Investors love a simple story, but markets usually reward a balanced one. Value works over long horizons, but cheap can stay cheap. Momentum captures trend persistence, but it can overpay at the worst possible time. Put them together and you get a more resilient process that avoids the ugliest value traps while steering clear of froth that tends to deflate. This is the practical guide I wish I had when I started building a stock screener for value plus momentum, including how to set thresholds, what to ignore, and where the landmines hide.
Why blend value and momentum
The academic rationale is well known. Value and momentum are distinct factors that have shown historical outperformance across markets and eras, and their returns have low correlation. You can read papers for the formal proofs. The practitioner’s case is simpler: value finds mispricing that the market has misjudged, momentum filters for stocks with actual buying pressure and improving perception. When the two agree, you have a company that is both attractively priced and receiving fresh demand. That pairing won’t make every pick correct, but it shifts probabilities meaningfully.
I have seen two patterns repeat in portfolios that rely on only one factor. A pure value book tends to fill with asset-heavy, structurally challenged businesses. They look cheap on price to book and EV/EBITDA yet never re-rate. A pure momentum book often buys late in the move, especially around story-driven https://tradeideascoupon.com/ inflections. When the music stops, the drawdowns are sharp. Combining them helps you pay a fair price for strength, not a fantasy price for sizzle or a discount for decay.
Start with the investable universe
Before you play with factor knobs in a stock screener, pick the pool you want to fish in. Decisions here do more for risk and returns than most realize. Liquidity screens keep you from getting trapped in microcaps. Basic quality filters reduce false positives. The best stocks to buy now are rarely the ones you cannot exit during stress.
I like to set a float-adjusted market cap floor, often 1 to 2 billion dollars for a US universe, lower for markets where mid caps dominate. Average daily dollar volume matters more than share volume. A common cutoff is 5 to 10 million dollars traded per day, though smaller investors can go lower. Exclude ADRs with limited liquidity, and if you trade outside the US, account for different accounting regimes and sector concentrations that can skew factor metrics.
It also helps to apply a sanity check on accounting cleanliness. You can use a light version of the Piotroski F-score or flag aggressive accruals. Not as a hard rule, but as a yellow card that will prompt a closer look. A stock scanner that ignores data quality risks invites noise.
Defining value that captures economics, not just optics
Value is not one thing. It is a family of proxies that all try to measure what you get relative to what you pay. If your screen only uses one metric, you will invite pathologies associated with that metric. Price to book prefers asset-heavy banks and insurers. PE ratios penalize companies with temporarily depressed earnings. Sales multiples miss capital intensity. A composite often works better.
For operating businesses, enterprise value to free cash flow is my anchor. It captures leverage and the actual cash left after maintenance. I will still include EV/EBIT and EV/EBITDA to triangulate, because each tells a slightly different story about cyclicality and non-cash charges. For capital-light software, forward EV/Revenue tempered by gross margin and net retention can be more informative. There is no universal yardstick, just metrics that fit the economics of a sector.
The trick in a stock screener is to avoid overfitting. A practical approach is to standardize a handful of values across the universe, convert them to z-scores within sector, and then average them to a composite value score. Sector-relative scoring matters because a 25 times earnings multiple means different things for utilities versus cybersecurity. This also reduces the bias toward old economy sectors that always screen cheap on raw multiples.
If you prefer thresholds to composites, set them loosely and let momentum do the heavy lifting. For example, accept any stock in the cheapest 40 percent by sector on a composite of EV/EBIT, EV/FCF, and price to tangible book. That leaves room for quality businesses that are not optically dirt cheap, while still avoiding the top third of expensive names.
What momentum actually measures
Momentum comes in varieties too. Price momentum looks at total return over a lookback window, usually 6 to 12 months, excluding the most recent month to reduce short-term reversal effects. Relative strength compares performance against the market or sector. Trend stability matters as well: two stocks may be up 30 percent, but the one with a smooth climb tends to be less prone to air pockets than the one with two gap-ups and a choppy drift.
