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 9 September 2026 and assigned it the closest of 31 fixed categories, at 87% 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
32 measurements spanning 41 days, net -2,002. 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 31,698–34,300 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
17 Sept 2026, 05:38
31,998
-48
15 Sept 2026, 05:01
32,046
-40
13 Sept 2026, 12:59
32,086
-83
11 Sept 2026, 17:16
32,169
-82
9 Sept 2026, 06:41
32,251
-184
5 Sept 2026, 21:41
32,435
-116
3 Sept 2026, 20:18
32,551
-78
2 Sept 2026, 11:43
32,629
-19
1 Sept 2026, 13:55
32,648
-38
31 Aug 2026, 10:25
32,686
-55
30 Aug 2026, 07:28
32,741
-37
29 Aug 2026, 09:14
32,778
-53
28 Aug 2026, 10:38
32,831
-43
27 Aug 2026, 11:25
32,874
-49
26 Aug 2026, 08:47
32,923
-64
25 Aug 2026, 05:35
32,987
-21
24 Aug 2026, 07:24
33,008
-82
22 Aug 2026, 14:23
33,090
-53
21 Aug 2026, 08:27
33,143
-73
20 Aug 2026, 05:13
33,216
first reading
Engagement
42 posts held, back to 13 June 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 74 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
13.1%
avg views ÷ 31,998 subscribers
Avg views / post
4,200
8 posts measured
Reaction rate
0.259%
reactions ÷ views · ER floor
Posts in window
8
of 42 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 20 September 2026
Posts held
42 (13 June 2026 – 20 September 2026)
Views total
33,560
Reactions total
87
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 06:48 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
275
Videos
199
Links
616
Lifetime counters from Telegram’s own channel header, read 23 September 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
35s
Average length
35s
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
575 reactions across 40 posts, in 9 distinct kinds. The most used accounts for 75.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
432
75.1%
👍
48
8.35%
🔥
41
7.13%
👏
36
6.26%
🏆
8
1.39%
🎉
5
0.87%
🙏
3
0.522%
🍾
1
0.174%
🤩
1
0.174%
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 40 of the 42 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 575 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 42 most recent posts we hold, published 13 June 2026 to 20 September 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.
بعد از مدتها، یک آفر متفاوت از زورا.
تا ۶۰٪ تخفیف روی پلنهای
لستپراپ و دو مرحلهای زورا
بدون شرط اضافه و بدون تغییر در قوانین پلنها؛
همان تجربه زورا، این بار با هزینهای متفاوت.
۶۰٪ تخفیف | کد Z60X
قابل استفاده تا فاند 6K
۵۰٪ تخفیف | کد Z50X
قابل استفاده تا فاند 25K
۲۵٪ تخفیف | کد Z25X
قابل استفاده تا فاند 200K
فرصتی کمسابقه برای انتخاب پلنی که با سبک معاملاتی شما هماهنگتر است؛ با قوانین اصلی همان پلن و ب…
خالق سبک NDS کیست؟
دکتر فازی لاجیک، با نام اصلی ایرج جعفریان، تریدر ایرانی فعال در فضای بینالمللی است که با ارائه سبک NDS، دیدگاهی متفاوت برای خواندن رفتار و ساختار بازار معرفی کرد.
اما NDS چگونه شکل گرفت و چه منطقی پشت این سبک معاملاتی قرار دارد؟ برای آشنایی بیشتر با خالق این سبک، مسیر حرفهای او و مفاهیم NDS، مقاله زیر را از دست ندهید:
🔗 [مطالعه مقاله خالق سبک NDS]
پس از مطالعه، منتظر دیدگاهها و نظرات ارزشمن…
🔵 عضویت در گروه VIP کاربران ZoraFX
اگر تا امروز تجربهی برداشت سود موفق از ZoraFX را داشتهاید، میتوانید به جمع اعضای VIP زورا افیکس بپیوندید.
در این گروه، خدمات، مزایا و برنامههای اختصاصی ویژهی کاربران VIP زورا ارائه خواهد شد.
برای بررسی شرایط عضویت، کافیست وارد بات زیر شوید و ایمیل حساب ZoraFX خود را تأیید کنید:
👉 https://t.me/zorafx_loyalty_bot
پس از تأیید سابقهی برداشت، دسترسی شما به گروه VIP فعال خواه…
📘 راهنمای صفر تا صد پلن LastProp زوراافیکس
اگر درباره LastProp سؤال دارید یا میخواهید قبل از خرید دقیقاً بدونید مسیر چطور پیش میره، این راهنما رو براتون آماده کردیم.
از خرید و دو فاز ارزیابی تا حساب Real و برداشت سود، قوانین، محدودیتها، سطح عملکرد، مزایا و شرایط برداشت، همه بهصورت ساده و قدمبهقدم داخل این فایل توضیح داده شده.
