Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 95% 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 58 days, net +32,356. 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 528,410–570,472 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
4 Oct 2026, 08:35
565,619
+4,502
25 Sept 2026, 15:02
561,117
+3,970
19 Sept 2026, 04:21
557,147
+1,134
16 Sept 2026, 16:00
556,013
+1,040
14 Sept 2026, 16:58
554,973
+877
13 Sept 2026, 05:19
554,096
+606
11 Sept 2026, 04:40
553,490
+1,293
8 Sept 2026, 08:56
552,197
+1,547
5 Sept 2026, 05:37
550,650
+693
3 Sept 2026, 09:56
549,957
+883
2 Sept 2026, 00:33
549,074
+539
31 Aug 2026, 23:36
548,535
+754
31 Aug 2026, 00:28
547,781
+630
30 Aug 2026, 02:13
547,151
+165
29 Aug 2026, 05:42
546,986
+795
28 Aug 2026, 08:54
546,191
+1,020
27 Aug 2026, 11:08
545,171
+748
26 Aug 2026, 07:47
544,423
+818
25 Aug 2026, 05:36
543,605
+1,027
24 Aug 2026, 05:28
542,578
first reading
Engagement
547 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 125 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
1.86%
avg views ÷ 565,619 subscribers
Avg views / post
10,500
274 posts measured
Reaction rate
0.331%
reactions ÷ views · ER floor
Posts in window
274
of 547 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 6 October 2026
Posts held
547 (5 August 2026 – 6 October 2026)
Views total
2,889,630
Reactions total
9,553
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Oct 2026, 20:53 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
≈4,250
Videos
≈7
Links
≈4,260
Lifetime counters from Telegram’s own channel header, read 6 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.
Video runtime
14m 26s
Average length
14m 26s
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
17,774 reactions across 546 posts, in 26 distinct kinds. The most used accounts for 54.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
9,684
54.5%
👍
4,405
24.8%
🔥
1,167
6.57%
🤩
945
5.32%
👌
670
3.77%
👨💻
236
1.33%
⚡
131
0.737%
✍
90
0.506%
👀
90
0.506%
🏆
77
0.433%
🎉
59
0.332%
🤣
55
0.309%
👏
27
0.152%
🤡
26
0.146%
🤔
22
0.124%
😁
21
0.118%
🤯
18
0.101%
👾
13
0.073%
🤝
9
0.051%
💯
7
0.039%
6 further kinds
22
0.124%
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 546 of the 547 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 17,774 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 547 most recent posts we hold, published 5 August 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.
Adaptive EA design using random graph theory instead of a fixed market map.
A state-transition network encodes each closed bar via EMA spread/ATR, ATR regime, and optional RSI buckets, producing 45 states. Transitions update a decayed, Laplace-smoothed Markov matrix. A k-step matrix power yields the distribution k bars ahead, converted into a bounded directional expectation plus an entropy-based confidence gate.
A …
Running one strategy across multiple symbols and hours creates separate variants, and account-level metrics can hide where performance differs. A dashboard script addresses this by grouping closed deals by symbol and UTC closing hour, then computing win rate and payoff-based edge ratio per cell.
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With Model Context Protocol (MCP), AI can work directly with MetaTrader 5 data and tools — turning the built-in AI Assistant into an agent capable of handling complex, multi-step tasks.
Analyze markets and trading history, review open positions, work with charts, test and optimize Expert Advisors, and perform supported trading operations — all through natural-language instructions.
Instead of manually collecting da…
ST-Expert reframes forecasting as a spatiotemporal problem: price history plus a dynamic network of cross-asset links. Using a Mixture of Experts, it shifts weight between specialist blocks as market drivers change, improving resilience, and exposing which relationships influenced a signal.
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Refactor proposal for MQL5 divergence logic: extract oscillator, pivot detection, divergence classification, and state tracking from Adaptive SuperTrend into a reusable header, DivergenceEngine.mqh.
The module owns settings, optional RSI handle, buffers, and state (last pivots, divergence type, bars-since). Public access stays narrow: last divergence type, age, oscillator value, reset, and required lookback.
Integr…
MetaTrader 5 EAs often keep critical strategy state only in RAM (grid depth, recovery steps, daily counters, online-trained model weights). After a terminal restart, the EA can mismanage existing positions because its internal context is gone.
