Telegram RegisterThe public register of Telegram
Telegram profile photo for 하나증권 미국주식 강재구

Channel

하나증권 미국주식 강재구

@hana_us_stock

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

11,128subscribers

+1,187 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-1001712864659
TypeChannel
Username@hana_us_stock
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 live19 September 2026
Measurements held30
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/hana_us_stock

Topic

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 49% 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. They sit inside a group of 5 channels that share the same post bodies with each other. 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)
Posted firstThenOverlapGap
@hana_us_stock/10220 · this entry5 Aug 2026, 06:39 UTC@globaletfi/209775 Aug 2026, 07:49 UTC1.0071 minutes
@globaletfi/209765 Aug 2026, 07:49 UTC@hana_us_stock/10221 · this entry5 Aug 2026, 08:01 UTC1.0011 minutes
@hana_us_stock/10226 · this entry5 Aug 2026, 20:34 UTC@globaletfi/209905 Aug 2026, 22:05 UTC1.001.5 hours
@hana_us_stock/10234 · this entry5 Aug 2026, 23:21 UTC@globaletfi/209965 Aug 2026, 23:22 UTC1.002 minutes
@hana_us_stock/10220 · this entry5 Aug 2026, 06:39 UTC@hanaglobalbottomup/88045 Aug 2026, 06:39 UTC1.00under a minute
@hanaglobalbottomup/88247 Aug 2026, 06:24 UTC@hana_us_stock/10246 · this entry7 Aug 2026, 06:27 UTC1.003 minutes
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@globaletfi6 (6/6 hand-verifiable sample passed)1.0049 minutesthis entry (51)
@hanaglobalbottomup5 (5/5 hand-verifiable sample passed)1.00under a minute@hanaglobalbottomup (41)

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. 1 of the 1 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 25 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 5, the earliest publisher we hold is @hanaglobalbottomup. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_mutual · clone_source, 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 4 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.

Growth

9,94111,12810,534.56 August 2026 — 9,941 subscribers6 August 2026 — 9,941 subscribers9 August 2026 — 9,957 subscribers12 August 2026 — 10,011 subscribers13 August 2026 — 10,029 subscribers14 August 2026 — 10,035 subscribers16 August 2026 — 10,051 subscribers17 August 2026 — 10,055 subscribers18 August 2026 — 10,054 subscribers19 August 2026 — 10,066 subscribers20 August 2026 — 10,070 subscribers22 August 2026 — 10,112 subscribers23 August 2026 — 10,142 subscribers25 August 2026 — 10,209 subscribers26 August 2026 — 10,252 subscribers27 August 2026 — 10,302 subscribers28 August 2026 — 10,327 subscribers29 August 2026 — 10,340 subscribers30 August 2026 — 10,341 subscribers31 August 2026 — 10,348 subscribers1 September 2026 — 10,376 subscribers2 September 2026 — 10,539 subscribers3 September 2026 — 10,721 subscribers5 September 2026 — 10,824 subscribers9 September 2026 — 10,896 subscribers11 September 2026 — 10,936 subscribers13 September 2026 — 11,058 subscribers15 September 2026 — 11,089 subscribers17 September 2026 — 11,113 subscribers19 September 2026 — 11,128 subscribers6 August 202619 September 2026
30 measurements spanning 44 days, net +1,187. 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 9,763–11,306 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)SubscribersChange
19 Sept 2026, 13:0111,128+15
17 Sept 2026, 02:1911,113+24
15 Sept 2026, 00:3811,089+31
13 Sept 2026, 12:5811,058+122
11 Sept 2026, 18:1710,936+40
9 Sept 2026, 06:2210,896+72
5 Sept 2026, 23:0110,824+103
3 Sept 2026, 17:2010,721+182
2 Sept 2026, 08:4810,539+163
1 Sept 2026, 08:5710,376+28
31 Aug 2026, 05:3410,348+7
30 Aug 2026, 05:4410,341+1
29 Aug 2026, 02:5310,340+13
28 Aug 2026, 04:1210,327+25
27 Aug 2026, 05:2510,302+50
26 Aug 2026, 02:0610,252+43
25 Aug 2026, 00:1810,209+67
23 Aug 2026, 15:0310,142+30
22 Aug 2026, 04:1510,112+42
20 Aug 2026, 21:4810,070first reading

