2015년부터 시장 분석과 정보를 제공해온 세종기업데이터는 유사투자자문업자로서 투자 판단에 참고할 수 있는 다양한 데이터를 제공합니다. 본 서비스는 투자 권유가 아닌 정보 제공 목적이며, 모든 투자 결정과 결과에 대한 책임은 이용자 본인에게 있습니다. 앞으로도 신뢰할 수 있는 정보를 제공하기 위해 노력하겠습니다.
Created
19 June 2018 — measured — cross-checked against a third-party dataset (ext.tg_channel)
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 10 September 2026 and assigned it the closest of 31 fixed categories, at 90% 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.
Growth
35 measurements spanning 69 days, net -167. 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 23,258–23,475 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
13 Oct 2026, 23:16
23,283
-13
10 Oct 2026, 21:35
23,296
+8
6 Oct 2026, 14:37
23,288
+2
1 Oct 2026, 13:00
23,286
-48
18 Sept 2026, 11:58
23,334
-2
16 Sept 2026, 03:58
23,336
-2
14 Sept 2026, 09:37
23,338
-11
12 Sept 2026, 18:21
23,349
-14
10 Sept 2026, 20:38
23,363
-5
7 Sept 2026, 16:35
23,368
+1
4 Sept 2026, 17:40
23,367
-9
2 Sept 2026, 00:15
23,376
-11
31 Aug 2026, 22:27
23,387
-2
30 Aug 2026, 23:28
23,389
-8
29 Aug 2026, 22:24
23,397
-2
28 Aug 2026, 22:07
23,399
-8
28 Aug 2026, 00:08
23,407
-5
26 Aug 2026, 22:13
23,412
-3
25 Aug 2026, 20:36
23,415
-13
24 Aug 2026, 22:44
23,428
first reading
Engagement
180 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 91 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
16.8%
avg views ÷ 23,283 subscribers
Avg views / post
3,920
68 posts measured
Reaction rate
0.129%
reactions ÷ views · ER floor
Posts in window
69
of 180 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 64 of 68 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 October 2026
Posts held
180 (5 August 2026 – 14 October 2026)
Views total
266,520
Reactions total
322
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
14 Oct 2026, 08:26 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
≈5,940
Videos
≈32
Links
≈5,680
Lifetime counters from Telegram’s own channel header, read 14 October 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
712 reactions across 122 posts, in 1 kind.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
712
100.0%
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 131 of the 180 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 712 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 180 most recent posts we hold, published 5 August 2026 to 14 October 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.
#삼성전자
① 시가총액·이격도: 열기가 빠지는 중
- 시총 1,356조로, 250거래일 고점 대비 -36.0%. YTD는 여전히 +78.3%.
- 60일 이격도는 -9.7%로, 상반기 +40~60%대 과열 구간에서 내려와 평균 아래로 진입.
- 월평균 시총 YoY도 6월 약 +480% 정점 이후 약 +170%까지 둔화. 주가 모멘텀이 정점을 지난 흐름.
② PBR 밴드: 장부가치 기준으로는 여전히 높은 위치
- 현재 PBR 2.34배. 최근 3년 범위 0.81~2.65배, 중앙값 1.22배 대비 상단.
- 시총은 PBR 90% 밴드를 넘었다가 다시 그 아래로 내려온 상태.
- 다만 자본총계가 빠르게 늘면서 밴드 자체가 계단식으로 올라가는 중.
③ 50주 밴드: 중기 추세는 아직 유지
- 50주 이동평균 대비 +6.8%, 밴드 내 55% …
50주 밴드 하단 이탈 기업
전일 주가 하락으로, 16개였던 후보군이 19개로 늘어났습니다.
행동경제학과 투자 심리에서 자주 언급되는 개념 중 하나가 바로 평균회귀(Mean Reversion)입니다.
주가가 단기간에 과도하게 하락했다면, 일정 시간이 지난 뒤 평균적인 수준으로 되돌아갈 가능성이 있다는 것입니다.
물론 실제 투자에서는 투자 기간과 시장 환경에 따라 결과가 달라질 수 있습니다.
중요한 것은 과매도 구간에 진입했다는 사실 자체보다, 무엇 때문에 주가가 하락했는지 파악하는 것입니다.
단순히 수급과 투자 심리의 영향으로 주가가 과도하게 밀린 것인지, 아니면 실적 둔화나 수주 감소 등 펀더멘털에 문제가 발생한 것인지 구분할 필요가 있습니다.
