HOW TO FIND CHEAP TECH STOCKS BEFORE EVERYONE ELSE DOES
HOW TO FIND CHEAP TECH STOCKS BEFORE EVERYONE ELSE DOESA practitioner’s guide to running full due diligence on software and technology companies — the way a deep value investor actually does it.
Welcome to Cheap Software Stocks Don’t recognize this sender? Unsubscribe with one click Cheap Software Stocks recently imported your email address from another platform to Substack. You'll now receive their posts via email or the Substack app. To set up your profile and discover more on Substack, click here. Benjamin Graham taught us that price is what you pay, value is what you get. That principle applies to a SaaS company in 2026 just as it applied to a railroad in 1936. The market still misprices companies. It still panics. It still extrapolates short-term weakness into permanent impairment. And when it does, that’s when we go shopping. Most investors think “value” and “tech” are opposites. We disagree. Some of the greatest wealth-compounding opportunities of the past two decades have been cheap tech stocks trading at a discount to intrinsic value. The trick is knowing where to look — and knowing how to look. This post is a complete walkthrough of our due diligence process for software and technology stocks. We’ll cover how to screen for candidates, how to read the financials like a forensic accountant, how to build a simple valuation model, and how to know when to pull the trigger — and when to walk away. STEP 1: SCREENING FOR CANDIDATESThe first job is to find ideas. The market is large and noisy. You don’t have time to analyze every company, so you need a disciplined screen that surfaces businesses worth studying. We start with quantitative filters. These aren’t valuation screens — we’re not trying to find stocks that look cheap on a spreadsheet. We’re trying to find businesses that have real earning power but are temporarily in the penalty box. Primary screens we run:
[Practitioner Note] Tools like Stratosphere, Tikr, or Koyfin make these screens easy to run. We also manually read the “Frequently Cited Stocks” section of 13F filings from investors we respect — if a great investor is buying a beaten-up tech stock, we want to understand why before the next 13F cycle reveals it to everyone else. STEP 2: UNDERSTANDING THE BUSINESS MODEL FIRSTBefore we open a single spreadsheet, we spend time understanding what the company actually does and how it makes money. Sounds obvious. You’d be surprised how many investors skip this step and go straight to the P/E ratio. In software and tech, business model quality varies enormously. A company selling perpetual licenses is fundamentally different from one selling annual SaaS subscriptions, which is different from a marketplace, which is different from a hardware company with a services attach rate. Each has a different risk profile, a different valuation framework, and different things you need to understand to form a view. We ask a set of basic questions upfront:
This part of the process is qualitative and messy. Read every earnings call transcript from the past three years. Read competitor filings. Read industry analyst reports. Talk to people who use the product if you can. The goal is to build conviction — or to kill the idea early — before you’ve invested hours in a financial model. “We only buy what we understand. If we can’t explain the moat in two sentences, we don’t own it.” STEP 3: DISSECTING THE INCOME STATEMENTNow we open the 10-K. The income statement tells us about profitability, but in tech it can be deeply misleading if you read it naively. Here’s how we work through it. Revenue quality and growth We want recurring revenue, ideally ARR (Annual Recurring Revenue) or MRR-based. One-time revenue that gets counted alongside recurring revenue is a yellow flag. We disaggregate the revenue into its components and track each one separately across quarters. Is the growth coming from new customers or from expansion within existing accounts? Both are good, but for different reasons. For SaaS companies, we pay close attention to the breakdown between subscription revenue and professional services. Professional services revenue is lower quality — it’s labor-intensive, lower margin, and doesn’t recur the way software does. A company inflating its headline revenue number with services attach is not as healthy as the top-line growth suggests. Gross margins — the most important number in tech Gross margin is the structural DNA of a tech business. Software gross margins above 70% indicate high-quality unit economics. Below 60%, we start asking hard questions. Below 50%, you’re essentially looking at a services business wearing a software valuation, and that’s a problem. Gross margin benchmarks: - World-class SaaS: 75–85% - Good SaaS: 65–75% - Mixed model: 50–65% (dig into the mix) - Red flag: below 50% (structural concern) Operating expenses: separating real costs from accounting fiction GAAP operating expenses for software companies are badly distorted by stock-based compensation (SBC). This is one of the most important adjustments to make. SBC is a real economic cost — dilution is real — but it’s also non-cash and often used by management to obscure true profitability. We do two things: we adjust for SBC to understand cash economics, and we separately track SBC as a percentage of revenue to understand the dilution rate. SBC above 15% of revenue for a mature company is a problem. It means management is compensating employees