2 measurements taken within a single day. 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 851–853 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 01:19
852
no change
7 Aug 2026, 19:08
852
first reading
Engagement
19 posts held, back to 29 October 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
66.0%
avg views ÷ 852 subscribers
Avg views / post
562
1 post measured
Reaction rate
2.14%
reactions ÷ views · ER floor
Posts in window
1
of 19 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 16 July 2026
Posts held
19 (29 October 2025 – 16 July 2026)
Views total
562
Reactions total
12
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 01:19 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
91
Videos
12
Links
33
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
7s
Average length
7s
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
263 reactions across 18 posts, in 15 distinct kinds. The most used accounts for 24.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
64
24.3%
custom 6080151017855387268
57
21.7%
❤
53
20.2%
💯
33
12.5%
🔥
24
9.13%
❤🔥
8
3.04%
🫡
8
3.04%
🤓
7
2.66%
👎
2
0.76%
😁
2
0.76%
👏
1
0.38%
🖕
1
0.38%
😐
1
0.38%
🤣
1
0.38%
🥰
1
0.38%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 18 of the 19 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 263reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 29 October 2025 to 16 July 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.
Telegram Stars
Stars received
25
across the posts below
Posts paid on
1
of 19 we hold a reading for · 5%
Most on one post
25
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @kleycode. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 19 most recent posts we hold for this entry, published 29 October 2025 to 16 July 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Может ли ChatGPT торговать лучше человека?
Нашёл свежий обзор исследований про LLM-агентов в трейдинге. Авторам конечно надо верить не на 100%, потому что косяки есть даже в тексте, но зерно правды в статье содержится. В paper разобраны системы, которые читают новости, отчётность и рыночные данные, а затем самостоятельно принимают торговые решения.
Спойлер: идеи интересные, но отдавать GPT деньги пока рано.
Все си…
Мои недавние наработки для ускорения работы с ИИ:
Древовидная структура
Я держу файл, в котором кратко описан каждый из моих проектов, дабы Claude не терялся и сразу находил нужный при сбросе очередной сессии. Клод сам дописывает в этот файл новые проекты и удаляет старые. Внутри каждого проекта есть отдельный файл, в котором обычным списком хранятся последовательно все внесённые ключевые изменения и дата их приняти…
Защитил вчера курсовую 3-го курса на 10/10
Суть: строится процесс, который в каждый фиксированный момент времени неотличим от броуновского движения (распределение N(0, t)), но броуновским движением при этом не является - у него есть скачки.
Что было сделано: взял сжатую статью Hamza–Klebaner (2006), структурировал весь текст вместе с реконструкцией большинства доказательств, для каждой используемой классической тео…
За последние 3 месяца после первого касания с Claude code стало понятно как много пиздежа в твиттере. Каждый второй инфлюенсер выдает секретный промпт, который нагенерил ему сверхприбыльную стратегию на 200% годовых, 300к в наносек.
На деле профит возможен только при понимании, что такое бэктесты и как правильно их писать, что такое рынок, какие игроки на нем присутствуют и тд и тп. Особенно это актуально в околофин…
Я тут на днях, просыпаясь ночью, подумал как можно обойти алгоритм поиска ближайшего соседа от Spotify (Annoy). В итоге пришла идея с разделением пространства на сферы вместо плоскостей, а затем пускать перпендикуляры в n-мерном пространстве и таким образом оптимизировать обход дерева.
Annoy - это библиотека на C++, которую юзают все подряд для векторного поиска. Рекомендации, эмбеддинги, RAG. Стандарт индустрии.
П…
На днях пришла идея сравнить модель Блэка-Шоулза и нейросетки в предсказании цен на кол-опцион. Нагенерил данных без улыбки волатильности и с ней. Взял улыбку, так как именно она возникает когда люди сильно верят в возможность больших скачков.
Без улыбки результаты следующие:
--- РЕЗУЛЬТАТЫ ---
Средняя ошибка Блэка-Шоулза: $0.0814
Средняя ошибка Нейросети: $0.1743
Понятно, что в формуле Блэка волатильность являе…
Энтузиазм
У каждого деятельного человека основополагающим фактором успеха является энтузиазм. Здесь важно четко отличать энергию от энтузиазма. Человек может быть энергичным, но без энтузиазма - тогда он делает через силу и принуждение, не наслаждаясь самим процессом. Я прям сверхдолгое время был убежден, что сила в тупом делании и дисциплине, однако при каждой попытке внедрить желание совершать нетривиальные для мо…
Траблы с применением машинного обучения в финансах
Надо понимать, что на рынке 99% всего движения графика — это шум. То есть это такие движения, которые ни одна современная модель просто не может системно предсказывать из раза в раз. Откуда этот шум берётся?
1️⃣ Трейдеры;
2️⃣ Изменения ставки ФНС;
3️⃣ В целом иррациональность большинства поступков людей.
Не даром при попытке моделировать рынок необходимо использова…
Составил расписание на 2-ой семестр 3-го курса, вероятно похожу еще на пары на Покре по машинке и количественным финансам
❤5👍2
Showing the 12 most recent of 19 posts we hold for @kleycode. 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.
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 8 August 2026 — this
entry's latest reading, not the date you are reading this.
“Аркадия” (@kleycode), 852 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/kleycode.
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.