My Deep Value Stock Screening Process: From 3,000 Stocks to a Short List of 5

There are roughly 3,000 publicly traded US companies with a market capitalization under $2 billion. Most of them are not worth your time. A small number of them are great values hiding in plain sight. Genuinely cheap, financially strengthening businesses that the market has overlooked, misunderstood, or written off prematurely.

The challenge is finding them without spending your entire life staring at a Bloomberg terminal.

I have been doing this for over twenty years, including my time running Value Stock Guide, which was specifically built on small-cap deep value research. Over that time I have refined a screening process that systematically narrows 3,000 candidates down to roughly five that deserve serious analytical attention. This article walks you through that process, step by step.

Key Takeaways

• The starting universe for deep value screening in small caps is all US-listed stocks under $2B market cap: a little over 3,000 names
• Quantitative filters eliminate roughly 90% of candidates based on valuation, balance sheet quality, and financial momentum
• The Piotroski F-Score is the single most important composite filter for separating improving businesses from value traps
• Qualitative review is non-negotiable: quantitative screens find candidates, but judgment determines what you buy
• Catalyst identification is the final gate. Cheap is not enough, there must be a reason the gap between price and value will close

Why Small-Cap Value?

Before I explain the process, let me explain why the search is concentrated in small-cap value in the first place.

The small-cap value premium is one of the most well-documented phenomena in financial markets. Small-cap value stocks have historically outperformed the broad market by a meaningful margin over long periods. The academic evidence is robust. Fama-French and numerous subsequent researchers have confirmed it.

But why does it persist? Because most institutional investors cannot effectively operate in this space. A $5 billion fund cannot build a meaningful position in a $300 million market cap company without moving the price against itself. The efficiency of the market is lowest precisely where the opportunity is greatest. That asymmetry is what I am trying to exploit.

Step 1: Define the Starting Universe

Parameters:

• US-listed stocks only
• Market capitalization: $50 million to $2 billion
• Excludes: financial companies (banks, insurance) unless specifically running a financial-focused screen. Their accounting is different enough to require separate analysis
• Excludes: biotech and pre-revenue companies. I need real cash flows to analyze

The lower bound of $50M matters. Below that level, liquidity becomes genuinely dangerous. I have written about the risks of low-liquidity small-cap stocks. They are real and they are distinct from ordinary volatility. Getting into a $30M market cap stock is easy. Getting out when you want to is not.

I used to revel in micro caps and nano cap stocks with abysmal liquidity. A truly patient investor is able to build up a meaningful position over time. As my processes evolved (periodic rebalances), I now find that there needs to be a minimal amount of liquidity for my process to work effectively.

The upper bound of $2 billion is flexible. If I find a compelling name at $2.5B, I will look at it. But the sweet spot for institutional neglect and analytical edge is under $2 billion.

Starting count: approximately 2,800–3,200 names depending on market conditions.

Step 2: Apply Quantitative Valuation Filters

This is the first elimination round. I am looking for cheap stocks trading at a significant discount to intrinsic value measures.

Filter 2a: Price-to-Book Ratio below 1.5

Price-to-book is the foundational deep value metric, rooted in the Graham-Dodd tradition. A P/B below 1.5 means the stock trades at or near the tangible asset value of the business. For asset-heavy businesses (industrials, manufacturers, distributors), this is a meaningful anchor. For asset-light businesses, I adjust or bypass this filter and substitute EV/EBIT.

I am hunting for businesses that could theoretically be liquidated at close to or above the current stock price. I could go deeper in the valuation rabbit hole if I can find stocks in the net-net category. That is the margin of safety built into deep value investing.

Filter 2b: EV/EBIT below 12

Enterprise value to earnings before interest and taxes. This cross-capital-structure multiple captures cheapness for businesses where book value is less meaningful. It is harder to manipulate than P/E and does not suffer from the EBITDA problem of ignoring capital intensity.

I use P/B for asset-heavy businesses and EV/EBIT for asset-light ones. Applying both filters simultaneously creates a combined valuation screen. A stock typically needs to pass at least one of these two tests.

