 …
🧿 유안타 AI 미국 주식시장 마감시황(8/14)
[퀀트 신현용 (02-3770-3634)]
[시황 이재원 (02-3770-5719)]
━━━━━━━━━━━━━━━
🤖 AI 한줄평
도매물가 둔화가 금리 동결·인하 기대에 불을 지피며 S&P 500이 사상 최고가를 새로 썼고, 실적을 웃돌고도 마진 우려로 급락한 시스코와 장기 실적 목표에 폭등한 메모리주가 극명하게 갈린 하루였습니다.
━━━━━━━━━━━━━━━
🔥 [1] 오늘의 핵심 이슈 5가지
1️⃣ S&P 500 사상 최고가 마감
• 도매물가 둔화로 금리 인하 기대가 살아나며 S&P 500 +0.65%로 종가 기준 사상 최고치 경신.
• 나스닥 +0.81%, 다우존스 +0.13%, 러셀2000 +0.24% 동반 상승 마감.
2️⃣ 도매물가 둔화에 연준 정책 기대 이동
…
❤1
Showing the 12 most recent of 66 posts we hold for @tRadarnewsdesk. 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.
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
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“유안타 News 라운지” (@tRadarnewsdesk), 9,933 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/tRadarnewsdesk.
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.