A common persistence bug is overwriting the live state file: a crash mid-write truncates it, leaving “valid-looking” but wrong data. The proposed fix is atomic-style saving: w…
A specification panel reflects the broker’s current contract report. Broker Contract Change Watch logs when selected contract properties differ from the last saved observation, with a baseline stored per account server, login, and chart symbol.
Watched fields include digits, point size, minimum tick, contract size, volume min/max/step and directional limit, stops and freeze levels. It also tracks trading and executi…
An Adaptive Kalman Trend Filter indicator is designed to reduce short-term price noise and present a clearer view of the underlying trend. It applies Kalman-style state estimation to smooth input data while retaining enough responsiveness to reflect meaningful movement.
The adaptive component modifies the filter’s sensitivity as volatility and market structure change. In lower-noise phases it can prioritize smoothne…
RSI Exhaustion Reversal - EURUSD is an open-source MQL5 Expert Advisor built for strategy research, historical testing, and education. It is restricted to the MetaTrader 5 Strategy Tester and will not place trades when attached to a regular chart. Full source code is included for inspection and modification.
The strategy targets EURUSD on M5 with SELL-only logic. It watches RSI(14) for an overbought exhaustion condi…
ZoneUS30 is a simplified Expert Advisor focused on the US30 index and limited to SELL-only execution. The logic targets overextended upside moves where price may revert toward a prior reference area, triggering entries when internal conditions align.
The model combines mean-reversion behavior with the practical impact of swap. When a broker pays positive overnight swap on US30 shorts, holding positions across multip…
Entry/exit points remain the core problem in algorithmic trading because recognizable patterns are usually visible only after the move. Trend and flat regimes are easy to label visually, but unreliable as predictive signals without quantified probabilities.
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Inversion Fair Value Gaps adds automated fair value gap detection with bar-close confirmation and no repaint behavior.
Gaps are tracked until a candle body closes through the zone, marking an inversion event. After inversion, the tool monitors for bounce reactions off the inverted area and generates signals.
Options include a midline, filled-zone removal, and adjustable color settings for zones and markers. Alert r…
❤31👍16🔥9🤩9✍8👨💻4👏2
Showing the 12 most recent of 547 posts we hold for @mql5dev. 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.
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 2 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 15 August 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.
MQL5 Алготрейдинг @mql5ru · 20,433 Telegram ranks this channel #1 of 56 here — alongside 55 others — read 28 September 2026
MetaTrader Hints @metatrader_hints · 38,240 Telegram ranks this channel #1 of 47 here — alongside 46 others — read 3 September 2026
Trading Algorítmico MQL5 @mql5es · 45,956 Telegram ranks this channel #1 of 61 here — alongside 60 others — read 28 August 2026
FBS Analytics @fbsanalytics · 86,566 Telegram ranks this channel #8 of 84 here — alongside 83 others — read 17 August 2026
FundedNext Official Channel @FundedNextOfficialCommunity · 61,219 Telegram ranks this channel #29 of 77 here — alongside 76 others — read 22 August 2026
ETI - English @eti_algos · 37,782 Telegram ranks this channel #31 of 59 here — alongside 58 others — read 30 August 2026
Register KFX VIP / VVIP 🇮🇩 @registerkfxvip · 44,338 Telegram ranks this channel #45 of 74 here — alongside 73 others — read 27 August 2026
Octa Analytics @octa_analytics · 75,353 Telegram ranks this channel #59 of 84 here — alongside 83 others — read 19 August 2026
🎖 NetProfitFX 🥷🏽 FREE Trading Signals @NPFXSignals · 18,834 Telegram ranks this channel #60 of 63 here — alongside 62 others — read 5 October 2026
Hexa Bot @HexaAutotradingEA · 19,264 Telegram ranks this channel #64 of 67 here — alongside 66 others — read 2 October 2026
TMA OFFICIAL® @TMAbyArty · 24,921 Telegram ranks this channel #69 of 86 here — alongside 85 others — read 14 September 2026
FXStreet Forex News @fxstreetforex · 103,181 Telegram ranks this channel #71 of 88 here — alongside 87 others — read 15 August 2026
This channel appears in 12 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
4 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 4 October 2026 — this
entry's latest reading, not the date you are reading this.
“MQL5 Algo Trading” (@mql5dev), 565,619 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/mql5dev.
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.