Stock Screening Strategy: How to Build One That Works

A stock screening strategy is a written set of rules that narrows thousands of listed companies down to a short list you can actually research. You start with a goal (value, quality, dividends, growth or momentum), choose a handful of filters that match it, combine them with clear logic, and then review every result by hand. The screen produces candidates, not conclusions. This guide shows how to build that process step by step, with the criteria each style tends to use and the mistakes that make a screen misleading.

TL;DR

• Define your goal first. The goal decides the criteria, not the other way around.
• Use a small set of filters from different categories (size, valuation, quality, trend) instead of one number or thirty.
• Know how your tool combines filters: AND narrows the list, OR widens it.
• Treat screen results as a research queue. Check the chart, the financials and the risks before acting.
• Past screen results describe history, not current conditions. Re-run and re-check regularly.

Table of Contents

• What a stock screening strategy actually is
• How to screen stocks, step by step
• Stock selection criteria by strategy
• Three sample screen designs
• Common screening mistakes
• How to validate a screen and account for its limits
• Turning screen results into an organized research workflow
• Our perspective
• Where LevelScan fits
• FAQ
• Sources

What a stock screening strategy actually is

Stock screening means filtering a database of stocks against rules you set. The rules can be fundamental (how a company earns and what it is worth), technical (how the price has behaved) or a mix of both. The output is a list of tickers that pass every rule.

A strategy is more than a pile of filters. It answers four questions in writing:

1. What am I looking for? (An undervalued company, a steady dividend payer, a fast grower, a stock in an uptrend.)
2. Which measurable criteria stand in for that idea?
3. How do those criteria combine?
4. What happens after a stock passes? (Who reviews it, against what checklist, and how often?)

Without the fourth question, a screen is just a list generator. With it, screening becomes the first stage of a repeatable research routine.

How to screen stocks, step by step

1. Start with a goal and a time horizon

A long-term investor looking for durable businesses and a swing trader looking for stocks near a technical level need different screens. Write one sentence: “I want profitable mid-sized companies trading below their historical valuation,” or “I want large, liquid stocks in an uptrend that are pulling back.” Every filter you add should serve that sentence. If a filter does not, delete it.

2. Pick the universe

Decide what you are screening before deciding how. Typical universe filters are:

• Market capitalization: large, mid or small companies behave differently. Small caps tend to be more volatile and less liquid.
• Sector or industry: comparing a bank’s debt ratio with a software company’s is meaningless, so screen within sectors where ratios are not comparable across industries.
• Average daily volume: a minimum trading volume keeps you away from stocks that are hard to enter or exit.
• Exchange and security type: U.S.-listed common stocks only, for example, which removes funds and other instruments from the list.

3. Choose a few criteria that match the goal

This is the core of the strategy. The next section lists common choices by style. Keep the list short: a small number of well-chosen criteria that together describe your opportunity set works better than a single-factor screen (only P/E) or an overloaded one with dozens of rules, a point Pomegra’s screening guide also makes.

4. Set thresholds and decide how filters combine

A threshold is the cutoff, such as “return on equity above X.” Choose it by looking at the distribution of your universe, not by guessing. If your screen returns nothing, loosen the strictest rule. If it returns hundreds, tighten or add a category you skipped.

Then decide the logic. Most screeners treat multiple filters as AND by default, meaning a stock must pass all of them. The documentation for the tvscreener filters describes this exactly: separate conditions are combined with AND unless you explicitly use OR. That has a practical consequence for your design:

• AND is for requirements. “Market cap above my minimum AND positive earnings AND price above its 200-day average.”
• OR is for alternatives. “Dividend yield above my target OR dividend growth above my target.”
• Mixing them lets you express rules like “in sector A or sector B, and also liquid and profitable.” Group the OR conditions so they apply only where you intend.

If you are unsure what your tool does, run a small test with two filters and check that the result count behaves the way you expect before building the full screen.

5. Review the list manually

The screen ends where research begins. For each name, open the chart, read the latest filings, check what drove the numbers and note the nearest risks. A low P/E might signal a bargain or a business in decline. A high growth rate might come from a one-time event. Only a human review separates those cases. Our walkthrough on researching individual stocks lays out a process for this stage.

