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Tickerz
Real-time market attention, measured with receipts.
Tickerz tracks when crypto assets and a curated set of US equities start trading differently from their own recent baseline. It scores how unusual that activity is and keeps a permanent public record of what happened next. The methodology is public, the JSON API is free and open, and this launch marks day one of the live record.
Every market site shows you prices, candles, market caps, and volume.
What I wanted to know was something different: when does an asset start behaving unusually relative to itself?
That became Tickerz.
Sigma-1 produces Heat™, a 0 to 100 score based on how abnormal an asset’s recent price and volume behavior is compared with its own trailing baseline.
It does not compare Bitcoin to Solana or NVIDIA to Tesla. Each asset is measured against its own history. So a normally quiet asset suddenly moving can score hotter than a large asset having a fairly normal day.
When Heat reaches 70, Tickerz opens an event and freezes the price. Then it records what happened +24h, +7d, and +30d later.
Wins and losses are treated exactly the same. The record stays there.
That part matters to me. A lot of market products are very good at showing what is interesting right now, but once the list changes, there is no real way to go back and judge whether the signal meant anything.
Tickerz keeps the receipts.
I also chose not to score assets until there is enough baseline data to make the comparison meaningful. Sigma-1 requires at least 14 days of history before an asset gets a Heat score.
At launch, Tickerz covers the top 100 crypto assets plus a curated group of major US equities.
The methodology is public, the Sandbox lets you run the model over historical data, and the Board is available through a free JSON API with no key or signup.
And the name is pretty literal: z-scores, per ticker.
Tickerz is not trying to predict the market or tell anyone what to buy. Heat measures attention, not merit.
If you check it out, I’d especially like feedback on the methodology, the receipts, and what you think Tickerz should measure next.
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About Tickerz on Product Hunt
“Real-time market attention, measured with receipts.”
Tickerz was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #137 on the daily leaderboard. Tickerz tracks when crypto assets and a curated set of US equities start trading differently from their own recent baseline. It scores how unusual that activity is and keeps a permanent public record of what happened next. The methodology is public, the JSON API is free and open, and this launch marks day one of the live record.
Tickerz was featured in Fintech (47.5k followers), Investing (26.8k followers) and Data & Analytics (5.8k followers) on Product Hunt. Together, these topics include over 31.5k products, making this a competitive space to launch in.
Who hunted Tickerz?
Tickerz was hunted by Sami Kirberg. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Tickerz stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sami Kirberg