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ROIC Stock Screening: 5-Step Framework + 938-Company Sector Benchmarks (Save 4 Hours)

Manual ROIC screening takes 4+ hours per session. Learn our 5-step framework with sector-specific benchmarks from 938 companies showing why retail median ROIC (15.9%) differs from utilities (5.7%). Screen 500+ companies in 30 minutes with sector-adjusted thresholds.

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18 min read
ROIC Stock Screening: 5-Step Framework + 938-Company Sector Benchmarks (Save 4 Hours)

đź“Š TL;DR: ROIC Stock Screening

  • âś“ Problem: Manual ROIC screening takes 4+ hours per analysis session (extracting balance sheets, calculating NOPAT, tracking 5-year averages)

  • âś“ Solution: 938-company benchmarks + 5-step framework showing why sector context matters: retail median ROIC is 15.9% vs utilities 5.7% (2.8x difference)

  • âś“ Result: Screen 500+ companies in under 30 minutes with sector-adjusted thresholds

  • âś“ Key finding: 41.2% of companies exceed 15% ROIC, making absolute thresholds insufficient without sector comparison

  • âś“ Time saved: 6.5 hours per screening session vs manual Excel approach

Introduction: Why Most Investors Screen ROIC Wrong

Screening stocks by Return on Invested Capital (ROIC) should be simple: find companies above 15%, call it a day. But here's the problem—our analysis of 938 non-financial companies reveals that 41.2% exceed 15% ROIC, yet they're not all quality investments.

Why? Sector context matters more than absolute thresholds.

A retail company at 15.9% ROIC sits at the sector median—perfectly average. The same 15.9% ROIC for a utility company would represent extraordinary performance (sector median: 5.7%). Without sector benchmarks, you'll misinterpret nearly half of all companies' ROIC performance.

This guide provides a complete ROIC screening framework backed by real S&P 500 data: sector-specific benchmarks, actionable screening criteria, and 28 company examples showing what "good" ROIC actually means in each industry.

What you'll learn:

  • Why retail median ROIC (15.9%) exceeds manufacturing (11.2%) by 42%

  • Sector-specific screening thresholds (good, acceptable, avoid)

  • 5-step framework to screen 500+ companies in under 30 minutes

  • Real company examples: Home Depot (HD) (27.2%) vs Kroger (KR) (7.5%)—both retail, vastly different quality

ROIC Fundamentals: Quick Review

Return on Invested Capital (ROIC) measures how efficiently a company generates profit from the capital invested in its operations.

Formula:

ROIC = NOPAT / Invested Capital

Where:

  • NOPAT = Net Operating Profit After Tax (excludes interest expense)

  • Invested Capital = Working Capital + PP&E + Goodwill + Intangibles

Why ROIC matters for screening:

Important: This article uses the asset-based ROIC formula, which treats missing goodwill/intangibles as zero (appropriate for organic growers). For detailed guidance on reading financial statements, see the SEC's Beginner's Guide to Financial Statements. Our dataset covers 95%+ of non-financial companies.

The 5-Step ROIC Screening Framework

Most investors fail at ROIC screening because they use absolute thresholds without sector context. This framework solves that problem.

Step 1 - Filter by Sector Suitability

NOT all sectors should be screened by ROIC. Start by excluding:

❌ Exclude These Sectors:

  • Financial services (banks, insurance, asset managers)

    • Why: Debt is inventory, not leverage. Use ROE instead.

    • Example: Bank of America, JPMorgan Chase

  • Real estate (REITs, property developers)

    • Why: Regulatory capital structure requirements distort invested capital

    • Example: Prologis, American Tower

  • Technology (with caution) — requires R&D capitalization adjustments

    • Why: Expensed R&D understates invested capital

    • Example: Microsoft, Alphabet (ROIC appears inflated)

âś… ROIC-Suitable Sectors:

  • Manufacturing & Industrials

  • Retail

  • Healthcare (services + pharmaceuticals)

  • Utilities

  • Transportation

  • Energy & Materials

Practical tip: If you're using a stock screener, apply sector filters BEFORE ROIC filters. Saves time and prevents false positives.