Earnings momentum is the underrated sibling. Analyst estimate revisions, surprise frequency, and the direction of guidance can pre-empt price action. Many of the strongest price trends start with a string of upward revisions, not headlines. I pay close attention to three-month net upward revisions and the magnitude of changes to current-year EPS or revenue. For cyclical firms, gross margin expansion and inventory turns can be leading indicators.
In the screen, I like a two-layer approach. First, a price momentum filter based on 12-month return minus the most recent month, plus 6-month return, combined into a composite. Second, a simple estimate revisions flag: positive net revisions over the past 90 days, or at least a 1 to 2 percent upward move in consensus. If the stock fails both, I am wary of calling it a momentum name.
The value plus momentum handshake
The point of a multi-factor screen is not to be cute. It is to narrow a large field into a shortlist where the odds and the timing align. The handshake works like this: value asks, am I getting a fair deal for the cash flows and assets here; momentum asks, is the market starting to agree.
There is a sequencing nuance. A deep value name can survive with weaker momentum if the business is improving and the downside is protected by tangible assets or cash. A growth company with strong momentum can pass with only moderate value if cash generation is close. The intersection is not purely mechanical.
A practical rule I use in a stock scanner is to require both factors to be at least above average versus sector. That sounds soft, but the discipline lies in the composite construction and the cutoffs. You can raise the bars in frothy markets and lower them when opportunities are scarce. A second rule: when momentum is extreme, I tighten the value threshold to avoid paying for a blow-off top. When value is extreme, I require clearer trend confirmation to avoid a persistent value trap.
Building the screen step by step
This is where to translate principles into inputs you can actually run on a stock screener. The specific fields and names vary by platform, but the logic travels well.
- Universe and liquidity Market cap above 1 billion dollars for US stocks. Adjust as needed. Average daily dollar volume above 5 million dollars over 3 months. Exclude stocks under 5 dollars, unless you specialize in small caps. Sector-relative value composite EV/FCF, EV/EBIT, and price to tangible book normalized within GICS sector. Accept stocks in the cheapest 40 percent by composite within sector. For financials, replace EV-based metrics with price to tangible book and return on equity context. Price momentum composite 12-month total return minus the most recent month. 6-month total return. Require the combined percentile to be above the 60th within sector. Earnings momentum overlay Positive net EPS estimate revisions over 90 days, or at least 1 percent upward change in next fiscal year EPS consensus. Optional: positive surprise in the last reported quarter with guidance not downgraded.
This is one of the two allowed lists.
This produces a manageable set that you can review. It is worth stressing that the specific cutoffs are levers, not commandments. If your screen returns too many names, tighten one notch. If it returns too few, loosen one notch. Your tolerance for concentration and turnover will dictate where you land.
Avoiding common traps
False positives creep in through predictable doors. The most frequent is a cyclical at peak margins that still looks cheap on trailing earnings, paired with momentum that is simply reflecting the top of a cycle. Think late-cycle industrials with order books that cannot be sustained. Use capacity utilization, order backlogs, and lead times to sense whether you are near peak. Valuation on a mid-cycle EBIT estimate can keep you honest.
The second trap is the value mirage created by working capital games or unsustainable capitalized costs. EV/FCF can hide these for a few quarters. Scan the cash flow statement for a sudden drop in accounts payable days, or ballooning capitalized software development that flatters EBIT. If you cannot explain the cash conversion, you cannot call it value.
Third, momentum prone to sudden reversal often stems from single-product risk or overly promotional management. Check customer concentration, patent cliffs, and one-off catalysts. A biotech that popped on a phase 2 readout will not behave like a consumer staples company with steady revisions.
Finally, sector drift can pollute results. Value behaves differently in financials, energy, and real estate. Momentum in utilities is not the same as in semiconductors. Sector-relative scoring helps, but you may still want separate sub-screens with tailored metrics. In energy, for example, screens that integrate breakeven oil prices, reserve life, and hedging practices improve signal quality far more than generic PE ratios.