at the shareholders’ expense rather than earning returns for capital providers. Adjusted Operating Income formula: GAAP Operating Income + Stock-Based Compensation + Amortization of Acquired Intangibles + Restructuring Charges (if one-time) = Cash Operating Income (our base metric) We also watch R&D spend very carefully. In tech, R&D is the engine. A company that’s cutting R&D to hit near-term earnings targets is potentially starving its future. The question is always: is R&D being spent efficiently? We track R&D as a percentage of revenue over time and compare it to revenue growth. If R&D spending is rising but growth is slowing, the productivity of that spend is declining — that’s a sign of a business losing its innovative edge. STEP 4: THE CASH FLOW STATEMENT — WHERE TRUTH LIVESIf the income statement is the face a company shows the world, the cash flow statement is what’s actually happening underneath. This is where deep value investors spend a disproportionate amount of their time. Free cash flow is the only number that matters long-term Free cash flow is operating cash flow minus capital expenditures. For most software companies, capex is low — servers, laptops, office equipment — which is precisely why software can be such a remarkable business: capital is not the binding constraint. But we verify this. We’re looking for companies where free cash flow is high relative to net income — ideally higher, which indicates quality earnings. FCF Yield formula: FCF Yield = Free Cash Flow / Market Capitalization Target entry: FCF yield > 5–6% for mature software Exceptional value: FCF yield > 8% with stable or growing FCF Working capital dynamics and deferred revenue For subscription software companies, deferred revenue is a gift. When customers pay annually upfront, the company collects cash before recognizing revenue — this is a source of float, similar conceptually to an insurance company’s float. Watch deferred revenue growth. If it’s growing alongside ARR, the billing model is healthy. If deferred revenue is shrinking while ARR is growing, customers are moving to monthly billing — that’s a cash flow headwind worth understanding. The Rule of 40 — and why we use a stricter version The Rule of 40 holds that a healthy software company’s revenue growth rate plus free cash flow margin should sum to at least 40. It’s a rough heuristic that tries to balance growth and profitability. We use it as a sanity check, not a buy signal. A company at 60% on the Rule of 40 that’s trading at 4x EV/Revenue is different from one at 60% trading at 15x — and deep value investors only care about the former. Rule of 40 benchmarks: - Above 60: Exceptional efficiency - 40 (minimum threshold): Healthy benchmark - 40–60 (deep value sweet spot): Priced below quality - Below 40: Needs a catalyst — turnaround candidate STEP 5: THE BALANCE SHEET — FORTRESS OR LIABILITY?Deep value investing requires a margin of safety, and a strong balance sheet is a core source of that margin. We want companies that can weather a downturn, a competitive attack, or an economic recession without being forced into dilutive financing. For software companies, the balance sheet analysis focuses on a few key areas. Net cash position — cash and equivalents minus all debt — tells us immediately how much cushion exists. A company with $500M in cash and no debt trading at $1B market cap has a very different risk profile than the same market cap with $400M in debt. The enterprise value — market cap plus net debt — is what you’re actually paying for the business. We look at debt maturity schedules. A company with $300M in debt that matures in five years is fine. The same company with $300M maturing in 18 months during a period of elevated rates is in a very different position. Many value traps in tech have been created by investors who saw a cheap EV/EBITDA multiple without noticing the refinancing cliff sitting two years out. Red flag checklist — balance sheet: — Debt-to-EBITDA above 4x for a non-growing company — Covenant-heavy credit agreements near the threshold — Goodwill representing more than 50% of total assets (sign of acquisitive growth that may have been overpriced) — Rapidly declining cash balance with no path to cash generation — Any mention of “going concern” language in the auditor’s report — walk away immediately STEP 6: SAAS-SPECIFIC METRICS — THE OPERATING DASHBOARDFor software companies, the GAAP financials are necessary but not sufficient. We also track a set of operating metrics that reveal the health of the underlying subscription engine. These are reported in investor relations sections, earnings supplements, and — for the best-run companies — the 10-K itself. Net Revenue Retention (NRR) NRR is the single most important operating metric in SaaS. It measures how much revenue you retain from existing customers after accounting for churn, contraction, and expansion. An NRR of 110% means that even if you acquired zero new customers this year, revenue would grow 10% from your existing base alone — through upsells, seat expansion, and price increases. NRR benchmarks: - Above 120%: Elite — best-in-class retention - 110–120%: Strong — healthy expansion - 100–110%: Acceptable — flat, needs new logos - Below 100%: Problem — net churn, scrutinize immediately Customer Acquisition Cost (CAC) and Payback Period CAC payback period tells us how long it takes to recoup the cost of acquiring a customer through the gross profit generated by that customer. Under 18 