What if we compared traders' behavior on Noise with where people's attention is focused across the internet? Could that give us an edge in trading?
This measures reality independently: 1.00 means a topic is exactly at its own 90-day baseline.
This index combines 5 sources: GDELT news · Wikipedia · Hacker News · Wikipedia edits · YouTube. The coloured dots on each chart show which of them went into it. A market covered by a single source is that source's normalised series, not a composite. YouTube data starts in late August 2026, so this index stays in beta until it has enough history. Posts on X use the 4-source index.
No market matches that filter.
| Market | Index | 1d | 7d | 30d | Noise price | Noise 7 days | Sources in | Days |
|---|---|---|---|---|---|---|---|---|
| Claude | +0.5% | +108.5% | +174.8% | 62.28° | -9.3% | GDELT news, Wikipedia, Hacker News, Wikipedia edits, YouTube | 415 | |
| Humanoid Robots | +58.3% | +72.4% | +79.8% | 58.91° | -10.4% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Run Clubs | -0.8% | -12.3% | +66.1% | 3.03° | -16.1% | GDELT news, Wikipedia, YouTube | 414 | |
| AGI | -8.5% | -47.1% | +135.4% | 11.39° | -9.9% | GDELT news, Wikipedia, Hacker News, YouTube | 415 | |
| Sports Betting | +1.4% | +23.8% | +25.2% | 36.24° | -14.9% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Oil | +7.6% | +16.8% | +46.1% | 20.26° | +4.0% | GDELT news, Wikipedia, YouTube | 414 | |
| Peptides | -8.2% | -3.8% | +9.7% | 17.35° | -11.2% | GDELT news, Wikipedia, YouTube | 415 | |
| Tariffs | -0.7% | +9.8% | -11.2% | 81.22° | -0.3% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| CGM & Metabolic Biohacking | +2.0% | -9.2% | +41.2% | 3.34° | -0.3% | GDELT news, Wikipedia, YouTube | 414 | |
| UK Underground | -2.8% | +14.0% | +9.6% | 1.86° | +12.0% | Wikipedia, YouTube | 414 | |
| ChatGPT | +10.1% | +9.4% | -10.0% | 17.95° | -10.1% | GDELT news, Wikipedia, Hacker News, Wikipedia edits, YouTube | 415 | |
| Calisthenics | +2.0% | +0.1% | +0.6% | 2.21° | -15.1% | Wikipedia, YouTube | 414 | |
| Attention Economy | +1.0% | +1.9% | +15.8% | 91.49° | +9.1% | Wikipedia | 414 | |
| Pro Wrestling | -4.8% | -6.3% | +8.0% | 3.51° | +5.0% | GDELT news, Wikipedia, YouTube | 414 | |
| Coinbase | -1.1% | +21.9% | +32.4% | 63.10° | -3.8% | GDELT news, Wikipedia, YouTube | 415 | |
| Traditional Chinese Medicine | -6.7% | -11.2% | -24.6% | 1.58° | +23.3% | GDELT news, Wikipedia, YouTube | 414 | |
| Game Boy Modding Culture | +0.0% | +9.3% | -9.2% | 3.24° | -25.7% | Wikipedia, YouTube | 414 | |
| Analog | +5.9% | +9.0% | +0.0% | 3.23° | -10.0% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| GTA VI | -5.1% | -36.6% | +11.2% | 65.20° | -35.1% | GDELT news, Wikipedia, YouTube | 415 | |
| Bear Market | -5.6% | -18.8% | +25.1% | 3.27° | -3.5% | GDELT news, Wikipedia, YouTube | 414 | |
| Bully | -8.4% | +13.5% | +129.8% | 200.75° | +5.8% | GDELT news, Wikipedia, Wikipedia edits, YouTube | 414 | |
| K-Pop | +0.5% | +1.7% | +6.5% | 2.58° | -22.3% | GDELT news, Wikipedia, YouTube | 414 | |
