Channel
@Macrojunglemicrolens
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
22,959subscribers
+112 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001768167577 |
|---|---|
| Type | Channel |
| Username | @Macrojunglemicrolens |
| Description | 본 채널은 시장에 대한 즉각적인 의견이나 전망 제시보다는, 공개된 외국계 리서치를 기반으로 구조·전제·변화 포인트를 기록하는 데 목적을 두고 있습니다. 본 채널의 게시물들은 작성자 본인에 의한 매수 및 매도 추천의사가 아니며, 게시물에 표기된 내용상 시간 및 데이터가 현재와 괴리가 있을 수 있습니다. 또한, 투자자 의사결정과 투자결과에 대한 법적 증빙으로 사용될 수 없음을 밝힙니다. |
| Created | 18 March 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 8 November 2026 |
| Measurements held | 63 |
| Confirmed unchanged | 1 time, most recently 8 November 2026 |
| On Telegram | t.me/Macrojunglemicrolens |
Technology — 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 77% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Nov 2026, 13:50 | 22,959 | -9 |
| 7 Nov 2026, 05:40 | 22,968 | -9 |
| 6 Nov 2026, 06:35 | 22,977 | -29 |
| 5 Nov 2026, 04:48 | 23,006 | -11 |
| 4 Nov 2026, 03:45 | 23,017 | -26 |
| 2 Nov 2026, 23:59 | 23,043 | -14 |
| 1 Nov 2026, 20:46 | 23,057 | -2 |
| 31 Oct 2026, 16:45 | 23,059 | -11 |
| 30 Oct 2026, 19:17 | 23,070 | -8 |
| 29 Oct 2026, 18:57 | 23,078 | -9 |
| 28 Oct 2026, 20:09 | 23,087 | -12 |
| 27 Oct 2026, 22:18 | 23,099 | -17 |
| 26 Oct 2026, 18:47 | 23,116 | -14 |
| 25 Oct 2026, 15:21 | 23,130 | -4 |
| 24 Oct 2026, 16:05 | 23,134 | -10 |
| 23 Oct 2026, 12:41 | 23,144 | -19 |
| 22 Oct 2026, 11:47 | 23,163 | -20 |
| 21 Oct 2026, 08:20 | 23,183 | -12 |
| 20 Oct 2026, 05:11 | 23,195 | -13 |
| 19 Oct 2026, 02:18 | 23,208 | first reading |
114 posts held, back to 29 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 114 posts for this entry, the most recent from 6 October 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 8 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.
10,874 reactions across 114 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 10,874 | 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 114 of the 114 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 10,874 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 114 most recent posts we hold, published 29 July 2026 to 6 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.
요즘 글을 자주 쓰지 않는데요. AI로 스스로만의 특별한 작업들을 하고있습니다. 펀드산업 현직에서도 PM들이 각자 자신만의 대시보드를 만들거나 어플리케이션을 자가제작 하는 모습들이 보입니다. 그러나 지켜보면 중론은 모두가 비슷한 대시보드로 종착되는 모습이 강하다 느낍니다. 개인적으로는 헤지펀드 PM으로서 마켓 써머리 이상의 기능을 찾아야한다고 생각합니다. 그런만큼, 포트폴리오 전략과 컨트롤 측면과 스크리닝 엔진에 대한 고민이 많아집니다. 어느해 시점부터는 대중들의 정보의 시간격차와 접근차별성은 극히 줄어들었고, AI를 통한 툴 개발로 얼마나 내 포트폴리오에 도움될 수 있는 알파캡쳐를 할 수 있는가가 더 중요한 것 같습니다. 모두가 생각보다 창의로워서 모두가 생각보다 같아질 리스크를 제대로 측정할 수 있을까요. 또한, 많은 부분들을 의…
❤351
다음분기의 경우, 대부분의 사이버보안 기업들의 어닝콜 톤 모멘텀과 일치하는 효익을 더 자세히 증명할 시기입니다. 실제적인 큰 변환점으로 뽑는 사건인 Anthropic의 Mythos 사태, Open AI의 Hugging face 사태가 일어난 7월, 8월 이후의 분기입니다. 보안의 전방 프로세스(디텍션)와 후방 프로세스(리버커리)까지 모든 프로세스의 사이버보안 기업들이 해당 시점을 업계 특이점으로 강조하고 있는 상황이며, 실제적으로 AI infra 생태계 조성자인 NVDA와 미국 정부까지 빠르게 움직이고 있고 화두로 떠올랐던 시기입니다. 다만, 개인적으로 보고있는 특이점은 이번 Open AI의 Hugging face 사건인데, 이 경우 기존 보안 프로세스로 작동했어야할 보안구조를 너머 이미 깊숙히 침투하고 미국 프런티어랩 폐쇄형 모델로는 …
❤113
$CRWD $NVDA - CROWDSTRIKE, AWS, AND NVIDIA EXPAND GLOBAL CYBERSECURITY STARTUP ACCELERATOR, DEFINING THE NEXT GENERATION OF INNOVATION FOR THE AGENTIC ERA
❤42
https://x.com/JensenHuang/status/2104499465055023424
❤34
위 상황을 감안할때, 할인과 변동성의 지속을 택할지, 모멘텀의 발화에 구축을 시도할지, 투자자들이 고민할 차례.
