Screeners – Finviz, TradingView, and Koyfin in Practice

Lesson 5: Screeners – Finviz, TradingView, and Koyfin in Practice

A screener does not find “opportunities”. It filters noise down to a measurable list of candidates that you then analyse by hand. 90% of advanced stock picking is rejecting companies, not choosing them. A well-built screener is a risk-elimination system, not a ranking of returns.

Lesson goal

You will learn to build multi-stage screeners in Finviz and TradingView, define Warsaw Stock Exchange (GPW) and US universes, avoid data traps, and build a watchlist with measurable inclusion and exclusion criteria instead of subjective opinions.

1. Screener architecture – universe, hard filters, soft filters

Rule: safety and quality first, valuation second. The reverse order (low P/E first) floods you with companies in trouble.

2. Finviz – fast filtering of the USA

Finviz Screener (finviz.com/screener) has the filter groups: Descriptive, Fundamental, Technical, All.

A baseline configuration for quality training:

Descriptive: Market Cap +300M to Large, Country USA, Exchange NYSE/NASDAQ
Fundamental: P/E Profit >0, Forward P/E Profit >0, Debt/Eq <0.8, ROE >15%, ROIC >10%, Sales growth past 5Y >5%
Technical: Price above SMA200, Average Volume Over 500K, RSI not Overbought 70

Data checklist:

Export: Finviz Elite allows a CSV export. Without Elite, copy the ticker list and paste it into a spreadsheet for further analysis in Koyfin/TradingView.

3. TradingView Screener – GPW and USA together

TradingView -> Stock Screener. The key differences versus Finviz:

• You can filter by GPW: Exchange = GPW, Market = Poland.
• Filters: Market Cap, Performance (YTD, 3M), Valuation (P/E, EV/EBITDA, P/S, P/B, Dividend Yield), Financials (Debt to Equity, Current Ratio, ROA, ROE, Net Margin, Gross Margin), Technical (MA, RSI, ATR).
• You can create a custom screen with a formula:

Example of a custom filter in TradingView (Pine logic as the condition):
Gross Margin > 40 and ROIC > 12 and Net Debt/EBITDA < 2.5 and FCF Margin > 5 and Price > SMA200

GPW mapping table:

GPW workflow:

1. Universe: GPW, Market Cap >100M PLN
2. Liquidity: Avg Volume 30D * price > 200k PLN
3. Quality: ROE 3Y avg >10%, Debt/Equity <1, Current Ratio >1.2
4. Valuation: EV/EBITDA < 12, P/E < 20
5. Export the list to a TradingView watchlist: WIG_quality_25

4. Combining screeners – a system of elimination

Do not look for one perfect screener. Build a funnel:

Step 1: Finviz/TradingView 300 companies -> Step 2: Koyfin import + add ROIC 5Y, FCF conversion, SBC -> 80 companies
-> Step 3: Manual review of 10-K / GPW reports: leverage, goodwill, RPT -> 20 companies -> Step 4: Sector-relative valuation
-> 8 companies on the deep watchlist

Measuring screener effectiveness:

• Hit rate: what % of the screener passes through to step 3?
• False positives: how many companies with a low P/E had net debt/EBITDA >4?
• Stability: run the screener historically quarter by quarter back in time – were the results similar?

5. Data traps in screeners

Screener quality formula:
Screener Score = (ROIC - WACC) * FCF conversion * (1 / (1 + Net debt/EBITDA))
The higher it is, the more quality per unit of balance-sheet risk – but only calculate it within a sector

When the plan says “do not trade”

• You do not trade a company just because it passed the screener – the screener is a list to analyse, not an entry signal.
• You do not trade a company that passes the valuation filters but fails the safety filters (debt, liquidity, CFO).
• You do not trade on screener data older than 5 business days after the quarterly results are published – the data is stale.
• You do not trade when the screener shows P/E <5 and dividend yield >10% with free float <10% – that is a GPW liquidity trap and the spread will eat your profit.
• You do not trade a universe of <30 companies after filtering – the sample is too small and the statistical error is large.
• You do not trade a US list if you have not checked whether the ticker is an ADR, REIT, BDC, or MLP – they have different accounting and taxes.

Mistakes that cost the most

1. Sorting from the lowest P/E. It returns companies in restructuring, after write-downs, with negative equity, or with a one-off profit. Wasted time plus a selection error.
2. No balance-sheet filters. A “growth” screener (Sales growth >20%) without a net debt/EBITDA filter returns companies growing on debt.
3. Mixing standards. Comparing the ROE of a bank with the ROE of a software company – two different businesses, two different risks.
4. Ignoring SBC. US technology companies have 5-15% of revenue in SBC – a P/E screener does not show that. You have to add an adjustment in Koyfin.
5. No screener journal. You run different filters every day without recording them – you do not know what works. Measure and save the screener version.

Measurable exercise

1. Build 2 screeners and save them as templates:
   • “GPW Quality”: Exchange GPW, Market Cap >100M PLN, Debt/Equity <0.8, Current Ratio >1.3, ROE >12%, ROIC >10%, EV/EBITDA <12, Average Volume 30D >150k PLN, Price > SMA200, FCF >0.
   • “USA Quality Compounders”: Market Cap >1B, ROE >15%, ROIC >12%, Gross Margin >45%, Net Debt/EBITDA <2, FCF Margin >8%, Sales 5Y CAGR >5%, Price vs SMA200 >0%.
2. Run both and export 30 tickers each.
3. For each one calculate: what % have a dividend FCF pay-out above 100% (if it pays one), and how many have short interest >10% (USA).
4. Pick 3 from each with the lowest net debt/EBITDA and the highest CFO/EBIT conversion – add them to the deep watchlist.
5. Save the filter version with the date – come back in a month and compare the rotation of the list (how many companies dropped out and why).

Time: 60 minutes to build + 60 minutes to verify 6 companies. Output: 2 saved screeners + 1 watchlist of 6 companies + a change log.

Check yourself

1. Why is a “low P/E” filter without a net debt/EBITDA filter dangerous?
2. How do you tell a company with negative EV from a cheap company in a screener?
3. What does the “Price above SMA200” filter mean and when would you turn it off?
4. Why do you have to check whether a ticker in Finviz is an ADR if you are building a US screener?
5. How will you measure the stability of your screener over time?

Frequently asked questions

Finviz or TradingView – which is better for GPW? TradingView has full GPW data, Finviz does not. For the USA both are good, but TradingView lets you combine GPW and the USA on one screen. Finviz is faster for an initial filter of the USA.

Are free screeners enough? To start, yes, but TTM data can lag by a quarter, and ROIC/FCF filters are often calculated differently. Koyfin (partly paid) and TIKR give more consistent definitions. Measure the definition gap on a single company.

How often should you run a screener? Weekly after the earnings season (February, May, August, November) and monthly outside it. Running it daily generates noise.

Does a screener account for splits and dividends? Yes, price filters are adjusted, but check historical DPS in the reports, because aggregators mix regular dividends with special ones.

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