Step 2 - Establish Sector-Specific Benchmarks

Never compare ROIC across sectors. A "good" ROIC in utilities (10%+) would be mediocre in retail (15%+).

Use these benchmarks from our 938-company analysis:

SectorMedian ROICP25 (Below Average)P75 (Above Average)Companies Analyzed
Retail15.9%9.7%22.4%59
Other12.0%7.1%18.7%78
Manufacturing11.2%6.5%18.4%335
Services_Healthcare9.6%3.0%18.2%157
Transportation8.2%3.6%15.3%43
Utilities5.7%4.8%10.2%50

Key findings:

  • 2.8x ROIC spread between highest (Retail 15.9%) and lowest (Utilities 5.7%) sectors

  • Manufacturing baseline: 11.2% median (largest sample, most representative)

  • Retail surprise: Highest median ROIC (survivor bias + modern efficiency—see Section 4)

How to use these benchmarks:

  • Identify the company's sector

  • Compare to sector median (not overall 15% rule)

  • Assess position: Above P75 = excellent, Above median = good, Below P25 = avoid

Step 3 - Apply Sector-Adjusted Screening Thresholds

Based on sector benchmarks, use these actionable screening rules:

Retail Sector (Median 15.9%)

Manufacturing Sector (Median 11.2%)

  • Excellent (>18.4%): Premium brand or IP advantage

    • Examples: Eli Lilly 48.5%, Caterpillar 32.6%, Merck 24.2%

  • Good (11.2%-18.4%): Solid execution, competitive positioning

    • Examples: Johnson & Johnson 17.2%, 3M 16.7%

  • Acceptable (6.5%-11.2%): Below median, monitor closely

    • Examples: Pfizer 13.4%, AbbVie 11.9%

  • Avoid (<6.5%): Capital-intensive with poor returns

Utilities Sector (Median 5.7%)

  • Excellent (>10.2%): Exceptional for regulated industry

    • Examples: American Electric Power 13.2%, Southern Company 10.9%

  • Good (5.7%-10.2%): In line with sector norms

    • Examples: NextEra Energy 5.6%

  • Acceptable (4.8%-5.7%): Below median but acceptable given regulation

    • Examples: Duke Energy 5.2%

  • Avoid (<4.8%): Underperforming even with regulated returns

    • Examples: Dominion Energy 4.1%

Transportation Sector (Median 8.2%)

  • Excellent (>15.3%): Efficient operations despite capital intensity

    • Examples: UPS 12.8%

  • Good (8.2%-15.3%): Sector-average performance

    • Examples: Norfolk Southern 9.1%

  • Avoid (<3.6%): Below P25, likely operational issues

    • Examples: FedEx 5.9% (below median, investigate)

Step 4 - Screen for Absolute Minimums (Safety Filter)

Even with sector-adjusted thresholds, apply these universal rules:

Hard Filters:

  • Negative ROIC: Automatic exclusion (destroying capital)

  • ROIC < 5%: Below cost of capital for most companies

  • ROIC > 50%: Investigate for data errors (e.g., Casey's General Stores showed 243% due to negative invested capital—removed as outlier)

Soft Filters (Investigate):

  • ROIC 5%-8%: Marginal returns, only accept if sector median is similarly low (utilities, transportation)

  • ROIC declining 3+ years: Warning sign of deteriorating competitive advantage

Step 5 - Verify with Multi-Year Averages

Critical: NEVER screen on single-year ROIC. Use 3-5 year averages to smooth:

  • Cyclical fluctuations (especially energy, materials)

  • One-time restructuring charges

  • Acquisition effects (goodwill distortions)

How to calculate:

5-Year Avg ROIC = (ROIC_2020 + ROIC_2021 + ROIC_2022 + ROIC_2023 + ROIC_2024) / 5

Why this matters:

  • High-ROIC companies tend to maintain quality over time

  • Single-year spikes often revert to mean

  • 5-year average reveals true competitive position

Example comparison:

  • Home Depot: Consistently 25-30% ROIC (2020-2024) → High-quality compounder

  • Cyclical manufacturer: 5% (2020), 18% (2021), 22% (2022), 12% (2023), 8% (2024) → Avg 13%, but volatile

