Channel
@ivistscalp5
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
140subscribers
+3 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002391740614 |
|---|---|
| Type | Channel |
| Username | @ivistscalp5 |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 30 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 2 times, most recently 30 August 2026 |
| On Telegram | t.me/ivistscalp5 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 22 Aug 2026, 07:58 | 140 | +1 |
| 15 Aug 2026, 03:55 | 139 | +2 |
| 8 Aug 2026, 23:17 | 137 | no change |
| 6 Aug 2026, 23:46 | 137 | first reading |
20 posts held, back to 21 May 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 1 pageof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 8 August 2026 |
|---|---|
| Posts held | 20 (21 May 2026 – 8 August 2026) |
| Views total | 48 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 23:17 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.
Measured directly from 2 videos 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.
VISTmany and iVISTscalp5 This research is part of the VISTmany project, with iVISTscalp5 serving as its primary computational research and market-analysis framework. The project began with empirical observations of recurring market timings and their relationship with subsequent price movement. These observations were first implemented and systematically studied through iVISTscalp5, which generates forward-looking t…
VISTmany Research Journal Researching Financial Markets Through Time 1. The Beginning of the VISTmany Research Journal 2. Why Time Has Been Forgotten in Financial Market Analysis. A Fundamental Research Problem 3. The Time Hypothesis: Can Time Be an Independent Variable in Financial Markets? 4. From Price to Time: A New Methodology for Financial Market Research 5. From Signals to Temporal Space: Why Market Time…
https://www.mql5.com/en/blogs/post/772243
#VISTmany #TLV #iVISTscalp5
The system projects time, direction, and expected movement through Liquidity Activation Points (timings). #iVISTscalp5 #VISTmany #scalping #xauusd
Clusters represent a concentration of temporal activity and may indicate regions where market participation becomes more active compared with isolated timings. Timing Rays Analytical projections that remain independent of current price action prior to activation. As a timing approaches, these projections visually converge toward the market, illustrating the potential spatial range associated with the activation wi…
Time as the Primary Market Trigger: The VISTmany Research Methodology and iVISTscalp5 Framework In modern technical analysis, the vast majority of analytical methods focus primarily on the price dimension. Most approaches attempt to answer a single question: “To what level will the price move?” The VISTmany research project proposes an alternative perspective by placing the time–price relationship at the center of…
TLV Time Language VISTmany A Language for Studying Financial Markets Through Time ⸻ LAP Liquidity Activation Point A moment when the probability of market movement increases. ⸻ t(p) Timing Level A moment in time when market activation may occur. ⸻ p(p) Price Level A key market price structure. ⸻ TPA Time Price Alignment The interaction between timing and price. ⸻ TSI Timing Strength Index A measure of ti…
#iVISTscalp5 is not merely a trading indicator. It is a research framework for studying market behavior through time. The framework is based on a simple but powerful hypothesis: The critical question is not where the market may move. The critical question is: When is the market ready to move? By combining #Time Structures, Price Structures, and Liquidity Activation Points, iVISTscalp5 provides a structured meth…
VISTmany is an independent research project dedicated to studying the influence of time on financial market behavior. Unlike most market methodologies that focus primarily on price, volume, or traditional technical indicators, VISTmany explores the temporal structure of markets and the moments when market activity is more likely to become activated. The project is built around its own analytical framework known as …
Photo, posted without a caption
The system projects time, direction, and expected movement through Liquidity Activation Points (timings). #iVISTscalp5 #VISTmany #scalping #TLV
Showing the 12 most recent of 20 posts we hold for @ivistscalp5. 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.
Citation-graph rank — 280,856 of 1,626,935entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
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 22 August 2026 — this entry's latest reading, not the date you are reading this.
“iVISTscalp5” (@ivistscalp5), 140 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/ivistscalp5.
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.