پیشنهاد میکنیم قبل از شروع پلن LastProp، یکبار کامل این راهنما رو مطالعه کنید. 💙
…
📢 اطلاعیه بروزرسانی نمادهای کریپتو | سپتامبر ۲۰۲۶
معاملهگران گرامی زورا،
امیدواریم همواره معاملات موفق و پرسودی را تجربه کنید. 🌱
به اطلاع میرساند، در راستای بهبود عملکرد و اعمال برخی بهروزرسانیها و اصلاحات فنی، تنظیمات تعدادی از نمادهای کریپتویی در آخر هفته پیشرو بهروزرسانی خواهد شد.
🔹 به همین منظور، از تمامی معاملهگران درخواست میشود تمامی معاملات باز خود روی نمادهای کریپتویی را حداکثر تا ساعت 23:59 UTC رو…
درگاه تتری اختصاصی ZoraFX راهاندازی شد 🚀
فاز اول درگاه پرداخت تتر ZoraFX روی شبکه BEP20 با موفقیت راهاندازی شد.
از این پس برای انتقال دارایی، نیازی به دریافت و هماهنگی آدرس به روش قبلی ندارید و میتوانید مستقیماً از طریق درگاه اختصاصی ZoraFX:
• حساب معاملاتی خود را شارژ کنید
این درگاه با هدف سادهتر، سریعتر و امنتر شدن فرآیند پرداخت کاربران توسعه داده شده و گام مهم دیگری در مسیر تکمیل زیرساختهای اختصاصی Zora…
قبل از اینکه دنبال نقطه ورود باشید، باید به یک سؤال مهم پاسخ دهید: امروز بازار احتمالاً به کدام سمت حرکت میکند؟
در سبک ICT، پاسخ این سؤال با مفهومی به نام بایاس شکل میگیرد؛ دیدگاهی که جهت احتمالی بازار را مشخص میکند و کمک میکند برخلاف جریان اصلی معامله نکنید.
اگر میخواهید چارت را هدفمندتر تحلیل کنید، مقاله بایاس در ICT را از دست ندهید:
🔗 [مطالعه مقاله بایاس در ICT]
روزی که پنج ذهن متفاوت تصمیم گرفتند بازار را رمزگشایی کنند، یکی از پیچیدهترین و مرموزترین سبکهای معاملاتی شکل گرفت:
RTM یا Read The Market؛
هنر خواندن بازار.
اگر کمتر از دو سال است که وارد بازار شدهاید، احتمالاً RTM نقطه شروع مناسبی برایتان نیست؛ اما اگر آمادهاید عمیقتر از ظاهر کندلها به بازار نگاه کنید، این مقاله را از دست ندهید:
🔗 [آشنایی با سبک معاملاتی RTM]
پس از مطالعه، منتظر نظرات و تجربههای ارزشمند…
بازار قبل از شروع یک حرکت جدی، چه نشانههایی از خود بهجا میگذارد و چطور میتوان منطق پشت جریان قیمت را بهتر درک کرد؟
تحلیل NRT تلاش میکند با تمرکز بر رفتار قیمت، ساختار بازار و نقاط حساس، دید عمیقتری از مسیر احتمالی حرکت قیمت به معاملهگر بدهد. در این مقاله توضیح دادهایم NRT چیست، چگونه به چارت نگاه میکند و چه تفاوتی در تحلیل بازار ایجاد میکند.
🔗 [مطالعه مقاله تحلیل NRT]
پس از مطالعه، منتظر دیدگاهها و تجرب…
ICT یا RTM؛ کدام سبک انتخاب بهتری است؟
هر دو سبک به رفتار قیمت و ردپای پولهای بزرگ توجه دارند؛ اما در نوع نگاه به بازار، شناسایی موقعیتها و انتخاب نقطه ورود تفاوتهای مهمی میان آنها وجود دارد.
در این مقاله، شباهتها و تفاوتهای ICT و RTM را بررسی کردهایم تا راحتتر تشخیص دهید کدام سبک با دیدگاه و شخصیت معاملاتی شما سازگارتر است.
اگر هنوز بین این دو سبک مردد هستید، این مقایسه را از دست ندهید:
🔗 [مشاهده مقایسه …
قبل از هر معامله، یک سؤال مهم وجود دارد: بازار امروز بیشتر تمایل به صعود دارد یا نزول؟
در ICT، پاسخ به همین سؤال با مفهوم Bias شروع میشود؛ یعنی پیدا کردن جهت احتمالی بازار قبل از ورود به معامله.
👇 در مقاله زیر کاملتر بخوانید:
🔗 [لینک مقاله]
منتظر کامنتها و نظرات ارزشمندتون هستیم. 💬
❤6
Showing the 12 most recent of 42 posts we hold for @zorafx_academy. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
The shares total 113%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 42 most recent posts we hold, published 13 June 2026 to 20 September 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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 4 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 23 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
ZoraFX |بروکر، پراپ @zorafx_fa · 51,141 Telegram ranks this channel #1 of 75 here — alongside 74 others — read 23 September 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“ZoraFX_Academy” (@zorafx_academy), 31,998 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/zorafx_academy.
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.