Position sizing and holding discipline
Screening is step one. Portfolio outcomes come from what you do next. I have found it safer to size new positions smaller unless both factors are strong and the business quality is clear. You can pyramid as momentum confirms and the thesis develops. Averaging down in a value plus momentum framework is usually a mistake, because a drop in price weakens the momentum leg by design.
Holding periods vary by market regime, but expect a few months to more than a year for the majority of winners. Momentum fades, value closes, and fundamentals move on. A helpful practice is to predefine signals that would cause you to trim or exit. If estimate revisions turn negative for two consecutive months, reduce. If the stock re-rates to the top quartile of sector valuation with flat revisions, harvest. The best time to plan exits is before you need them.
When value and momentum disagree
Great screens produce contradictions. I treat them as prompts for deeper research. If value looks excellent but momentum is negative, ask why. Is the business facing secular decline, legal risk, or a product obsolescence cycle that the numbers do not yet capture? If not, perhaps the market is simply underreacting. In that case, wait for at least a stabilization in price relative to the sector before stepping in. No need to catch falling knives when you can buy the handle.
If momentum is strong and value is weak, be careful not to rationalize excess. The exception is when your alternate valuation framework, tailored to the sector, supports the price. For a software company with 90 percent gross margin and 120 percent net dollar retention, EV/Revenue might be the right anchor, and the screen’s generic composite may be mislabeling the stock as expensive. Use sector-specific templates to avoid throwing out legitimate winners.
Dealing with data quirks and revisions
Backtests often look clean because they rely on point-in-time databases that avoid look-ahead bias. Real life involves delayed filings, estimate updates, and classification changes. A practical stock scanner should build in buffers to reduce the impact of stale or noisy data.
Two conventions help. First, lag your fundamentals by at least one reporting period to ensure you are not using data that an investor could not have known at the time. Second, refresh estimates and prices at a consistent cadence, daily or weekly. Momentum is sensitive to as-of dates. If you run the screen every Friday, stick to that. Also, avoid jumping on the day of an earnings release unless you understand how your platform ingests and timestamps the new numbers.
Outliers deserve manual review. An EV/FCF of 3 could be real or it could be a denominator that excludes a one-time capex spike. A 200 percent one-year return could include a reverse split or a microcap rescue financing that distorts the baseline. If a result looks too good to be true, it often is.
Turning screens into a repeatable workflow
Discipline beats brilliance. Set a weekly rhythm. Monday morning screen, midweek diligence, Friday decisions. Keep a watchlist of near-misses where one factor is close. The moment a stock crosses your threshold, you do not want to start research from zero. Clip management commentary, track one or two leading indicators per name, and write one-paragraph theses for each candidate.
For institutional investors, integrate the screen into a research management system with tags for factor exposure. If the book drifts toward high momentum across the board, you will know you are loading the same risk in different wrappers. Private investors can do a lighter version with a spreadsheet. If you prefer automation, many platforms allow email alerts when a stock meets your criteria. Be deliberate about how many alerts you accept, or you will start to ignore them.
Case sketches from the field
A few quick patterns to illustrate how the value plus momentum mix plays out.
A materials company with energy cost headwinds saw margins compress in 2022, which pushed the stock into the cheapest quartile on EV/EBIT. In early 2023, European gas prices stabilized, analysts nudged estimates up 3 to 5 percent, and the 6-month price momentum rose into the 70th percentile within its sector. The screen caught it, the business recovered, and the stock re-rated from 7 times EBIT to 10 times over nine months. Not a moonshot, but a clean, repeatable example of mean reversion with confirmation.
A payments processor looked expensive on trailing earnings, but on a sector-specific lens using EV/Revenue adjusted for take rate expansion and operating leverage, it sat near fair value. Price momentum was strong, and estimate revisions consistently positive by a few percent each month. The generic screen would have excluded it on value. A tailored sub-screen for software and fintech allowed it through. The stock compounded steadily for a year until valuation reached the top decile of its peer group, at which point the exit rule triggered a trim.