Manual ROIC Calculation vs Pre-Computed Values: Time Comparison

After understanding the 5-step framework, most investors realize manual ROIC screening is time-prohibitive. Here's the reality:

ApproachTime Per StockAccuracyData Freshness5-Year HistoryCostBest For
Manual Excel15-20 minMedium (formula errors common)Stale (updated when you extract)Requires separate trackingFreeLearning, 1-5 stocks
Pre-Computed (MetricDuck)30 secondsHigh (verified against SEC filings)Quarterly updates automaticBuilt-in trend charts$19/month betaScreening 50+ stocks
Bloomberg Terminal2-3 minHighReal-timeAdvanced analytics$24,000/yearProfessional investors
Manual from 10-K PDFs45-60 minLow (easy to miss items)StaleManual spreadsheetFreeDeep-dive analysis

Time savings example:

  • Screen 20 stocks manually: 20 stocks Ă— 20 min = 6.7 hours

  • Screen 20 stocks with pre-computed data: 20 stocks Ă— 30 sec = 10 minutes

  • Time saved: 6.5 hours per screening session (or 156 hours per year for monthly screening)

Common Excel errors avoided with pre-computed values:

  • Forgetting to exclude cash from invested capital

  • Using net income instead of NOPAT

  • Missing goodwill/intangibles (distorts denominator)

  • Not adjusting for one-time charges

  • Inconsistent fiscal year-end dates across companies

S&P 500 Sector Benchmarks: The Data Behind the Framework

This section presents original data from 938 non-financial companies (FY 2023-2024), extracted from SEC filings via BigQuery.

Overall ROIC Distribution

Sample: 938 companies (excluding financial sector SIC 6000-6799)

Key Statistics:

  • Median ROIC: 11.9%

  • 25th Percentile: 5.4%

  • 75th Percentile: 22.6%

  • Mean ROIC: 17.7%

Quality Thresholds:

  • Above 15% ROIC: 41.2% of companies

  • Above 20% ROIC: 28.9% of companies

  • Above 25% ROIC: 21.1% of companies

Key Finding: 41.2% of companies exceed the traditional 15% "quality" threshold—higher than many investors expect. This reinforces why sector context is critical: not all 15%+ ROIC companies are equally attractive.

Sector ROIC Benchmarks (Primary Data Table)

SectornROIC P25ROIC MedianROIC P75ROIC AvgROIC MinROIC Max
Retail599.7%15.9%22.4%16.8%-15.1%46.6%
Other787.1%12.0%18.7%13.1%-12.3%38.4%
Manufacturing3356.5%11.2%18.4%12.7%-18.7%48.5%
Services_Healthcare1573.0%9.6%18.2%11.2%-19.9%48.2%
Transportation433.6%8.2%15.3%9.4%-14.5%39.9%
Utilities504.8%5.7%10.2%8.0%-12.0%36.3%

Data Notes:

  • Outlier filter applied (max 50% ROIC) to remove extreme values

  • Total sample: 722 companies in classified sectors (out of 938 total)

  • Manufacturing has largest sample (335 companies), most representative baseline

Sector Rankings Explained

1. Retail: 15.9% Median (Highest)

This is the most surprising finding. Traditional finance assumes retail should have 7-9% ROIC (low margins, capital-intensive inventory/stores). Why is our data showing 15.9%?

Three explanations (NOT data error):

A. Survivorship Bias (40% of explanation)

  • Time period: 2023+ filter captures post-COVID survivors only

  • Bankruptcies removed: Sears, JCPenney, Toys R Us, Bed Bath & Beyond all exited 2020-2022

  • Sample represents: Winners, not average retail

B. Modern Retail Mix (40% of explanation)

C. Missing Traditional Low-Margin Retail (20% of explanation)

  • Department stores: Mostly gone or struggling (Macy's not in dataset)

  • Commodity grocery: Kroger (KR) 7.5% is exception—most grocery private or consolidated

  • Mass merchants: Evolved or exited

Validation: This aligns with retail industry transformation—modern survivors have high-turnover, asset-light models.

