Equity screening is where quantitative discipline meets fundamental judgment. The challenge is not finding a filter) it is combining dozens of metrics without building a custom database that goes stale every earnings season. Dividend yield, short interest, revenue growth, and valuation multiples all live in different silos unless your platform normalizes them into one queryable catalog.
Vantafin does not offer options chains, greeks, or unusual options flow data. What we provide is a stock screener with 80+ metrics accessible through the screener app, GET /screener and GET /screener/fields over REST, and screen_stocks via the MCP server. This post shows how to build multi-metric screens that surface names matching your thesis without options data you do not have.
Build multi-metric filters
Start with GET /screener/fields to discover the full metric catalog) dividends, valuation, profitability, leverage, short interest, momentum, and more. Combine filters that match your process: a value screen might require low EV/EBITDA, positive free cash flow, and dividend growth; a momentum screen might layer price performance with volume and market cap floors.
Results appear in the app and via the REST API. Export tickers to watchlists and set email alerts on price thresholds for names that pass your screen. Alerting is where screening earns its keep. A name that enters your filter universe deserves a notification, not a tab you check when the day is over.
Start conservative on filter count and loosen until result sets are actionable. Over-constrained screens that return three names teach you little; under-constrained screens that return three hundred are just the full market.
Integrate with equity work
When a name passes your screen, open the company page and check the calendar for earnings dates. A cheap valuation screen hit heading into earnings week means something different than the same hit in a quiet month. Cross-check short interest and pre-earnings news context so screen results sit inside a thesis) not as a thesis.
Write one sentence in your coverage note when a screened name enters the list: which metrics triggered, what would remove it, and whether the catalyst calendar supports or conflicts with the setup. That discipline prevents retroactive storytelling when the stock moves.
Power users chain screen_stocks with other MCP tools for morning briefings: "screen semiconductor names with dividend yield above 2% and short interest below 10% of float." The agent returns candidates; you decide which three merit a call to the desk.
Availability
Live on paid plans (see pricing. Methodology and field definitions in docs. Not investment advice; a research tool for your own process.
We expand the metric catalog as new datasets ship. The screener improves when users report fields they need for workflows we have not documented yet. Tell us what filter would save your desk an hour each week.
Screening for conviction without options chains
Equity desks often want to know which names show unusual momentum, volume, or valuation dislocations) without maintaining a separate options data feed. Vantafin's screener exposes the full metric set: valuation, financials, margins, growth, technicals, and dividends, with comparison operators you can combine into multi-factor screens. The same query engine powers screen_stocks in the MCP server and the public REST screener route.
Start from relative ranks rather than absolute thresholds. Volume z-scores, price change over five and twenty sessions, and short interest relative to sector median surface names that "feel" active before you read a headline. Export finalists to watchlists and pull bulk quote snapshots for a consistent mark before the desk meeting.
Anchor every screen result to the company profile, recent news, and the calendar row for the next earnings or split. A momentum print without catalyst context is noise that wastes reaction time; the same print into a scheduled event week deserves a closer read.
Follow-through on price and news
After a name ranks high on momentum and volume, subscribe to LM.{ticker} for per-minute quotes and N.{ticker} for headlines on the same WebSocket connection. Cash markets confirm whether a screen signal expressed broad participation or a one-day spike. Historical research improves when you store screen outputs with timestamps and study which factor combinations preceded next-day drift versus fade.
Route top-decile screen results to email price and news alerts with thresholds you tune to your universe. Recipients should open primary sources (profile, news, filings) before acting on a single column value. Batch screen refreshes via REST off-peak and cache results locally rather than hitting live endpoints on every page load.
Pair screener output with short interest squeeze watch workflows when crowded names also show elevated momentum. The combination describes positioning and price action together without importing derivatives data you do not need for the thesis.
Research hygiene and desk norms
Screens excel at prioritization, not at final investment decisions. Treat results as a ranked queue for human review alongside management guidance and material 8-K events on the same symbols. When two names in the same sector rank highly, read whether the signal expresses single-name idiosyncrasy or a thematic move.
Archive screen outputs with subsequent returns to calibrate which thresholds justified desk time in your history. Thresholds that feel conservative in backtest often prove noisy in live markets unless you adjust for earnings seasons and index rebalance weeks. Confirm entitlements on pricing before automating wide-universe screens each morning.