Best European stock screener: 2026 comparison
A stock screener filters hundreds of stocks in seconds according to your criteria. But not all screeners are equal — coverage, data quality and the relevance of the filters vary considerably. This guide compares the main tools and helps you choose the one best suited to your strategy.
What is a stock screener?
A stock screener (or stock filter) is a tool that lets you query a database of stocks using quantitative criteria. You set thresholds (P/E < 15, revenue growth > 10%, net debt/EBITDA < 2x…) and the screener returns the list of stocks that tick all your criteria simultaneously.
The value is speed: instead of analysing 300 stocks one by one, you narrow the universe to 15–20 candidates worth a deeper look. The screener does not replace judgement — it directs it.
Fundamental principle: a screener is a pre-selection tool, not a final-selection tool. A stock that passes all your filters is not automatically a good investment — it is simply a candidate worth taking an interest in.
The two main families of screeners
| Type | Criteria used | Suited to | Limitation |
|---|---|---|---|
| Fundamental screener | P/E, EV/EBITDA, FCF, revenue growth, net debt, ROE… | Long-term, value, growth investors | Data sometimes lagging (quarterly/annual) |
| Technical screener | RSI, moving averages, volumes, breakouts, Golden Cross… | Traders, swing traders, momentum | Says nothing about company quality |
| Composite screener | A score combining fundamentals + momentum + risk | Investors who combine both approaches | Requires understanding the weighting |
Comparison of the best screeners in 2026
Overview — all markets
| Tool | European small-cap coverage | Local GAAP data | Score / ML | Track record | Price |
|---|---|---|---|---|---|
| TradingView | Partial | ✗ Gaps | ✗ | ✗ | Free → €60/month |
| Zonebourse | ✓ Euronext + Growth | Partial | ✗ | ✗ | Free → €30/month |
| Boursorama / ABC Bourse | Basic large caps | ✗ | ✗ | ✗ | Free |
| Finviz | ✗ US only | ✗ | ✗ | ✗ | Free → $25/month |
| Koyfin / Tikr | Partial | ✗ Gaps | ✗ | ✗ | Free → €50/month |
| Screener Small Caps | ✓ 800+ stocks | ✓ IFRS + local GAAP | ✓ XGBoost | ✓ Public | Free → €19–39/month |
For US stocks
| Tool | Strengths | Weaknesses | Price |
|---|---|---|---|
| Finviz | Very complete, fast, heatmap visualisation, many technical filters | Mainly the US market, delayed data on the free tier | Free / Elite ~$299/year |
| Simply Wall St | Visual interface, accessible to beginners, narrative analysis | Sometimes approximate data, paid for the essentials | ~$10–25/month |
| Tikr Terminal | Very complete historical financial data, international | Learning curve, analyst-oriented | Free limited / Pro ~$29/month |
For European stocks
| Tool | European coverage | Strengths | Weaknesses |
|---|---|---|---|
| Boursorama / Zonebourse | Good coverage of large-cap indices | Free, Euronext data, integrated news | Limited filters, no composite score, incomplete small-cap data |
| ABC Bourse screener | Medium (large caps + some Growth) | Free, usable basic criteria | Very few filters, no complete Euronext Growth data |
| Screener Small Caps | 800+ Euronext Growth & Access stocks | ML score 0–100, regulator data integrated, daily updates, BUY/HOLD/SELL signal, tax-wrapper eligibility | Specialised in European small caps only |
The structural problem of generalist screeners on European small caps: a significant share of Euronext Growth stocks report under local GAAP (rather than IFRS). International aggregators — Refinitiv, FactSet — structurally struggle to process these accounts correctly, with delays of 3 to 6 months on fundamentals. On this segment, a tool fed directly by the national regulators' data (such as the AMF in France) makes a significant difference.
Which screener for your strategy?
Answer 3 questions to find the tool that fits your approach:
The criteria of a good fundamental screener
Here are the essential fundamental filters to check in any screener you are considering:
| Criterion | Why it matters | Indicative small-cap threshold |
|---|---|---|
| EV/EBITDA | Measures valuation independently of the financial structure | < 8× for value, < 12× reasonable |
| Revenue growth (3–5 year CAGR) | The main predictive feature of the ML model | > 10% preferable |
| Net debt / EBITDA | Measures the sustainability of debt | < 2× for safety, < 3× tolerable |
| Free Cash Flow | Measures real value creation (vs accounting profit) | Positive FCF for 2 consecutive years minimum |
| ROE / ROCE | Capital efficiency — a sign of a potential moat | > 12% for ROE |
| Momentum (6–12 month performance) | The momentum effect is documented on small caps | Positive or > the benchmark index |
Screeners and tax-advantaged accounts: an often-forgotten criterion
For European investors, eligibility for a tax-advantaged equity account is a decisive filter — gains within such a wrapper are often exempt from income tax after a holding period. Most international screeners do not include this criterion. It is nonetheless decisive: between an identical stock held in a tax-advantaged account and in an ordinary securities account, the net performance can differ by several points a year over the long run.
Eligibility example (France, PEA-PME): eligible companies employ fewer than 5,000 people and have annual revenue not exceeding €1.5 billion or a balance-sheet total of €2 billion. Almost all Euronext Growth stocks are PEA-PME eligible. Other European countries have their own equivalent wrappers.
Why an ML screener is different
Traditional screeners apply fixed thresholds chosen by the user (P/E < 15, debt < 2x…). An ML screener like Screener Small Caps takes a different approach: the XGBoost model was trained on the history of outperformance of Euronext Growth stocks to identify which combinations of features best predict 12-month outperformance versus the benchmark.
The result: the 0–100 composite score reflects not your assumptions, but what historical data shows to be genuinely predictive on this segment. The most important features (5-year revenue CAGR, EV/EBITDA, 3-month volatility) were selected by the model itself. The track record is public and verifiable: all predictions are logged before market close, results net of costs.