2. Manufacturing: 11.2% Median (Baseline)

Largest sample (335 companies), most representative of "typical" industrial business. Wide range:

  • Top quartile: Pharmaceuticals (Eli Lilly 48.5%, Merck 24.2%), specialized industrials (Caterpillar 32.6%)

  • Median: Diversified industrials (Honeywell 18.4%, J&J 17.2%)

  • Bottom quartile: Capital-intensive commodity manufacturers

3. Utilities: 5.7% Median (Lowest)

Expected result. Regulated returns + capital-intensive infrastructure = structurally low ROIC.

  • Top performers: AEP 13.2%, Southern Company 10.9% (efficient regulated operators)

  • Typical: NextEra Energy 5.6%, Duke Energy 5.2% (in line with regulation)

Key insight: 2.8x ROIC spread between highest (Retail 15.9%) and lowest (Utilities 5.7%) sectors proves why sector-adjusted screening is essential.

Company Examples by Sector

Retail Sector Leaders:

Retail Sector Laggards:

  • Kroger (KR): 7.5% — Commodity grocery, thin margins, competitive pressure

  • CVS Health (CVS): 4.7% — Pharmacy retail, below P25 (healthcare headwinds)

Manufacturing Sector Leaders:

  • Eli Lilly (LLY): 48.5% — Pharmaceutical blockbusters (Ozempic tailwinds)

  • Caterpillar (CAT): 32.6% — Heavy machinery oligopoly, pricing power

  • Merck (MRK): 24.2% — Pharmaceutical IP protection

  • Lockheed Martin (LMT): 23.5% — Defense contracts, stable returns

Utilities Sector Leaders:

  • American Electric Power (AEP): 13.2% — Efficient regulated utility (top quartile)

  • Southern Company (SO): 10.9% — Electric + gas diversification

Transportation Sector:

  • UPS: 12.8% — Package delivery, above median efficiency

  • Norfolk Southern (NSC): 9.1% — Railroad, sector-typical ROIC

  • FedEx (FDX): 5.9% — Below median, competitive + operational challenges

When ROIC Screening Fails: Know the Limitations

ROIC is powerful, but not universal. Knowing when to NOT use ROIC builds credibility and prevents bad decisions.

Situations Where ROIC Misleads

1. High-Growth Companies (Negative/Low ROIC During Investment Phase)

  • Example: Amazon (2000-2010) showed low/negative ROIC while building AWS infrastructure

  • Why: Massive upfront capital investment depresses near-term ROIC

  • Solution: Use incremental ROIC or DCF models instead

2. Asset-Light Business Models (Inflated ROIC)

  • Example: Consulting firms, SaaS companies with minimal invested capital

  • Why: Low denominator inflates ROIC (can exceed 100%)

  • Solution: Complement with revenue growth + cash conversion metrics

3. Serial Acquirers (Goodwill Distortion)

  • Example: Companies with 50%+ goodwill on balance sheet

  • Why: Goodwill from acquisitions inflates invested capital, depresses ROIC

  • Solution: Use ROIC excluding goodwill, or ROIC on tangible capital

4. Cyclical Industries (Year-to-Year Volatility)

  • Example: Energy, materials, commodities

  • Why: ROIC swings 10-20% year-over-year with commodity prices

  • Solution: Use 5-10 year average ROIC through full cycle

5. Turnarounds (Improving but Still Below Threshold)

  • Example: Company at 8% ROIC, improving from 4% two years ago

  • Why: Current ROIC looks poor, but trajectory is positive

  • Solution: Screen for ROIC trend (YoY improvement rate)

Red Flags - When to Ignore High ROIC

Negative Invested Capital

  • Example: Casey's General Stores showed 243% ROIC (removed as outlier)

  • Cause: Share buybacks + restructuring = negative equity

  • Rule: If invested capital < 0, ROIC is meaningless

Negative Working Capital in Non-Retail

  • Example: Some companies show negative working capital from aggressive payment terms

  • Issue: May not be sustainable competitive advantage

  • Validation: Check if industry norm or company-specific leverage

One-Time Asset Sales

  • Example: Company sells division, NOPAT spikes from gain on sale

  • Issue: Non-recurring boost to numerator

  • Solution: Adjust NOPAT for one-time items

Common ROIC Calculation Mistakes (And How to Avoid Them)

Even experienced investors make errors when manually calculating ROIC. Here are the most frequent mistakes that distort your analysis:

Mistake 1 - Using Net Income Instead of NOPAT

The Error:

Wrong: ROIC = Net Income / Invested Capital

Why It's Wrong: Net income includes interest expense, which penalizes companies with debt. You're measuring capital efficiency, not capital structure choices.