주가가 많이 빠진 기업을 찾는 것보다, 빠질 이유가 충분하지 않은 기업을 찾는 것이 …
상폐 위기에 있는 코스닥 시총 400억 미만 480곳, 절반이 적자
코스닥은 상장 유지 시총 기준이 내년 1월 기존 200억에서 300억으로 올라갑니다.
시총 400억 미만으로 끊어서 리스트를 뽑았는데 그중 절반은 적자입니다.
이미 시총 200억 미만 97곳은 관리 종목 사정권입니다.
보유 종목이 이 480곳에 있는지, 흑자인지 적자인지 체크해보세요.
양이 많아 엑셀 파일로 첨부해두었습니다!
https://sejongdata.com/insights/79
상폐 기준이 또 올라간다, 코스피 시총 600억 미만 139곳 리스트
7월부터 코스피 상장유지 시총 기준이 300억으로 올랐고 내년 1월 500억으로 또 오릅니다.
10월 8일 종가 기준 시총 600억 미만 139곳 전수로 뽑았습니다.
내년 1월 500억 기준이 적용되면, 지금 500억대 종목도 그대로 사정권이기 때문에 시총 600억대 미만으로 필터를 끊었습니다.
300억 미만 43곳은 이미 사정권인데, 내 종목이 여기 있나, 흑자인가부터 봐야 합니다.
엑셀 파일로 첨부해두었습니다!
https://sejongdata.com/insights/78
시그널③ 밴드하단 이탈 후보군
50주 시가총액 밴드 하단을 이탈한 기업들입니다.
주가가 많이 빠진데는 이유가 있지만, 이유를 분석하고 나면 새로운 기회로 작용할 수 있습니다.
세종닷컴 사이트 내에서 정량적 분석(이익, 밸류에이션 등)까지 한번에 체크해보세요!
https://sejongdata.com/signals/band
[세종기업데이터 업데이트] 기업 시그널 페이지 업그레이드
좋은 기업을 찾는 방법은 하나가 아닙니다.
📍실적은 좋아지고 있지만 주가는 부진한 기업,
📍적자에서 벗어나 이익이 빠르게 개선되는 기업,
📍장기간의 주가 흐름에서 중요한 하단 밴드를 이탈한 기업.
각각 다른 관점에서 기업을 탐색할 수 있도록 기업 시그널 페이지에 2개의 분석 조건을 추가했습니다.
기존의 「YoY 개선」에 더해 다음 두 가지 시그널을 새롭게 제공합니다.
① 이익 모멘텀
최근 4개 분기 영업이익 흑자 여부와 3개 분기 연속 이익 개선 흐름을 확인하면서, 시가총액이 최근 3개월간 부진한 기업을 찾아봅니다.
② 밴드 하단 이탈
50주 시가총액 밴드 하단을 이탈한 기업을 포착합니다. 일시적인 이탈인지, 하락 흐름이 지속되고 있는지 추가로 확인할 수 있습니다.
이제 실…
이번에 현대로템이 실적발표를 예년 대비 빨리 하네요.
보통 이런 경우에는 실적에 대한 자신감이 뿜뿜 할 때 실적발표를 미리 땡겨서 하는 경우가 많았는데, 현대로템이 이번에 어떤 실적을 발표할지 궁금하네요.
지금까지 현대로템의 영업이익과 시가총액은 대체로 유사한 방향성을 보여줬는데, 이번 3분기 실적이 좋다면, 시가총액 방향성도 확 바뀔 가능성이 있을지도 주요 체크 포인트가 아닐까 싶습니다!
공시 기준 실적발표일은 2026년 10월 19일(월) 오후 2:10분입니다.
https://sejongdata.com/company/064350
# 3Q26 실적 스크리닝_2026.10.08
- ‘26년 10월 8일(목) 종가 기준입니다.
- 삼성전자, LG전자, LG에너지솔루션이 '26년 3분기 잠정실적을 발표했고, 해당 내용이 반영되었습니다.
- 이번 한주도 정말 고생 많으셨습니다.
- 자세한 내용은 첨부파일을 확인해 주시면 감사하겠습니다.
- 즐거운 연휴 되시길 바라겠습니다! 감사합니다.
https://sejongdata.com/insights/40
❤10
Showing the 12 most recent of 180 posts we hold for @sejongdata2013. 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
@sejongdata2013 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
8 October 2026
Most recent edit
8 October 2026
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 1 registered channel — 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 13 October 2026 — this
entry's latest reading, not the date you are reading this.
“세종기업데이터” (@sejongdata2013), 23,283 subscribers as measured 13 October 2026. Telegram Register, tgregister.com/channel/sejongdata2013.
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.