sector-analysis
Skill9 starsChanged 8 months agoMITView on GitHub
Sector classification, key metrics by industry, industry life cycle, competitive dynamics — frameworks for sector-level equity analysis. The Global Industry Classification Standard (GICS) provides a four-tier hierarchy: - 11 Sectors > 25 Industry Groups > 74 Industries > 163 Sub-Industries Technology / SaaS: Real Estate / REITs:
1 other project uses a version of this.
Adopted by
Most recently taken up by
- Serennity007/invest-skilltheir own version, first seen Aug 25, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- Serennity007/invest-skill★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository52 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- consolidationSkill
- deferred-taxesSkill
- gaap-standardsSkill
- hgb-standardsSkill
- ifrs-standardsSkill
- lease-accountingSkill
- revenue-recognitionSkill
- balanced-scorecardSkill
- deckungsbeitragsrechnungSkill
- investitionsrechnungSkill
- kostenrechnungSkill
- aml-kycSkill
- basel-iiiSkill
- mariskSkill
- sox-complianceSkill
- kpi-systemsSkill
- wertschoepfungskettenSkill
- covenant-analysisSkill
- credit-scoring-modelsSkill
- rating-methodologiesSkill
- econometricsSkill
- fiscal-policySkill
- labor-marketsSkill
- monetary-policy-analysisSkill
- trade-economicsSkill
- earnings-modelsSkill
- budgetingSkill
- cash-flow-forecastingSkill
- rolling-forecastsSkill
- scenario-planningSkill
- variance-analysisSkill
- solvency-iiSkill
- comparable-analysisSkill
- dcf-valuationSkill
- deal-structuringSkill
- lbo-modelingSkill
- pitch-book-creationSkill
- precedent-transactionsSkill
- corporate-tax-planningSkill
- international-taxSkill
- transfer-pricingSkill
- vat-optimizationSkill
- working-capitalSkill
- cap-table-analysisSkill
- lbo-modeling-detailSkill
- portfolio-management-peSkill
- startup-valuationSkill
- term-sheet-analysisSkill
- asset-allocationSkill
- estate-planningSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 151
Select sector-appropriate metrics: Use metrics table above for the relevant sector
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Sector-Specific Analysis
Sector classification, key metrics by industry, industry life cycle, competitive dynamics — frameworks for sector-level equity analysis.
When to Activate
- Analyzing a company within its sector context
- Identifying sector-specific KPIs and valuation metrics
- Comparing companies across an industry peer group
- Assessing industry structure and competitive dynamics
- Evaluating where an industry sits in its life cycle
- Porter's Five Forces analysis for a specific sector
- Screening for sector investment opportunities
Core Concepts
Sector Classification (GICS)
The Global Industry Classification Standard (GICS) provides a four-tier hierarchy:
- 11 Sectors > 25 Industry Groups > 74 Industries > 163 Sub-Industries
| Sector | Key Characteristics | Primary Valuation |
| Energy | Commodity-driven, cyclical, capital-intensive | EV/EBITDA, P/CF, NAV |
| Materials | Commodity exposure, cyclical | EV/EBITDA, P/B |
| Industrials | Economic cycle sensitive, diverse | P/E, EV/EBITDA |
| Consumer Discretionary | Consumer spending sensitive | P/E, EV/EBITDA, EV/Sales |
| Consumer Staples | Defensive, stable demand | P/E, Dividend Yield |
| Health Care | Regulatory risk, pipeline value | P/E, EV/Sales (biotech), DCF |
| Financials | Spread income, regulatory capital | P/E, P/B, P/TBV, Dividend Yield |
| Information Technology | Growth-oriented, scalable | EV/Sales, EV/EBITDA, P/E (if profitable) |
| Communication Services | Mix of growth and value | EV/EBITDA, P/E, EV/Subscriber |
| Utilities | Regulated returns, yield play | P/E, Dividend Yield, EV/RAB |
| Real Estate | Asset-based, income-generating | P/FFO, P/NAV, Cap Rate, Dividend Yield |
Sector-Specific Key Metrics
Banking:
| Metric | Formula | Benchmark |
