A social-media feed can combine useful charts, commentary and sales material. Evaluate each post’s provenance and purpose rather than treating an author’s years on the platform as evidence of quality.

The same 1% on two chart scales

Read axis labels and ranges before judging a posted chart. This counterexample separates a price change from its visual magnification.

Scroll sideways to see the full diagram

The same 1% on two chart scalesTwo panels show the same fictional prices, 100 and 101, at the same consecutive moments. The first vertical scale runs from 0 to 110; the second from 99 to 102. Points lie on the correct linear axes. The difference occupies little height on the broad scale and more on the zoomed scale. Both changes equal (101/100 − 1)*100 = 1%. Two points do not describe the intervening path. Read the axis range before judging the visual size of a move.SAME DATA, DIFFERENT APPEARANCEFictional prices • two readings onlyScale 0–110055110t0t1100 →101Scale 99–10299100101102t0t1100 →101Both: (101 /100 − 1) × 100Change = 1%The axis enlarges the image, not the return.

Assumptions: Two fictional positive prices of one instrument at consecutive moments. Both panels are linear, with identical time order and spacing but different price-axis ranges. No trades or costs. This compares two displays of the same data.

Readings 100 and 101 are identical in both panels. On the 0–110 axis, the difference of 1 is small relative to the whole range. On the 99–102 axis it occupies one third of the range. The percentage calculation is unchanged: (101 /100 − 1) × 100 = 1%.

When sharing a chart, keep the unit, axis range and time labels visible. Zooming helps reveal small changes and is not itself an error. Inferring a larger return solely from line steepness, without reading the scale, would be an error.

We assess no actual post or author. The connector between readings is illustrative: this model does not reveal the intervening price path or a future direction.

Changing the axis range does not change the one-percent price move.

What Twitter offers when it works on the good side

X can help locate institutional releases and signed research. Reach an institution’s profile from its official website and follow a post back to the underlying publication. Do not assume that every channel publishes simultaneously or that social media precede other sources. A short extract can omit a table, definition or correction. An employer name or profile badge does not validate each forecast.

The Weekly ChartStorm by Callum Thomas describes a weekly selection focused on the S&P 500 and related market and macro topics. Its publisher says chart-tweet-storms began in 2015, the newsletter in 2021 and paid access in 2023. This is context for a currency hypothesis, not a ready-made FX trade list or an audited return record. Check a sample issue, source links, current access and payment terms.

What selected screenshots leave out

A post showing only a winner does not establish the complete account result. Ask for the period, initial capital, deposits and withdrawals, open losses, costs and selection method. In a hypothetical record, three gains of PLN 100 and two omitted losses of PLN 200 total −PLN 100 before other costs. Every winning screenshot could be authentic while the selected presentation remains misleading. A subscription fee alone does not prove fraud; inspect the service, cancellation terms and conflicts of interest.

Survivorship bias arises when visible successes omit unsuccessful participants. Selective screenshots can also omit losing trades. The illustrative mechanism does not establish counts of profitable accounts.

How to build a feed that helps instead of interfering

Start from authenticated institutional sources and trace posts to the original releases. Verify named analysts’ current affiliations rather than relying on an undated employer list.

Create public or private topic lists for the sources needed by your method, and check visibility before saving. X’s list timeline selects the included accounts; it does not fact-check their posts. Choose reading windows and notifications suited to the task and evaluate their usefulness, without assuming a fixed daily time saving.

For any posted chart, record its source, data cutoff, unit, axis range, series definition and chosen period. A hypothetical rise from 4% to 5% is one percentage point but a 25% relative increase. Read both axes and any time shift before treating similar line shapes as a relationship.

A deliberately constructed, nonfinancial example has A levels 100, 101, 104, 105, 108 and B levels 100, 103, 104, 107, 108. Pearson correlation of levels is about +0.94. Their absolute changes are 1, 3, 1, 3 and 3, 1, 3, 1, with correlation −1. Both end eight units higher, yet their successive changes move oppositely. Percentage returns create another series. Define what was compared; none of these coefficients establishes causation or a trading edge.

Check the service and applicable jurisdiction

Check the legal entity, service and applicable jurisdiction separately from the author’s popularity. Where a service requires authorisation, use the relevant regulator’s register and independently matched contact details; warning notices provide additional information, and absence from a warning list is not approval. For analysis, check the original document, data and stated limitations. An analyst need not have a personal trading record to explain an official release.

Regulatory treatment depends on content, service and jurisdiction. FCA FG24/1 concerns UK financial promotions, including activity by unauthorised influencers. In the EU, ESMA explains that even a nontechnical public post may constitute an investment recommendation under the MAR framework. Personalised advice is a separate question. An educational label or “not investment advice” disclaimer does not alone decide the content’s legal character, and charging for a course does not automatically make it portfolio management.

Twitter as a mirror that easily reflects somebody elses mistake

There is a subtler trap that even reasonable accounts can spring. When a respected analyst posts a EUR/USD chart with a note "interesting level at 1.0850," and you happen to be sitting on a position there, your brain reads it as confirmation. It is not confirmation; it is the opinion of a single person who rarely shares your position size, your time horizon, or your account currency. The same logic applies to copy-trading platforms such as eToro and ZuluTrade — I expand the topic in my note on copy-trading services and the deeper psychological essay on survivorship bias in trading.

Use weekly market preparation to record an original URL, publication date, factual claim, interpretation and any unresolved question. A post during a release may point to useful information, but verify it against the official publication before using it. When a position is open, apply the same information rules and preserve why any decision changed.

What to do tomorrow

  1. Review sources that omit underlying data or show only selected account outcomes. For a paid offer, inspect the entity, service, cancellation terms and evidence for its claims rather than judging by price alone.
  2. Organise the institution, macro and instrument-specific sources you actually need into lists. Weekly ChartStorm illustrates equity and macro commentary; a separate currency hypothesis is needed before using that context in FX.
  3. Choose a trial reading window and notification settings suited to your information needs. Assess what you found and whether it affected decisions; a time limit is your workflow choice, not an established return improvement.
  4. Verify an author’s identity, current affiliation, original research and corrections. A fixed two-year publication history is not a qualification threshold, and a badge does not verify each chart.
  5. Check applicable regulator registers and warning notices. Absence from a warning list is not proof of authorization or safety.