Channel
@derivativesforall
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
1,124subscribers
+87 since we began measuring on 4 September 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001983407342 |
|---|---|
| Type | Channel |
| Username | @derivativesforall |
| Created | Between 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 4 September 2026 |
| Last confirmed live | 2 November 2026 |
| Measurements held | 14 |
| Confirmed unchanged | 1 time, most recently 2 November 2026 |
| On Telegram | t.me/derivativesforall |
Crypto & trading — 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 29 September 2026 and assigned it the closest of 31 fixed categories, at 86% 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 |
|---|---|---|
| 2 Nov 2026, 14:35 | 1,124 | +27 |
| 30 Oct 2026, 13:49 | 1,097 | +51 |
| 27 Oct 2026, 06:26 | 1,046 | -3 |
| 24 Oct 2026, 00:37 | 1,049 | -2 |
| 21 Oct 2026, 07:20 | 1,051 | -1 |
| 18 Oct 2026, 12:47 | 1,052 | +2 |
| 15 Oct 2026, 21:09 | 1,050 | +3 |
| 12 Oct 2026, 19:21 | 1,047 | +2 |
| 6 Oct 2026, 10:56 | 1,045 | +5 |
| 29 Sept 2026, 15:38 | 1,040 | -1 |
| 15 Sept 2026, 13:55 | 1,041 | +2 |
| 11 Sept 2026, 18:21 | 1,039 | +1 |
| 6 Sept 2026, 21:37 | 1,038 | +1 |
| 4 Sept 2026, 14:22 | 1,037 | first reading |
18 posts held, back to 23 September 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 page 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 18 posts for this entry, the most recent from 25 August 2026. An engagement rate over an empty window would be a number about nothing.
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.
115 reactions across 14 posts, in 5 distinct kinds. The most used accounts for 53.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 61 | 53.0% | |
| 👍 | 33 | 28.7% | |
| 🙏 | 12 | 10.4% | |
| 👌 | 8 | 6.96% | |
| 👎 | 1 | 0.87% |
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 16 of the 18 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 115 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 23 September 2025 to 25 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.
کلام اخر. لطفا هرتحلیلی رو قبول نکنیم و احساسی در مورد موضوعات تصمیم نگیریم. هر دوستی که این تحلیل از نظرش درسته. همین امروز بازار مشتقه رو بزار کنار لطفا هنوز دنبال سودهای نجومی هستیم! مملکت تورم داره. اما بازار مشتقه قرار نیست جبرانش کنه
👍9
Signed فرنوش دوات گرزاده
باخت سنگین سهامداران انار 🔵صندوق سهامی انار با تمرکز بر استراتژی کاوردکال در یکسال اخیر بازدهی ۶۰ درصدی رو خلق کرده؛ 🔵دیگر صندوق سهامی گروه ترنج یعنی سرو در همین مدت موفق به ثبت بازدهی ۱۴۱ درصدی شده! ◀️تجربۀ تلخ انار نشون داد خطاهای محاسباتی مدیران صندوق‌ها و تغییرات ناگهانی استراتژی‌های معاملاتی تا حد می‌تونه باعث زیان و سلب‌اعتماد سهامداران بشه. @BehnamSamadi_ir ☑️
Signed فرنوش دوات گرزاده
وقتی یکی دانش کاری رو نداره هر تحلیلی ارائه میده ساده ترین تحلیل این هست، رسالت این صندوق ها متفاوت و کارش ساختن سود بالاتر از صندوق درآمد ثابت با ریسک کم تر و بازدهی بالاتر برا دیده شدن هرچیزی رو نزاریم. باز یخرده همه چی آروم شده چسبیدن به بازار مشتقه
👍5
Signed فرنوش دوات گرزاده
@Sahraoption ble.ir/join/7e2UjLscNo
❤1
Signed فرنوش دوات گرزاده
در بررسی اخیر مدل قیمت‌گذاری آپشن بارندورف-نیلسن و شپرد (BNS)، بیش از پیش به توانمندی این چارچوب در بازنمایی پویایی‌های واقعی بازار پی بردم. مدل BNS بر این اصل استوار است که نوسان‌پذیری، فرآیندی ایستا نیست. این متغیر ممکن است برای دوره‌هایی نسبتاً خاموش باشد، اما به‌ناگاه با جهش‌های قابل‌توجهی همراه می‌شود. این مدل با بهره‌گیری از فرآیندهای بازگشت به میانگین یا به بیانی دیگر بازگشت نوسانات به سطح بلندمدت، امکان بروز…
❤5👍1
Signed فرنوش دوات گرزاده
Photo, posted without a caption
❤1
Signed فرنوش دوات گرزاده
📊 مدل‌های قیمت‌گذاری جامپ-دیفیوژن (پواسون)؛ ضرورتی برای بازارهای واقعی مدل‌های بلک-شولز فرض می‌کنند قیمت دارایی همواره پیوسته حرکت می‌کند، اما در دنیای واقعی، شوک‌های ناگهانی (مثل اخبار اقتصادی، بحران‌ها یا سقوط‌های ناگهانی) بارها دیده می‌شوند. اینجاست که مدل‌های Jump-Diffusion وارد می‌شوند. این مدل‌ها با افزودن یک فرآیند پواسون (Poisson Process) به حرکت براونی، پدیده‌های نادر اما تأثیرگذار را شبیه‌سازی می‌کنند. 🔑…
❤5
Signed فرنوش دوات گرزاده
Photo, posted without a caption
Signed فرنوش دوات گرزاده
مدل کُو نشان می‌دهد که واکنش بیش‌ازحد و کم‌واکنشی بازار می‌توانند با ساختار پرش‌ها توضیح داده شوند؛ بنابراین این مدل تنها یک ابزار ریاضی نیست، بلکه تلاشی برای نزدیک‌تر کردن مدل مالی به رفتار واقعی بازار است. این مقاله یک مدل پیشرفته برای قیمت‌گذاری اختیار معرفی می‌کند که با افزودن پرش‌های تصادفی دو نمایی به حرکت قیمت، هم واقع‌گراتر از بلک-شولز است و هم برای محاسبات مالی کارآمد و تحلیلی می‌ماند. @derivativesforall
Signed فرنوش دوات گرزاده
Posted without readable text
این فیلم ها بهتون کمک میکنه ببینید چقدر از پس کار میاید اگر میخواید پولاتونو از دست بدین. خب بدین به تیم ما چرا غریبه😄😄😄😄
👌4
Signed فرنوش دوات گرزاده
با سلام و احترام بعنوان عضو کوچکی از خانواده بازاذ مشتقه یک توصیه دوستانه دارم. الان که بازار مثبت باز شده و بازار پکیج فروشان داغ شده. تحت تاثیر قرار نگیرید. و پول به دوره ای که مطمئن نیستید ندین.
👌4❤1
Signed فرنوش دوات گرزاده
Showing the 12 most recent of 18 posts we hold for @derivativesforall. 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.
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.
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.
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.
This channel appears in 4 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 2 November 2026 — this entry's latest reading, not the date you are reading this.
“کانال بازار مشتقات برای همه” (@derivativesforall), 1,124 subscribers as measured 2 November 2026. Telegram Register, tgregister.com/channel/derivativesforall.
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.