Engagement

178 posts held, back to 3 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 38 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
19.4%
avg views ÷ 11,128 subscribers
Avg views / post
2,160
39 posts measured
Reaction rate
0.242%
reactions ÷ views · ER floor
Posts in window
39
of 178 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 34 of 39 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 29 August 2026
Posts held178 (3 August 202629 August 2026)
Views total84,205
Reactions total189
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 15:14 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

843 reactions across 147 posts, in 18 distinct kinds. The most used accounts for 64.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
54264.3%
👍19423.0%
🤣273.20%
😁141.66%
👏111.30%
🤯101.19%
😭80.949%
🔥70.83%
👎50.593%
🤬50.593%
😱40.474%
🤔40.474%
🏆30.356%
💯30.356%
🙏20.237%
🥰20.237%
🍓10.119%
🖕10.119%

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 162 of the 178 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 943 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 178 most recent posts we hold, published 3 August 2026 to 29 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.

Recent posts

29 Aug 2026, 09:17 UTC910 views12 reactionsread 29 August 2026

워시가 늘 연준이 방향성을 주는 걸 선호하지 않는다고 했던 기존의 기조를 보여주는 게 아닐지

12

29 Aug 2026, 09:11 UTC943 views17 reactionsread 29 August 2026
Photo

어제 캐빈워시 연설문입니다 전체 내용은 워낙 뉴스에서도 많이 돌아다녔으니 많이 보셨을 거 같구요 연설 전반이 매파적으로 해석될 부분도 있지만 연설 앞에 등산과 농담에 대한 부분도 좀 생각해볼 필요가 있는데요.. 제 음모론일 수 있지만 캐빈 워시도 등산을 좋아하는 건가 싶어서 반갑긴 했는데 워시가 던 컨 전 Fed 부의장과 밴 버냉키 전 연준의장과의 등산 경험 얘길 꺼냅니다 등산에 비유한 게 Hike(산행 또는 인상)라는 말을 써서 그런게 아닌가 싶긴 한데 던 컨과의 등산에 대해선 '살아남았다(I Survived)'라고 하면서 '아 빡셌어..'라고 하면서 공격적인 금리인상을 비유한 듯하고 버냉키와의 등산에 대해선 '훨씬 더 느긋한 페이스였다'라고하면서 완만한 금리인상 방향을 시사한 듯 하네요 그러면서 현재는 던 컨일지 아니면 밴 버냉키와의 등산

17

29 Aug 2026, 08:35 UTC819 views1 reactionsread 29 August 2026

[Meta, 180억달러 아동 안전 합의… 연령확인 AI 학습 위한 아동 데이터 활용에 법적 보호] ⁠ *180억달러 합의 -Meta가 미국 29개주 Attorney General과 최대 180억달러 규모의 아동 안전 관련 합의 체결 -합의에는 아동 보호 조치 강화와 함께 Meta가 아동 데이터를 보유·활용하는 일부 행위에 대해 주정부가 소송을 제기하지 않기로 하는 조항 포함 -해당 면책은 Meta의 Age-assurance Model 학습과 테스트 목적에 한정 -TechCrunch는 아동 안전을 다루는 사건에서 아동 데이터 활용에 법적 보호를 제공했다는 점이 이례적이라고 평가 ⁠ *Age-assurance Model -Meta는 합의 발효일로부터 1년 이내 13세 미만 사용자를 탐지하는 Model을 개발·학습하고 테스트를 시작해야 함 -합의