6. Record, repeat and refine

Save the screen, the date you ran it and what you did with each result. Review the notes after a few weeks: which filters produced names you kept, and which produced noise? Adjust one variable at a time so you know what changed the outcome.

Stock selection criteria by strategy

The table summarizes the measures most commonly used for each style. These are illustrative categories, not recommendations, and the right thresholds depend on your universe and goals.

The fundamental rows follow the standard breakdown described in Pomegra’s guide to top-down and bottom-up screening. Here is how to think about each one.

Value screens

Value screens hunt for stocks the market may be pricing cheaply. The risk is the “value trap,” a stock that is cheap because its business is deteriorating. Pair a valuation filter with a quality filter (positive earnings, manageable debt) to reduce that risk.

Quality screens

Quality screens favor companies that turn capital into profit consistently. Because ratios like leverage differ widely by industry, compare companies within the same sector rather than against the whole market.

Growth screens

Growth screens focus on the direction of revenue, earnings or cash flow. Look at more than one year of results so a single strong quarter does not dominate the list, and check whether growth is paired with profitability.

Dividend screens

A very high yield can be a warning sign if the price has fallen sharply or the payout exceeds what the company earns. Filtering by payout ratio or dividend growth helps separate sustainable income from stressed income.

Momentum and technical screens

Technical screens work from price and volume rather than financial statements. Common building blocks include price relative to a moving average, distance from a 52-week high or low, volume compared with its average, and volatility. Technical analysts also mark support (a price area where buying has previously emerged), resistance (an area where selling has previously emerged) and an invalidation level, the price at which the original setup no longer holds. If you combine technical signals, our piece on swing trade indicators explains how to avoid stacking indicators that measure the same thing.

Top-down screens: sectors first

Some investors begin with the sector rather than the company, restricting the universe to areas showing relative strength and then applying company-level filters. That approach is covered in our guide to sector rotation strategy.

Three sample screen designs

These examples show structure only. The thresholds are left for you to set from your own data, since we do not publish market figures here.

A quality-at-a-reasonable-price screen

• Universe: U.S. common stocks above your minimum market cap and volume.
• AND return on equity above your threshold.
• AND debt level below your threshold for the sector.
• AND P/E below the sector median.
• Review: read the last two annual reports, check what drives margins.

A dividend sustainability screen

• Universe: large and mid-cap stocks.
• AND yield above your minimum.
• AND payout ratio below your ceiling.
• AND (dividend growth above your threshold OR a long record of uninterrupted payments).
• Review: compare payouts against free cash flow, not just earnings.

A trend-pullback screen

• Universe: liquid stocks in the sectors you follow.
• AND price above its long-term moving average.
• AND price within a set percentage of a nearby support area.
• AND volume above its average on recent up days.
• Review: define the invalidation level before anything else, and note how far the price sits from it.

Notice the pattern in each: a universe filter, two or three criteria from different categories, and a manual review stage with its own checklist.

Common screening mistakes

Using a single metric. A screen that sorts only by P/E, yield or recent performance is easy to build and easy to fool. Combine at least a valuation, quality or trend measure with a liquidity filter.

Over-fitting. Adding rule after rule until a past winner appears on the list produces a screen tuned to history. The more conditions you tune against one period, the less likely the pattern is to repeat.

Ignoring sector differences. Debt, margins and valuation multiples have different normal ranges in different industries. Apply sector filters or compare within groups.

Stale data. Many screeners update financial figures on a delay, and prices change constantly. A list generated last week may no longer describe today’s market. Always note the date of the data.

Skipping the review. Screen output is a starting queue. It does not tell you why a number looks the way it does.

How to validate a screen and account for its limits

If you test your screen on past data, be careful about what that test can tell you. Foxholm Financial’s March 2026 article on backtesting pitfalls explains that bias-free backtesting is an ideal rather than a reality, and that information you could not have known at the time (revised economic data, restated earnings, retroactively adjusted index membership) can sneak into a test and flatter the results.