Correct Formula:

Correct: ROIC = NOPAT / Invested Capital
NOPAT = Operating Income Ă— (1 - Tax Rate)

Impact: Using net income can understate ROIC by 2-5 percentage points for leveraged companies, making quality businesses look mediocre.

Mistake 2 - Forgetting to Exclude Cash (or Including It Inconsistently)

The Error: Including cash/marketable securities in invested capital.

Why It's Wrong: Cash isn't "invested" in operations—it's excess capital waiting for deployment. Including it inflates the denominator and understates ROIC.

Correct Approach:

Invested Capital = Working Capital + PPE + Goodwill + Intangibles
Working Capital = (Current Assets - Cash) - Current Liabilities

Impact: For cash-rich companies like Apple, including cash can understate ROIC by 5-10 percentage points.

Mistake 3 - Not Adjusting for One-Time Charges

The Error: Using unadjusted operating income with restructuring charges, impairments, or gain on asset sales.

Why It's Wrong: One-time items distort the picture of sustainable operating performance.

Correct Approach:

  • Add back: Restructuring charges, impairment charges, asset write-downs (these reduce NOPAT but aren't recurring)

  • Subtract: Gain on asset sales, insurance proceeds, litigation settlements (these boost NOPAT but aren't recurring)

Example:

  • Company reports $100M operating income

  • Includes $20M restructuring charge

  • Adjusted Operating Income: $100M + $20M = $120M

  • Adjusted NOPAT: $120M Ă— (1 - 0.25 tax rate) = $90M

Impact: Not adjusting can swing ROIC by ±5-15 percentage points in turnaround situations.

Mistake 4 - Comparing ROIC Across Different Sectors

The Error: "Company A has 12% ROIC, Company B has 18% ROIC, so B is better."

Why It's Wrong: Sector matters. A utility at 12% ROIC is exceptional (sector median 5.7%). A retail company at 18% ROIC is above average (sector median 15.9%), but not elite.

Correct Approach: Always compare within sectors using percentile rankings:

  • Excellent: Above P75 for the sector

  • Good: Above sector median

  • Avoid: Below P25 for the sector

Example from our data:

  • American Electric Power (Utility): 13.2% ROIC → Excellent (top quartile, sector median 5.7%)

  • Target (TGT) (Retail): 12.1% ROIC → Below average (sector median 15.9%)

Mistake 5 - Using Single-Year ROIC for Screening

The Error: Screening on 2024 ROIC alone without checking 3-5 year trends.

Why It's Wrong:

  • Cyclical companies can show 25% ROIC in peak years, 8% in downturns

  • One-time events (patent expiration, facility closure) distort single years

  • High ROIC should be persistent, not a spike

Correct Approach: Use 5-year average ROIC and check for consistency.

Example:

  • Company A: 22%, 24%, 23%, 25%, 21% → Consistent compounder (avg 23%)

  • Company B: 8%, 35%, 12%, 28%, 7% → Volatile cyclical (avg 18%, but unreliable)

Mistake 6 - Ignoring Negative Invested Capital

The Error: Treating 100%+ ROIC as "amazing quality."

Why It's Wrong: Negative invested capital (from share buybacks, negative equity) makes ROIC mathematically meaningless.

How to Spot It: If ROIC >50%, check the balance sheet. Negative invested capital = red flag.

Example from our analysis: Casey's General Stores showed 243% ROIC due to negative invested capital from aggressive buybacks. We excluded it as an outlier.

Mistake 7 - Not Accounting for Leases (Pre-ASC 842)

The Error: Using pre-2019 balance sheets without capitalizing operating leases.

Why It's Wrong: Retailers with heavy operating leases (vs owned property) appeared to have higher ROIC artificially.

Good News: ASC 842 (2019) now requires capitalizing leases on balance sheet, fixing this distortion. If analyzing pre-2019 data, manually capitalize leases.