1

28 Aug 2026, 07:36 UTC≈2,460 views5 reactionsread 29 August 2026

[AI 데이터센터 경쟁 GW 단위로 확대… AWS·Microsoft·Google이 Hyperscaler 상위권] ⁠ *Hyperscale Data Center -AI 수요 급증과 대규모 투자로 구축 규모가 기존 MW에서 GW 단위로 확대 -Cloud Provider와 AI 기업들이 전력 확보까지 수년이 필요한 대규모 Campus에 자본 투입 -Grid Connection·Water·Cooling·Planning Consent·Engineer 확보 등이 Data Center 구축의 주요 제약 -이러한 병목을 빠르게 해결하는 기업들이 Chip Supplier부터 Construction Partner까지 Data Center 산업 전반의 방향을 결정하고 있다고 평가 ⁠ *1위 AWS -AWS가 전체 Data Center Capacity 기준 글로벌

4👍1

28 Aug 2026, 05:34 UTC≈1,160 views5 reactionsread 29 August 2026

기사를 쓴 분이 잘 모르고 한국에는 2018년부터 로봇세가 있다고 쓴 듯 하네요... 2017년 자동화 설비에 대한 세액공제를 축소하면서 외신이 로봇에 대한 혜택 축소 = 사실상 로봇세 이렇게 보도한 거 같은데... 오히려 반대인게 2026년 세제 개편안엔 AI 로봇부품은 반도체, 이차전지 등과 같이 국내생산세액공제 신설 대상에 포함돼 있죠... ------------------------------------------------------------- [빌 게이츠, Robot·AI Token 과세 제안… 인간 노동 대체 속도 늦춰야] ⁠ *Robot·AI Token 과세 제안 -마이크로소프트 공동창업자 Bill Gates가 Robot과 AI Token에 세금을 부과하는 방안 제안 -AI와 Robotics가 인간 노동을 빠르게 대체하는

3🖕1🤔1

28 Aug 2026, 05:34 UTC≈3,430 views2 reactionsread 29 August 2026

◈하나증권 해외주식분석◈ 선진국 기업분석 강재구(T.02-3771-3386) *텔레그램 채널: https://t.me/hana_us_stock ★ Marvell Technology (MRVL.US): 10월 도파민이 필요하다 ▶ 자료: https://buly.kr/EI6NHEX ▶ 단기 주가 약세 가능성. 10월 투자자의 날 행사가 중요 - 주가의 단기 약세 나타날 수 있지만 마벨 테크놀로지(이하 마벨)에 대한 중장기적인 긍정적 관점은 유지한다. 실적 발표 후 마벨의 시간외 주가는 급락했다. 마벨은 실적 발표하기 전 구글과 TPU 생태계 관련 협력을 확대했다. 마벨의 주가는 TPU 계약 공시 이후 11.8% 상승했다. 같은 기간 SOXX ETF가 1.1% 하락한 점 감안하면 구글과의 계약 덕분에 실적 기대감이 주가에 먼저 반영됐을 여

1👍1

27 Aug 2026, 22:39 UTC≈1,020 views2 reactionsread 29 August 2026
Forwarded from @hanaglobalbottomup

[하나 글로벌 기업분석 데일리 뉴스] 8/28 하나증권 김재임/송종원 Nvidia 시가총액 4천억 달러 증가 -AI 수요가 계속 강할 것이란 매출 전망에 투자 심리 개선됐음 -호실적 발표 뒤 목요일 주가 상승했음 -AI 산업 전반에 대한 시장 신뢰도 높였음 https://da.gd/YvCmAY Nvidia의 Hugging Face 129억 달러 인수 합의 -오픈소스 AI 플랫폼을 인수 대상으로 삼았음 -AI 생태계 내 사업 영역을 확대하려는 행보임 -Hugging Face 측은 인수 보도에 논평 거부했음 https://da.gd/WdgxR Nvidia의 중국 오픈 AI 모델 지원 강화 -DeepSeek와 Qwen에 맞춰 하드웨어 최적화하고 있음 -미국 정부가 중국산 모델을 제한할 가능성 경고했음 -관련 규제가 사업에 타격을 줄 수 있다고