months is very good. Over 36 months is a warning sign that the go-to-market machine is inefficient. We calculate this ourselves from the sales and marketing expense line divided by new ARR added in the period, adjusted for gross margin. CAC Payback Period formula: CAC Payback = (S&M Expense / New ARR Added) / Gross Margin % Example: $10M S&M ÷ $5M new ARR = 2.0x CAC ratio At 75% gross margin: 2.0 ÷ 0.75 = 2.67 years payback → Borderline acceptable; want to see this trending down over time Magic Number The magic number measures the efficiency of sales and marketing investment in generating new recurring revenue. We calculate it as net new ARR (current quarter ARR minus prior quarter ARR) times four, divided by prior quarter S&M expense. A magic number above 1.0 indicates you’re getting more than $1 of annualized new revenue for every dollar spent acquiring it. Below 0.75 suggests the go-to-market is struggling and needs to be fixed. STEP 7: BUILDING A SIMPLE VALUATION MODELWe are deliberately simple in our modeling. Complex DCF models with 15 tabs and precise projections out to 2040 give a false sense of precision. A five-year business is hard enough to model with reasonable accuracy. The goal of the model is not to predict the future — it is to understand what the market is implying about the future, and to judge whether that implied scenario is too pessimistic. The reverse DCF approach Rather than projecting forward, we work backward. Given the current stock price, what growth rate and terminal margin does the market need to assume to justify that price? If the implied scenario requires the company to grow 25% per year for 10 years to earn a fair return, that’s a high bar — any stumble and the stock falls. But if the implied scenario assumes zero growth forever and the company is still growing at 8%, the market is being irrationally pessimistic. That’s our opportunity. Reverse DCF — implied growth formula: EV = FCF × (1 - g/r) / (r - g) [simplified Gordon Growth Model] Solve for g (growth) given: · Current EV (market cap + net debt) · Current FCF (trailing or forward estimate) · r = discount rate (we use 10–12% for tech) If implied g is less than 0% for a growing business → potential value opportunity Scenario analysis — bull, base, bear We model three scenarios: base case (the business performs roughly as it has historically), bull case (growth reaccelerates, margins expand to peer levels), and bear case (revenue growth halves, margins stay compressed). We assign rough probabilities and weight the outcomes. The key question is: if the bear case materializes, do we lose money in a permanent way, or is it a temporary drawdown in an otherwise sound business? Deep value investing in tech requires a strong stomach for short-term pain. A stock can get cheaper after you buy it. What we’re trying to ensure is that the fundamental downside — the actual business value — is protected even in adverse scenarios. Price drawdown risk and fundamental risk are not the same thing. STEP 8: MANAGEMENT QUALITY AND CAPITAL ALLOCATIONGreat businesses run by bad management teams are investments that require the business to bail out the team. We prefer businesses where management thinks like owners — because they are owners. We look at management’s track record on capital allocation. Have acquisitions created value or destroyed it? Has the company returned capital to shareholders intelligently — buying back stock when cheap rather than at peak prices? Are they empire-building with other people’s money, or are they disciplined stewards of the balance sheet? Founder-led companies often score well here. Founders tend to think in longer time horizons, and they have direct personal stakes in permanent capital rather than just their comp plan. But founder-led doesn’t automatically mean good capital allocator — we’ve seen plenty of founders who love to acquire companies at multiples that never make economic sense. Five things we look for in management: 1. Skin in the game. Does management own meaningful stock — not just options? Insider ownership above 5–10% for the combined leadership team aligns incentives with shareholders. 2. Acquisition track record. Pull the last three acquisitions. What were the purchase multiples? What was promised vs. delivered? Goodwill impairments are admissions of prior overpayment. 3. Shareholder communication quality. Do they give guidance they actually hit? Are earnings calls candid about problems? Management that’s never wrong is either lucky or lying. We want honest partners. 4. Compensation structure. Is executive pay aligned with shareholder returns, or is it largely fixed and structured to pay out regardless of outcomes? Proxy statements reveal a lot. 5. Capital allocation framework. Has the company articulated a clear hierarchy for capital allocation: organic growth first, then acquisitions, then buybacks? Improvised capital allocation is a red flag. STEP 9: IDENTIFYING THE CATALYSTOne of the oldest traps in value investing is buying cheap things that stay cheap. In deep value, we’re looking for businesses trading below intrinsic value, but we also want some reason to believe that the gap between price and value will close within a reasonable time horizon — typically two to four years. Catalysts in tech can take many forms. A change in management — especially bringing in an operationally excellent CEO to replace a founder who was brilliant at building but poor at scaling. A business that has been through