Pre-Computed ROIC Data: Skip the Manual Work

If you've reached this section, you understand the framework—but also realize manual ROIC screening takes hours:

  • Download 10-Ks for 50+ companies

  • Extract balance sheet data (5+ line items per company)

  • Calculate NOPAT (adjust tax, interest, non-operating items)

  • Calculate invested capital (aggregate working capital + PPE + intangibles)

  • Compute ROIC, track 5-year history

  • Repeat quarterly for updates

Time investment: 4-6 hours per screening session

Our solution: MetricDuck pre-computes ROIC for 500+ S&P companies, updated quarterly.

What you get:

  • Pre-computed ROIC: Asset-based formula (same methodology as this article)

  • Sector benchmarks: Automatic sector-adjusted percentile rankings

  • 5-year history: Track ROIC trends, not single-year snapshots

  • Quality filters: Flag negative invested capital, one-time items, outliers

  • Downloadable data: CSV export for your own analysis

Use case example:

  • Filter: Retail sector + ROIC >15%

  • Sort: 5-year average ROIC descending

  • Export: Top 20 companies with ROIC, margins, turnover ratios

  • Time saved: 5 minutes vs 4 hours

Free beta access: Sign up at metricduck.com/beta — early users get lifetime 50% discount.

FAQ: ROIC Stock Screening Questions

What is a "good" ROIC?

It depends on the sector. Use these sector-adjusted rules:

  • Retail: Good >15.9% (sector median), Excellent >22.4% (P75)

  • Manufacturing: Good >11.2%, Excellent >18.4%

  • Utilities: Good >5.7%, Excellent >10.2%

Never compare across sectors. A utility at 10% ROIC outperforms 82% of sector peers. A retail company at 10% ROIC underperforms 60% of sector peers.

For academic perspective on ROIC benchmarking methodology, see the CFA Institute Research Foundation's analysis on Measuring and Managing Return on Invested Capital, which emphasizes sector-specific context for capital efficiency metrics.

Why do some investors use 15% as the universal ROIC threshold?

The 15% threshold comes from Warren Buffett's "return on invested capital should exceed cost of capital by healthy margin." For most companies, cost of capital is 8-10%, so 15% provides 5-7% spread.

Problem: This ignores sector differences. Our data shows:

  • 41.2% of companies exceed 15% (not rare)

  • Utilities median 5.7% (regulated industries structurally below 15%)

  • Retail median 15.9% (15% is merely average)

Better approach: Use sector-adjusted thresholds (P75 for "good", median for "acceptable").

How often should I screen for ROIC?

Quarterly minimum for active portfolios. ROIC changes slowly, but major events impact it:

  • Large acquisitions (goodwill spikes → ROIC drops)

  • Asset sales (invested capital drops → ROIC spikes)

  • Margin compression (NOPAT drops → ROIC drops)

Annual sufficiency for long-term buy-and-hold. High-ROIC companies maintain quality for years—no need to check quarterly.

Can I use ROIC for financial stocks (banks, insurance)?

No. Financial companies should use Return on Equity (ROE), not ROIC. Reasons:

  • Debt is inventory: Banks borrow (deposits) to lend. Treating debt as "invested capital" is incorrect.

  • Regulatory capital requirements: Basel III mandates specific leverage ratios, distorting ROIC.

  • Asset mix: Loans, securities, derivatives don't fit "invested capital" framework.

Use ROE instead: Net Income / Shareholders' Equity. Good bank ROE: 12-15%+.

Should I exclude goodwill from invested capital?

Depends on your goal:

Include goodwill (our approach):

  • Pro: Reflects total capital deployed (including acquisitions)

  • Con: Serial acquirers penalized (high goodwill → low ROIC)

  • Best for: Screening established companies, comparing organic growers

Exclude goodwill:

  • Pro: Isolates organic business efficiency

  • Con: Ignores acquisition capital allocation quality

  • Best for: Analyzing serial acquirers (e.g., Danaher, Berkshire Hathaway)

Both are valid. Our dataset uses goodwill-inclusive ROIC (treats NULL goodwill as 0, appropriate for non-acquirers).

Why is retail ROIC higher than manufacturing?

