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Telegram profile photo for iVISTscalp5

Channel

iVISTscalp5

@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.

Register entry

Telegram ID-1002391740614
TypeChannel
Username@ivistscalp5
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live14 September 2026
Measurements held4
Confirmed unchanged4 times, most recently 14 September 2026
On Telegramt.me/ivistscalp5

Growth

137140138.56 August 2026 — 137 subscribers8 August 2026 — 137 subscribers15 August 2026 — 139 subscribers22 August 2026 — 140 subscribers6 August 202622 August 2026
4 measurements spanning 15 days, net +3. 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 137–140 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
22 Aug 2026, 07:58140+1
15 Aug 2026, 03:55139+2
8 Aug 2026, 23:17137no change
6 Aug 2026, 23:46137first reading

Engagement

20 posts held, back to 21 May 2026the 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 20 posts for this entry, the most recent from 8 August 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Video runtime
1m 46s
Average length
53s

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.

Recent posts

8 Aug 2026, 10:08 UTC12 viewsread 8 August 2026
Photo

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

3 Aug 2026, 19:43 UTC36 viewsread 8 August 2026
Photo

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

25 Jun 2026, 11:43 UTC124 viewsread 8 August 2026
Video

The system projects time, direction, and expected movement through Liquidity Activation Points (timings). #iVISTscalp5 #VISTmany #scalping #xauusd

24 Jun 2026, 15:04 UTC94 viewsread 8 August 2026

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

24 Jun 2026, 15:02 UTC62 viewsread 8 August 2026
Photo

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

24 Jun 2026, 02:28 UTC66 viewsread 8 August 2026
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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

24 Jun 2026, 01:31 UTC68 viewsread 8 August 2026
Video

#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

17 Jun 2026, 14:30 UTC91 viewsread 8 August 2026

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

30 May 2026, 16:28 UTC134 viewsread 8 August 2026
Photo

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.

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.

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 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.