| 90s Nostalgia | -3.4% | -5.7% | -11.3% | 29.34° | +5.9% | GDELT news, Wikipedia, YouTube | 415 | |
| Quantum Computing | -3.5% | +12.3% | +18.8% | 197.17° | -1.0% | GDELT news, Wikipedia, YouTube | 414 | |
| Wearables | +3.8% | +2.0% | -3.1% | 2.24° | +10.8% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Micro Dramas | +2.5% | -18.3% | -3.6% | 3.32° | +8.7% | GDELT news, Wikipedia, YouTube | 414 | |
| Pokémon | -1.7% | -8.8% | -26.2% | 16.15° | -1.7% | GDELT news, Wikipedia, Hacker News, YouTube | 415 | |
| Snap Specs | +2.2% | -3.4% | +27.8% | 21.91° | +15.8% | Wikipedia | 414 | |
| Zyns | +3.1% | -5.6% | +12.1% | 36.41° | +0.8% | GDELT news, Wikipedia, YouTube | 414 | |
| Silver Tsunami | +6.1% | +6.2% | -36.7% | 2.83° | +17.2% | GDELT news, Wikipedia | 414 | |
| Star Wars | -2.7% | -16.6% | -22.6% | 3.40° | +0.9% | GDELT news, Wikipedia, YouTube | 415 | |
| Private Credit | -0.5% | -11.6% | +26.0% | 1.56° | -24.5% | GDELT news, Wikipedia, YouTube | 415 | |
| IRL | -2.1% | -5.9% | +4.9% | 17.99° | -6.1% | GDELT news, Wikipedia, YouTube | 414 | |
| Afrobeats | +6.8% | +14.8% | -28.4% | 3.15° | -9.2% | GDELT news, Wikipedia, YouTube | 414 | |
| Blind Boxes | -0.1% | -21.9% | -4.7% | 14.37° | -4.8% | GDELT news, Wikipedia, Wikipedia edits, YouTube | 414 | |
| Aliens | -4.1% | -2.2% | +10.8% | 129.71° | -6.6% | GDELT news, Wikipedia, YouTube | 414 | |
| Substack | -4.8% | +8.7% | -6.8% | 6.59° | +2.4% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Eggs | -1.9% | -9.8% | -20.0% | 1.46° | +18.4% | GDELT news, Wikipedia, YouTube | 414 | |
| Vibe Coding | -5.3% | -25.0% | +15.0% | 13.67° | -6.4% | GDELT news, Wikipedia, Hacker News, YouTube | 415 | |
| Data Centers | -2.5% | +25.6% | +4.0% | 4.01° | -80.1% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Unemployment | -2.1% | -15.6% | -0.3% | 9.29° | -14.5% | GDELT news, Wikipedia, Hacker News, YouTube | 414 | |
| Cursor | +1.8% | -10.7% | -37.1% | 37.85° | -8.2% | Wikipedia | 410 | |
| Psilocybin | -3.9% | -17.7% | -13.1% | 3.23° | -23.5% | GDELT news, Wikipedia, YouTube | 414 | |
| Obsession | -6.6% | +78.6% | +536.5% | 68.47° | -14.1% | GDELT news, Wikipedia, Wikipedia edits, YouTube | 410 | |
| Slop | -8.3% | -33.3% | -73.6% | 0.96° | +1.7% | GDELT news, Wikipedia, Hacker News, Wikipedia edits, YouTube | 414 | |
| Looksmaxxing | -2.1% | +8.0% | -20.9% | 1.23° | -3.1% | GDELT news, Wikipedia, YouTube | 415 | |
| OpenClaw | -8.3% | -48.8% | +294.2% | 1.23° | -4.8% | GDELT news, Hacker News, YouTube | 410 | |
| Ebola | -2.7% | +0.7% | -7.4% | 119.75° | -0.1% | GDELT news, Wikipedia, YouTube | 414 | |
| Hantavirus | +11.2% | +12.2% | +49.1% | 106.29° | +0.1% | GDELT news, Wikipedia, Hacker News, YouTube | 414 |
Each source series is smoothed with a time-aware EMA, then divided by its own trailing 90-day median. The baseline is a median, not a mean — attention data is all spike and no symmetry, and one viral day under a mean-based baseline raises the bar enough to hide the next real move.