❤124
표기된 에셋에는 그동안 유지되어온 한방향의 수급들을 리버설시키는 스레숄드는 9월에 몰려있다는 것이 주요 컨센서스. 추가적인 생각을 해야할 지점은, 현 시점에서 모여온 방향성들이 이어나갈 PnL자체의 업사이드와 다운사이드 스큐가 중요한 구간. 어제 월러 발언으로 FOMC 구성원들의 의견은 정확히 반반에 가까워졌기때문에, 남은 재량은 케빈 워시 의장 자체에게 있는 상황. 그리고 시작될 바이백 실제 실효와 시장 할인율에 영향을 주는 통화정책 이벤트는 시간가치를 보유하고 있는 이벤트 팩터. 실효일자가 줄어드는 구간에는 가격델타가 높지않은데, 해당 방향성에 잡힌 PnL이 맥스라면 포지셔닝의 지속성은 변화에 임박할 수도 있음. 컨센서스의 통계적인 3분기 약세 계절성 이전에 선제적인 조정이 충분히 발생했다는 점도, 최근 시장에 할인율을 요구한 기존…
❤115
https://x.com/openai/status/2092691861773160673?s=46&t=3KuoBy2GjYj1L6_2KT0Yzg
❤39
https://x.com/sama/status/2093060670472241368?s=46&t=3KuoBy2GjYj1L6_2KT0Yzg
❤35
https://www.investing.com/news/stock-market-news/palo-alto-networks-ceo-held-acquisition-talks-with-both-okta-and-datadog-4877455 춘추전국시대에서 각 레이어의 파이를 점유하기 위한 시도들이 나오고 있음. PANW의 OKTA, DDOG 인수 가능성 제기. 어제 디인포메이션 발 NVDA의 허깅페이스 인수 역시 마찬가지로, 폐쇄형 모델과 개방형 모델 사이의 사이버 보안의 필요성이 삼각구도로 이어지고 있음. 이번 미토스 사태와 OAI 해킹사태 이후 생각보다 기업들의 움직임들이 빠르게 등장하고 있음.
❤52
https://www.bloomberg.com/news/articles/2026-08-27/openai-anthropic-urge-cyber-defense-action-as-ai-models-improve
❤32
Sell-side 리비전은 4-6월 사이 커버리지 개선, 섹터 콜은 점진적으로 7월부터 일부 목격 중.
❤52
4-5월부터 AI업계에 영향과 예상이 대두되는 듯 했고, 6-7월에 실제 프론티어 에이전트들에서 사건 헤드라인이 발생했고, 7-8월에 미국 주요 정부, 기업인사들이 시급하게 움직이기 시작했음. *특히 미토스, OpenAI 허깅페이스 해킹사건 이후 젠슨황의 오픈모델 AI 얼라이언스 설립, NVDA 허깅페이스 인수 설까지 이어지는 7월-8월 구간이 가장 캐털리스트를 일으킴.
❤61
Showing the 12 most recent of 114 posts we hold for @Macrojunglemicrolens. 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.
@Macrojunglemicrolens 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.
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.
Named by 6 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.
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 8 November 2026 — this entry's latest reading, not the date you are reading this.
“Macro Jungle | micro lens” (@Macrojunglemicrolens), 22,959 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/Macrojunglemicrolens.
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.