Filter 2c: Free Cash Flow Positive (trailing twelve months)

This is a simple binary filter. The company must be generating positive free cash flow. Burning cash is acceptable in hypergrowth tech; it is not acceptable in the kinds of businesses I look at. Positive FCF confirms the business model is working at a basic level.

I have written at length about free cash flow and margin of safety. FCF is what actually builds intrinsic value over time.

After Step 2: approximately 400–600 names remain.

Step 3: Apply Balance Sheet Quality Filters

Valuation alone is not enough. I need to know the business can survive long enough for the value to be realized. This step screens for financial health and survivability. Many value investors find a cheap stock and consider their due diligence done. To really benefit from the undervaluation, you need to make sure that there is enough runaway for the company to be able to close its valuation gap.

Filter 3a: Current Ratio above 1.5

Current assets must exceed current liabilities by a comfortable margin. This screens out companies with near-term liquidity risk. For small caps going through operational stress, liquidity can evaporate quickly. I want the cushion. If you want to be very conservative, you can insist on the current ratio of 2 or greater.

Filter 3b: Debt/EBITDA below 3.0

Excessive leverage is the primary cause of what I call the “value trap with a time limit”; cheap stocks that run out of runway before the business recovers. Three times EBITDA is already meaningful leverage. Above that level, I need an exceptional reason to proceed.

I have been involved with too many small companies over the years to know that what may seem like prudent borrowing now can quickly devolve into an unmanageable debt spiral, if the management is not careful.

Filter 3c: No going-concern language in the most recent 10-K

This is a qualitative check I run at the quantitative stage because it is binary and fast. If auditors have raised going-concern doubts, the risk profile changes fundamentally. I will occasionally look at these situations separately as special situations, but they do not belong in my core deep value process.

For a deeper look at how to use financial ratios to identify value traps, I have a separate article that covers this in detail.

After Step 3: approximately 150–200 names remain.

Step 4: Apply the Piotroski F-Score Filter

This is the most important quantitative filter I run. It is also the one most investors skip because it requires more work than a simple ratio comparison.

Filter 4a: Piotroski F-Score of 7 or higher

The Piotroski F-Score uses nine binary signals across profitability, leverage, and efficiency to score whether a business is fundamentally improving or deteriorating. A score of 7–9 means the company is strengthening on most measures. A score of 1–3 means it is deteriorating. Scores of 4–6 are mixed.

The academic research behind the Piotroski F-Score showed that buying high-F-Score value stocks and avoiding low-F-Score value stocks dramatically improves the returns from simple value screens. The reason is intuitive: cheap stocks are cheap for a reason, and you want the ones where the reason is the market’s mistake, not a fundamentally broken business.

This filter cuts deeply. In most market environments, only a fraction of already-cheap, financially sound stocks also show Piotroski scores of 7 or above. That is exactly what I want, a demanding filter that leaves only genuinely interesting candidates.

Please note that there are times when I make exceptions if there are other situations that make the stock an incredible purchase. For example, a company in liquidation that may be a simple asset play on the gap between market value and market price of liquid assets.

After Step 4: approximately 30–50 names remain.

Step 5: Manual Qualitative Review

At this point I switch from quantitative screening tools to reading actual documents. Every stock that has survived the quantitative filters gets a manual review that takes me roughly 30 minutes per name. I call it my 30-minute stock evaluation checklist.

5a: Business Model Review

Can I understand what this business does? Does it produce something the world genuinely needs or want? Is the revenue model sustainable? Does it generate repeat business, or does the company have to sell to new customers constantly to maintain revenue?

I am not looking for exciting businesses. I am looking for businesses I can understand well enough to have a view on their intrinsic value. If I cannot explain what the company does in two sentences, it goes in the too-hard pile.

5b: Competitive Position Assessment

What keeps customers coming back? Is there switching cost, cost advantage, or network effect? I do not require a deep moat. Many of my best investments have been in mediocre businesses bought at exceptional prices. But I need to understand whether the business can defend its current profitability for the three to five years I expect to hold.