The same source suggests practices that apply to a personal screening process too:

• Use data that includes companies that were delisted, not only today’s survivors, so the test is not limited to winners.
• Use the date information was actually published, such as the filing date, rather than the end of the fiscal period.
• Hold out a period of data that you did not use while designing the rules.
• Include realistic trading costs.
• Test across different periods, including rising and falling markets.

The article also notes that changes in market regime can undermine any backtest, because history cannot predict structural breaks. In practice, that means two things for your routine. First, treat a historical test as a sanity check on your logic, not as a forecast. Second, keep separating what happened in the past from what the market looks like now: re-run the screen on current data, and look at current price action, news and earnings dates before drawing conclusions.

Turning screen results into an organized research workflow

A screen gives you ten or forty names. The next problem is keeping track of them. A simple dashboard or spreadsheet with a row for each stock helps: ticker, why it passed, key levels, risks, date reviewed and a status. Statuses matter more than they seem, because they stop you from re-researching the same names and show which ones need attention. Our guide to building a stock analysis dashboard covers what to include.

It also helps to define in advance what would make a setup stop being interesting. A price that falls through a key level is a reason to reassess, and our article on reversal risk explains why having that level in mind beforehand keeps decisions calmer.

Our perspective

Most screening problems are organization problems. Investors build a filter, get a list, and then lose the thread: why did this stock qualify, where are its important price levels, has anything changed since last week?

That is the problem we built LevelScan to address. We provide a curated watchlist, and each stock has its own research page with support, resistance and invalidation levels. Every name carries one of four standard status labels (Watching, In Zone, Moved or Invalidated), and the dashboard lets you filter by market cap, sector and volatility category. We update the research weekly.

Our view is that consistent structure is what makes screening useful. When every stock is described with the same reference points, you can compare quickly and spend your time on judgment rather than formatting. We design the platform to organize research, not to give personalized advice or promise results, and the final decision always stays with you.

LevelScan Editorial Team

Where LevelScan fits

If you would rather not build and maintain every layer of your research list yourself, LevelScan gives you a curated watchlist with standardized technical levels and weekly updates in one dashboard. You can see how LevelScan works or look at the Founding Membership page for current access details. It is a research organization tool, not a brokerage and not personalized investment advice.

You can also read more about the platform at LevelScan, or browse our technical analysis education for related guides.

FAQ

How many criteria should a stock screen have?

Use enough to describe your goal and no more. Pomegra’s guide recommends a modest set rather than a single metric or dozens of rules. A practical approach is one or two universe filters, then a few criteria drawn from different categories such as valuation, quality and trend.

What is the difference between a stock screen and a stock recommendation?

A screen is a filter: it lists stocks that meet rules you chose. It does not judge whether any of them is a good investment for you. Recommendations take your finances and risk tolerance into account. For personal advice, speak with a licensed financial professional.

How often should I re-run my screen?

That depends on your horizon. Long-term fundamental screens can be reviewed monthly or quarterly, after earnings updates. Technical screens go stale faster, so traders often re-run them weekly or more often. Whatever the schedule, record the date and check current conditions before acting.

Can I rely on a backtest to prove my screen works?

A backtest is a useful check on your logic, but it has well-known limits, including survivorship bias, look-ahead bias and regime changes, as Foxholm’s backtesting guide describes. Treat results as one input and keep testing across different market periods.

Sources

• Filters - tvscreener documentation
• Stock screening: top-down meets bottom-up | Pomegra
• Backtesting Pitfalls | Foxholm Financial

Recommended

• How to Research Individual Stocks: A Step-by-Step Process
• Stock Analysis Dashboard: What to Include and How to Build One
• Swing Trade Indicators: What to Use and How to Combine Them
• Technical Analysis Basics: A Plain-English Guide for Beginners

This article is provided for general educational and informational purposes only. It does not constitute personalized investment advice or a recommendation to buy or sell any security. Market information may change, and readers should independently verify all data and evaluate their own investment decisions. Past performance does not guarantee future results.