Opportunities › Quantitative valuation metrics for trading and research › Proposed app
Peerband
Valuation indicators from filings and prices, tested inside each industry
- Score
- 41
- confidence 38
- Evidence
- 3
- items on the page
- Rivals
- 3
- named in sources
- First version
- 45 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 1982
- Mature market · AI estimate
ScreensConcept
Desktop app: Financial analysis, backtesting rules, and drilling into filing details require dense dashboards, multiple data views, and sustained analytical work at a computer. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Valuation check
Cheaper than peers23rd pct
About this appAI proposal
Peerband turns company filings and market prices into valuation indicators, then judges each one against companies in the same industry instead of the whole market. Ask in plain words, in the app or from your own AI agent through MCP, and get the number, its peer range and the filing it came from.
It is built for quantitative traders, equity researchers and small research teams who now assemble this data by hand in spreadsheets or scripts. Pick an indicator, set an industry-relative rule, and run a backtest on the same page.
Every figure links back to its source filing or price date, so you can check it before you act on it. Peerband is a research tool, not investment advice.
- Tagline
- Know if it is cheap, compared with its own industry.
- Voice
- PrecisePlainSober
- Why this name
- A band is the range peers occupy; Peerband places each security inside it. Two plain words, easy to say.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Industry-relative indicators
Each valuation indicator is ranked against peers in its own industry, so a bank is never compared with a software firm.
No member yet
MCP server for agents
Connect Claude or any MCP-capable agent and ask for valuation insight in conversation. Answers return as structured data.
No member yet
Filing-to-number trace
Click any figure to see the filing line and price date behind it. No black-box scores.
No member yet
Backtest by rule
Define a rule such as bottom-quartile peer rank, pick a period and rebalance, and compare returns with a benchmark.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#14231FDeep Ink · primary#F6F3ECPaper · surface#1D2926Charcoal · text#E0902BAmber · accent#4F7A5EMoss · data#B5533CClay · data negative
Typography
Aa
Peerband
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
PricingAI proposal
The material gives no competitor prices. These tiers are a starting point to test, split by securities covered and backtest volume as the opportunity suggests.
Free
Free
- 20 securities
- Daily data
- Peer rank and source trace
- 5 backtests a month
Researcher
$49 a month
- 500 securities
- MCP server access
- Unlimited backtests
- Percentile alerts
- CSV and JSON export
Team
$199 a month
- Full coverage
- 5 seats
- Shared notes and watchlists
- API access
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Shared outputs. Users send read-only links to a valuation check or backtest to colleagues and clients. The page shows the peer range, sources and the Peerband name.
- Do they become customers?
- Recipients are often analysts who could sign up, but a one-time view may not convert. Test whether shared links produce free sign-ups and then paid seats.
- First customers
- Independent quant traders and small research teams of 1 to 5 people who already use AI agents and script their own valuation screens.
- Where to reach them
- GitHub and MCP directories: Publish a free MCP server listing and a sample repo for developers seeking valuation tools.
- Quant communities: Share worked backtest examples in quant forums and research newsletters.
- First milestone
- Ten paying researchers on the 49 dollar tier within 90 days, each running backtests weekly.
Why people already pay for this
- VerifiedGitHub repository gained 311 stars in 41 days
- Public claimAn MCP server that turns filings and prices into valuation indicators, and tests each one inside its own industry.
- Public claimThe tool is designed for quantitative research, backtesting, and alpha research workflows.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Market and filings dataLicensed price feed plus public filings sourceValuation needs prices and filings; redistribution rights must be cleared.
- This app · Compute jobsBackground worker and columnar storeFiling parsing and backtests are heavy and run outside web requests.
RisksAI inference
- DataMarket price data licences often restrict redistribution; cost and terms could limit a low-priced tier.
- TechnicalParsing filings into comparable figures is hard, and industry classification choices change peer ranks.
- CommercialInstitutional users may stay with their existing terminals; the open-source MCP tool in the evidence is a free alternative.
- RegulatoryOutput could be read as investment advice; disclaimers and careful wording are needed.
- AIAgents may misquote results; structured answers with source links are needed to limit errors.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.