5c: Management Quality Check

I look at three things: insider ownership (do management’s interests align with mine?), capital allocation history (how have they used the cash the business generates?), and compensation structure (are they rewarding themselves regardless of performance?).

Insider ownership above 10% is a meaningful positive for a small cap. A history of dilutive acquisitions at peak prices is a negative. Heavy stock option issuance to management is a yellow flag.

5d: Industry and Macro Tailwinds or Headwinds

I do not try to predict macro conditions. But I do want to understand whether there are obvious structural headwinds facing an industry that would make a recovery thesis implausible. A cheap brick-and-mortar retailer may look cheap, but if the entire category is being disrupted, the quantitative cheapness reflects fundamental deterioration rather than temporary mispricing.

After Step 5: approximately 10–15 names remain.

Step 6: Catalyst Identification

This is the final gate before a stock moves onto my active research list. Cheap is necessary but not sufficient. I need a reason to believe the gap between price and intrinsic value will close within a reasonable timeframe, typically three to five years.

I look for one of the following types of deep value catalysts:

Operational catalysts: New management, a restructuring plan, product launches, capacity expansions, or cost reduction initiatives that have a clear path to improving earnings.

Financial catalysts: Debt paydown that will meaningfully improve financial flexibility, a potential dividend initiation, or share buybacks at deeply discounted prices. Sometimes a stock is dragged down due to ongoing litigation, that once resolved can be a meaningful change in the business profitability and viability.

Corporate catalysts: Spin-offs that will surface hidden value, activist investor involvement, strategic review processes, or acquisition interest from industry players.

Market re-rating catalysts: The company recently crossed a profitability threshold (e.g., returned to positive FCF), or earnings revisions have turned positive after a period of decline. Sometimes companies are added to market indexes that triggers institutional buying from funds that follow those indexes.

Without an identifiable catalyst, I have learned to be cautious. Value traps often look like catalyst stories that never materialize. The presence of a believable catalyst is what separates “cheap and possibly getting cheaper” from “cheap with a clear path to resolution.”

After Step 6: approximately 5–8 names on the active research list.

Step 7: Deep-Dive Due Diligence

Only now do I build a detailed financial model. Everything before this step was about efficiently eliminating names. This step is about deeply understanding the ones that survived.

I read the last three to five annual reports, the last eight to twelve quarterly earnings calls, and any relevant investor presentations. I look for management’s stated priorities and whether their actions match their words. I build a simple DCF model not to generate a precise target price but to stress-test my assumptions about revenue trajectory, margin structure, and capital requirements.

I also run my complete financial ratios stock analysis checklist at this stage: all five ratios with full calculation from the financial statements, not just screener data.

The output is a research memo: a one-to-three page document summarizing the thesis, the key risks, the probable outcome range, and my estimate of intrinsic value. That memo is what I review when deciding whether to initiate a position and how to size it.

What the Process Is Designed to Avoid

More than anything, this process is designed to avoid two specific failure modes:

Value traps: Stocks that look cheap because they are cheap: the business is genuinely deteriorating and the low multiple reflects real, permanent value destruction. The Piotroski filter and qualitative review are my primary defenses against this.

Quantitative mirages: Stocks that pass every screen but have a fatal flaw hidden in the fine print. These could include a related-party transaction, an accounting change, a customer concentration risk that does not show up in ratios. The manual review catches most of these.

I have detailed thoughts on how to identify value traps using financial ratios. The topic deserves its own treatment.

Where Inner Circle Members Get the Advantage

I run this full process every week. There are multiple screening criteria I run to triangulate undervalued stocks from many different directions. The output of the few stocks that survive all seven steps goes into my Inner Circle research queue. Members get the full due diligence reports: the financial model, the thesis, the risk assessment, and the Kelly Criterion position sizing recommendation.

Running this process yourself is absolutely possible. What the Inner Circle provides is the finished analytical work on each name, saving the hours of due diligence that the screening process requires.

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Disclosure: I may hold positions in some of the stocks mentioned as examples in this article.

Photo by Jakub Żerdzicki on Unsplash