Sources combine by weight, renormalised over whichever actually reported, so a missing source shifts the mix rather than silently scoring zero. They combine by multiplying, not averaging — a weighted geometric mean. These are ratios, and the honest way to put ratios together is the one where a halving and a doubling cancel to 1.00 instead of averaging to 1.25.
The practical reason matters more: it forces a big reading to be corroborated. One source at 76× cannot outvote two sitting at 1.00, because the product still has those two in it. A number here is high because several places agree, or it is not high.
The window redraws the charts and the percentage beside each reading. That figure is the move between the first and last points actually plotted — it describes the line you are looking at, and nothing else.
Which is why it can sit a fraction of a point away from the fixed 7d column above. Those columns are exact-date lookups: 7d means the reading seven calendar days ago or nothing at all. The window figure starts wherever the topic's history actually starts inside the window, so on a market with a gap the two span slightly different intervals. The table is the reference; the panel describes its own chart.
Each panel's y-scale is refitted to the visible slice, which is why a chart can look dramatic at 7 days and flat at a year. The dashed line is 1.00 in every panel and at every window — that is the part which never rescales.
The index was never told about the calendar, and it found it anyway. The two highest days in Star Wars' 353-day record are 2.86 on 2026-05-05 and 2.83 on 2026-05-04 — May the 4th and the morning after. Step outside that week entirely and the next peak is 2.44 on 2026-05-25, the day A New Hope opened in 1977. Pokémon's February high is 2.90 on 2026-02-28 with 2.86 the day before — Pokémon Day and its morning after, against a February that otherwise never clears 1.87.
The lock is to the date give or take a day, and the day is the lagging half. The sources that confirm a move arrive behind the one that starts it — Wikipedia readership especially — so a combined peak sits on the event or just past it. What makes the rest of these numbers worth reading is that nothing anywhere in the pipeline knows what any of those days mean.
The index is a ratio to a topic's own normal. The price is in degrees, and each market's absolute level is its own history — ebola at 97° is not "worth more" than pokemon at 12°, any more than an index of 1.28 outranks one of 1.02 in popularity.
So the meaningful comparison is between changes, never levels — which is why the price sits in its own band and stays off the chart, and why its change follows the same window as the index beside it. Noise publishes a 24-hour change and nothing longer, so every other window is computed from our own snapshots, which covers the full 7 days. Where the record is shorter than the window, the cell reports the span it really covers and is labelled with it — a four-day move under a "1y" heading would be a quiet lie.
The Match order ranks markets by how far the price move and the index move agree over the window on screen. Change the window and the order changes with it: the question is what the two did over that stretch, not what the market is like in general.
The score is the smaller of the two moves, less the gap between them, in points —
min(|price|, |index|) − |price − index|. A market at +33.6% price
against +36.3% index scores 31; one at +52.7% against +77.2% scores
28; one at −1.6% against −3.8% scores −1.
Both halves carry weight. Closeness alone would put that last market first — a flawless agreement about nothing happening. Size alone would put +70% against +15% above +34% against +36%, which is not agreement, it is two things that both went up. Nothing has to be tuned, and a price that moved against its index scores negative and sinks, so the bottom of this order is the list of disagreements.
It says nothing about cause. Two numbers can agree because attention moved the price, because both answer to the same event, or because a month of price history is not yet enough to rule out a coincidence.
A market marked provisional has fewer than 120 days of history, so its "normal" is built from a short and often unsettled stretch. Cursor is the worked example: 78 days, nearly all of it decay from the spike when its Wikipedia article was created, which produces a truthful-looking −80% at 30 days that says more about the article's age than about attention.
The reading is still shown, because waiting for a full window would mean months of blank panels. It is marked because a three-week baseline and a settled year are not the same claim.
Instagram and TikTok have no usable free API, so topics that live there —
looksmaxxing above all — are systematically under-read. That is a missing
input, not a tuning problem.
90s-nostalgia is a diffuse mood rather than an entity and has no clean query;
it is kept as an honest floor for what this method can do.