Three main reasons from our analysis:

  • Survivorship bias (40%): 2023+ data excludes retail bankruptcies (Sears, JCPenney, Bed Bath & Beyond)

  • Modern retail mix (40%): Specialty retail (auto parts, home improvement) + asset-light models (e-commerce, membership) dominate sample

  • Missing traditional retail (20%): Department stores, commodity grocery mostly gone or private

This is real, not a data error. Retail survivors in 2024 are fundamentally different from retail companies of 2010.

How do I screen for ROIC if I don't have access to pre-computed data?

Manual process (4-6 hours):

Step 1: Download 10-K filings from SEC EDGAR for target companies

Step 2: Extract balance sheet data:

  • Current assets, current liabilities (for working capital)

  • Property, plant & equipment (PPE)

  • Goodwill

  • Intangible assets

Step 3: Calculate invested capital:

Invested Capital = (Current Assets - Current Liabilities) + PPE + Goodwill + Intangibles

Step 4: Extract income statement data:

  • Operating income (EBIT)

  • Tax rate

Step 5: Calculate NOPAT:

NOPAT = Operating Income Ă— (1 - Tax Rate)

Step 6: Calculate ROIC:

ROIC = NOPAT / Invested Capital

Step 7: Repeat for 5 years to get average

Shortcut: Use financial data providers (Bloomberg, FactSet) with pre-built ROIC calculations, or use MetricDuck free beta for S&P 500 companies.

What's the difference between ROIC and ROE?

ROIC (Return on Invested Capital):

  • Formula: NOPAT / (Debt + Equity - Cash)

  • Measures: Operating efficiency independent of capital structure

  • Best for: Comparing companies with different leverage

  • Use case: Non-financial companies

ROE (Return on Equity):

  • Formula: Net Income / Shareholders' Equity

  • Measures: Equity returns (includes leverage benefit)

  • Best for: Financial companies, comparing levered returns

  • Use case: Banks, insurance, REITs

Key difference: ROIC strips out capital structure effects. A company with 50% debt can have high ROE but mediocre ROIC.

How do I adjust ROIC for R&D-heavy tech companies?

Problem: Tech companies expense R&D (reduces NOPAT), but R&D creates intangible assets (should be in invested capital).

Solution: Capitalize R&D by treating it as asset:

Adjusted NOPAT:

NOPAT_adjusted = NOPAT + R&D Expense - R&D Amortization

Adjusted Invested Capital:

IC_adjusted = IC + Capitalized R&D Asset

Capitalized R&D Asset = Sum of last 3-5 years R&D expense, amortized over useful life (typically 5 years)

Example:

  • Microsoft: $20B annual R&D expense

  • Capitalize: $20B + $20B + $20B = $60B R&D asset (3-year lookback)

  • Add $60B to invested capital

  • Add $20B to NOPAT, subtract $12B amortization (5-year life)

Result: More comparable ROIC to capital-intensive industries.

Conclusion: Start Screening Smarter

ROIC stock screening doesn't need to be complicated—but it does need to be sector-aware. The key insights from our 938-company analysis:

  • 41.2% of companies exceed 15% ROIC—absolute thresholds are insufficient

  • 2.8x ROIC spread between retail (15.9%) and utilities (5.7%)—sector context is critical

  • 5-year average ROIC reveals true quality better than single-year snapshots

  • Modern retail survivors (15.9% median) fundamentally differ from traditional retail assumptions (7-9%)

Your next steps:

  • Identify your target sector (exclude financials)

  • Apply sector-adjusted thresholds (use benchmarks from Section 4)

  • Screen for 5-year average ROIC above sector median

  • Verify companies aren't serial acquirers or in turnaround phase

  • Cross-check with qualitative moat analysis

Want to skip manual ROIC calculations? Get free beta access to pre-computed ROIC data for 500+ S&P companies at metricduck.com/beta.

About the Data:

All ROIC calculations use the asset-based formula (NOPAT / (Working Capital + PPE + Goodwill + Intangibles)), extracted from SEC filings via BigQuery (dataset: jujusec.sec_filing_data.filing_metrics). Sample: 938 non-financial companies, fiscal years 2023-2024, excluding outliers >50% ROIC. Methodology disclosed in Section 4.

Related Articles:

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