A consumer discretionary retailer screened cheap after a soft quarter. Price momentum still deteriorated, and revisions trended down. Management admitted traffic had shifted online and supply chain cost relief would fade. The composite flagged cheap but dead money. Without momentum, the stock stayed cheap for another year, during which three other candidates with both factors working delivered the returns we wanted. The opportunity cost lesson sticks.
Risk control without strangling returns
The best screens lose money in down markets if unhedged, just like the broad market. Your job is to keep drawdowns acceptable and avoid concentration in correlated bets. Diversify across sectors, but not mindlessly. A basket of shipping companies that all screen cheap with momentum is still a bet on the same freight cycle. The same applies to semiconductors with identical end markets.
Stop-losses can help or hurt. Mechanical stops may kick you out of a position right before it resumes the trend. Soft stops, where you reassess if price closes below a key moving average or if relative strength deteriorates for several weeks, provide flexibility. The key is to ensure the momentum side has not fully broken before you decide to hold on purely for value.
Leverage is tempting when your screen hits a hot streak. Resist large increases. Factor returns are cyclical. The moment a strategy looks like the best way to find stocks, the odds rise that mean reversion is near. Maintain your sizing discipline through both feasts and famines.
Using tools without letting tools use you
Good platforms can feel like magic. A modern stock screener lets you mix dozens of fields, save presets, and run backtests. That convenience can lead to overfitting. Every additional filter narrows the universe and increases the chance you are building a model for last year’s noise.
Keep the core simple, then use your time on reading filings, earnings calls, and competitor commentary. Add one-off flags sparingly, such as insider buying or buyback activity, and treat them as tie-breakers rather than primary filters. Insider buying can be noise in many sectors, while buybacks without free cash flow support are more sizzle than steak.
If you enjoy coding, a custom pipeline lets you be precise and consistent. For everyone else, most major platforms provide enough power. The main benefit comes not from the fanciness of the tool but from the clarity of your rules and the discipline with which you apply them when buying stocks.
A compact checklist for your weekly run
- Confirm data freshness for fundamentals and estimates, including currency and split adjustments. Run the universe and liquidity filters, then apply your sector-relative value composite. Apply the price momentum composite and the earnings revisions overlay. Manually review outliers and sector-specific nuances, flag names for deeper work. Update watchlists, size constraints, and exit triggers for new and existing positions.
This is the second and final allowed list.
Calibrating expectations
Multi-factor investing sets a sensible expectation: a higher hit rate than momentum alone and a better payoff distribution than value alone. That does not mean a smooth ride. The blend can underperform during explosive growth-led rallies where expensive winners get more expensive, and during violent mean reversion where momentum breaks hard. Over a few years, however, I have seen the approach deliver above-market returns with fewer landmines than single-factor approaches.
If you are a long-only investor, measure success not just by a single year’s return but by the depth and length of drawdowns. A 12 percent annualized return with 15 percent peak-to-trough losses is far easier to live with than 15 percent annualized with several 40 percent drawdowns. Investors who survive, win.
A brief note on timing and patience
The screen’s output changes slowly if you use quarterly fundamentals and monthly lookbacks. That is a feature. It prevents churn and keeps you focused on bigger signals. Resist the urge to tinker weekly with thresholds unless market structure changes. A handful of good decisions per quarter usually matters more than daily fiddling. The muscle to build is patience in letting winners compound while watching for signs that either value has closed or momentum has cracked.
Bringing it all together
Think of value and momentum as two hands building the same house. Value lays the foundation by ensuring you pay a sensible price for real cash flows or assets. Momentum raises the frame by aligning your purchase with the market’s improving view. When both are present, the house stands better against storms.
Use a stock screener to enforce your rules and a watchlist to capture near-misses. Score value within sectors, not across the entire market. Let price and earnings momentum corroborate each other. Watch for cycles masquerading as secular trends. Above all, treat the screen as triage, not a verdict. The best stocks to buy now are the ones that pass your test and your judgment, in that order. When you can do that consistently, you will not just find stocks, you will build a durable, repeatable process that respects risk and lets winners work.