a significant restructuring and is now leaner, with a cost structure aligned to a lower-growth reality. A competitive scare that turned out to be overblown. A macro headwind — rising rates, enterprise budget freezes, FX headwinds — that is cyclical rather than secular. Sometimes the catalyst is simply time: the market remembers the bad quarter but forgets the durable business underneath. Holding through the forgetting period requires conviction, which is why all the prior steps matter. You can’t hold through a 40% drawdown unless you have genuine, deep conviction in the underlying business value. [Important distinction] We are not buying broken businesses hoping for a turnaround. A company with declining NRR, losing customers to better-funded competitors, with management that has missed guidance seven quarters in a row, is not a value opportunity — it’s a value trap. The question is always whether the business has enduring competitive advantages that have been temporarily obscured by noise, or whether the business itself is impaired. STEP 10: SIZING AND PORTFOLIO CONSTRUCTIONFinding a great idea is only half the job. Position sizing is where the expected value gets converted into actual portfolio outcomes. We size positions based on conviction, valuation upside, and the severity of the downside scenario. A high-conviction position where the bear case still implies a reasonable outcome might get 5–8% of the portfolio. A more speculative situation with a wider range of outcomes might get 2–3%. We never size so large that a single position failure becomes an existential problem for the portfolio. Permanent capital preservation is the first job. We also think about correlation. Multiple beaten-up SaaS companies are likely to be correlated — they’ll all get hit in the same risk-off event, and they’ll all recover together. That’s fine if you’ve sized the aggregate exposure intelligently. We typically run 15–25 positions, concentrated enough to matter, diversified enough to survive. PUTTING IT ALL TOGETHER: WHAT A REAL PROCESS LOOKS LIKEHere’s a simplified example of how we’d run through a candidate. Imagine a vertical SaaS company that serves the construction industry. It came up on our screen because it hit a 52-week low after a disappointing quarter where guidance was cut due to a slowdown in commercial construction permitting — a macro headwind, not a company-specific one. Step one: we understand the business. It sells project management and financial software to general contractors and subcontractors. Switching costs are high — contractors manage their entire job cost accounting on this platform. Once a contractor is live on the system, migration is painful and disruptive. That’s a moat we can hold in our head in two sentences. Step two: we look at the financials. Gross margins are 72% and have been stable. NRR is 108% — lower than a year ago when it was 114%, but still above 100%, meaning existing customers are still spending more, just growing more slowly. FCF margin is 14% even in this slow environment. The company is profitable. Step three: we run the reverse DCF. At the current stock price, the market is implying roughly 4% annual FCF growth for the next decade. But the vertical the company serves is one where software penetration is still in early innings, and the company has been compounding at 18% over five years. Even if it decelerates significantly to 10–12%, the stock is materially undervalued. Step four: we check the balance sheet. Net cash of $180M, no meaningful debt, so the business can weather the construction slowdown without stress. Management has been buying back stock — $40M in the last two quarters at prices below current levels. That’s a good sign. We take a 4% initial position. We’ll add to it if the stock goes lower and our thesis remains intact. The thesis is simple: commercial construction will eventually recover, and when it does, this company’s NRR will expand back toward 115%. At that point, the market will re-rate the multiple upward at the same time earnings power recovers. That double expansion — multiple re-rating plus earnings recovery — is exactly the kind of outcome that makes deep value investing in tech rewarding. FINAL THOUGHTSDeep value investing in technology is not about buying cheap junk and hoping it goes up. It is about finding genuinely excellent businesses — businesses with high gross margins, strong retention, real moats, and honest management — that are temporarily mispriced because the market has confused a cyclical problem with a structural one. The work is primarily analytical: understand the business, verify the cash flows, stress-test the balance sheet, and judge management honestly. But ultimately, it requires a psychological toughness that the analysis alone cannot provide. You will buy things that go lower before they go higher. You will hold through earnings seasons where the stock drops 15% and everyone tells you you’re wrong. The process described here is designed to give you the conviction to hold — because you’ve done the work. When the market sells high-quality tech indiscriminately, that is not a threat to the disciplined value investor. It is a gift. Learn to recognize it as such. Cheap Software Stocks is free today. But if you enjoyed this post, you can tell Cheap Software Stocks that their writing is valuable by pledging a future subscription. You won't be charged unless they enable payments.
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