1👍1

27 Aug 2026, 21:37 UTC≈1,310 viewsread 29 August 2026
Photo

선거 앞두고 마이크론의 투자를 강조하는 트럼프

27 Aug 2026, 20:31 UTC≈1,630 views3 reactionsread 29 August 2026
Photo

[Marvell FY2Q27 실적: AI 수주 강세 지속, FY27·FY28 매출 전망 상향] * 2Q FY27 실적 - 매출 $2.739B, YoY +37%, FactSet $2.72B 상회 - Non-GAAP EPS $0.94, FactSet $0.93 상회 - GAAP EPS $0.33 - GAAP 매출총이익률 53.1% - Non-GAAP 매출총이익률 58.9%, StreetAccount 58.8%, 전년동기 59.4% - Non-GAAP 영업이익률 36.6%, StreetAccount 36.7%, 전년동기 34.8% - 영업현금흐름 $605.5M, FactSet $749.5M 하회 * 사업부문 - Data Center 매출 $2.17B, StreetAccount $2.16B 상회 - Data Center 매출 YoY +46% -

3

27 Aug 2026, 14:09 UTC≈3,160 views8 reactionsread 29 August 2026
Photo

M7 중에선 호실적 발표한 엔비디아강세

6👍2

Showing the 12 most recent of 178 posts we hold for @hana_us_stock. 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.

[하나 Global ETF] 박승진
@globaletfi · 20,222
36 posts
하나증권 리서치
@HanaResearch · 24,968
11 posts
[하나증권 해외주식분석]
@hanaglobalbottomup · 10,924
8 posts
메모장
@idea_memo · 8,853
6 posts
급등일보 미국주식🇺🇸 속보·매크로·리서치
@FastStockNewsUSA · 40,651
3 posts
블루버드_장기우상향 투자공부방
@longtermgrowth · 386
2 posts
에버그린 Evergreen 정보 공유방
@talkevergreen · 13,434
2 posts
타점 읽어주는 여자(타자)
@tazastock · 40,320
2 posts
오를주식 - 뉴스/경제/주식
@GoUpstock · 20,978
1 post
텐렙
@Ten_level · 17,133
1 post
Yeouido Lab_여의도 톺아보기
@Yeouido_Lab · 43,309
1 post
엄브렐라리서치 Anakin의 투자노트
@anakinvest · 9,559
1 post
@아무자료 아무노래(2026년, 계급사회 가속화 3.0)
@anysong_Technon · 4,984
1 post
기업지평 넓히기
@broadeningones · 3,302
1 post
카이에 de market
@cahier_de_market · 22,483
1 post
베리나 망하면 한강 감
@cexwithkotether · 1,281
1 post
상장기업 수사대 ☎️
@cyber_rangers · 16,973
1 post
조금 느려도 괜찮아
@hyunhee82 · 2
1 post
인상주의 투자 인생 업그레이드노트
@insangnism · 11,308
1 post
investor1992
@investor1992rok · 1,197
1 post
잠실개미&10X’s N.E.R.D.S
@jake8lee · 17,277
1 post
지식 책꽂이 (이대호 기자)
@knowledge_to_wealth · 14,145
1 post
레드버드 기업분석
@redbirdstock · 9,963
1 post
영리한 동물원
@stockinvcowcow · 14,059
1 post
트리플 아이 - Insight Information Indepth
@triple_stock · 12,879
1 post
🗽엄브렐라(Umbrella Research) 리서치+ 네프콘 옆집부자형 since 2020
@umbrellaresearch · 12,852
1 post
LSKP CFO의 개인 공간❤️
@valuecore · 1,090
1 post
야자반 - Y.Z. stock
@yaza_stock · 13,107
1 post

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 5 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.

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.

Market News Feed
@marketfeed · 38,658
Telegram ranks this channel #71 of 84 here — alongside 83 others — read 31 August 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list 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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“하나증권 미국주식 강재구” (@hana_us_stock), 11,128 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/hana_us_stock.

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.