| NIM (Net Interest Margin) | Net interest income / Avg earning assets | 1.0-3.0% (varies by region) |
| CET1 Ratio | CET1 capital / RWA | >12% comfortable |
| NPL Ratio | Non-performing loans / Total loans | <2% is healthy |
| Cost-to-Income | Operating expenses / Operating income | <50% excellent, <60% good |
| ROTE | Net income / Avg tangible equity | >10% value-creating |
| LDR (Loan-to-Deposit) | Gross loans / Customer deposits | 80-100% typical |
| Provision coverage | Loan loss provisions / NPLs | >70% adequate |
Technology / SaaS:
| Metric | Formula | Benchmark |
| ARR (Annual Recurring Revenue) | MRR x 12 | Growth rate > 30% is strong |
| NRR (Net Revenue Retention) | (Beginning ARR + expansion - contraction - churn) / Beginning ARR | >120% excellent, >100% good |
| DAU/MAU | Daily active / Monthly active users | >50% high engagement |
| CAC (Customer Acquisition Cost) | Sales & marketing / New customers | Payback < 18 months |
| LTV/CAC | Customer lifetime value / CAC | >3x healthy |
| Rule of 40 | Revenue growth % + EBITDA margin % | >40% is strong |
| Gross margin | Gross profit / Revenue | >70% for SaaS |
| Magic Number | Net new ARR / Prior quarter S&M spend | >1.0 efficient |
Real Estate / REITs:
| Metric | Formula | Benchmark |
| FFO (Funds From Operations) | Net income + D&A - gains on sales | Primary earnings metric |
| AFFO (Adjusted FFO) | FFO - maintenance capex - straight-line rent adj. | Cash flow proxy |
| NAV (Net Asset Value) | Market value of properties - debt | Intrinsic value |
| Cap Rate | NOI / Property value | 4-8% varies by property type |
| Occupancy Rate | Leased sqm / Total leasable sqm | >90% healthy |
| WALE | Weighted average lease expiry | >5 years = stability |
| LTV (Loan-to-Value) | Debt / Property value | <50% conservative |
Insurance:
| Metric | Formula | Benchmark |
| Combined Ratio | Loss ratio + Expense ratio | <100% = underwriting profit |
| Loss Ratio | Claims incurred / Premiums earned | Varies by line |
| Expense Ratio | Operating expenses / Premiums written | <30% efficient |
| Investment yield | Investment income / Avg invested assets | Depends on rate environment |
| Solvency II ratio | Own funds / SCR | >150% comfortable |
| Reserve adequacy | Actual claims / Estimated reserves | ~100% adequate |
Retail:
| Metric | Formula | Benchmark |
| SSSG (Same-Store Sales Growth) | YoY sales growth for stores open >12 months | >3% strong |
| Sales per sqm/sqft | Revenue / Selling area | Varies by format |
| Inventory turns | COGS / Avg inventory | Higher = more efficient |
| Gross margin | Gross profit / Revenue | Varies widely (25-60%) |
| GMROI | Gross profit / Avg inventory | >2.0x target |
| Conversion rate | Transactions / Foot traffic | Higher = better |
| Basket size | Revenue / Transactions | Track trend direction |
Industry Life Cycle
Revenue Growth
^
| Growth
| / \
| / Maturity
| / Shakeout \
Introduction | / \____ Decline
___ | / \
/ \ | / \
/ \__________| / \
────────────────────────────────────────────────> Time| Stage | Growth | Margins | Competition | Investment Focus |
| Introduction | Low/negative | Negative (investment phase) | Few players, high barriers | Product development, market creation |
| Growth | High (>20%) | Expanding | New entrants, increasing | Market share, capacity |
| Shakeout | Slowing | Pressure | Consolidation, exits | Efficiency, scale |
| Maturity | Low (GDP-like) | Stable/optimized | Oligopoly, stable | Cash return, maintenance |
| Decline | Negative | Eroding | Exits, substitution | Harvest, restructure |
Porter's Five Forces by Sector
Framework application:
- Threat of new entrants: Capital requirements, economies of scale, brand loyalty, regulatory barriers, network effects, switching costs
- Bargaining power of suppliers: Supplier concentration, input differentiation, switching costs, forward integration threat
- Bargaining power of buyers: Buyer concentration, price sensitivity, product differentiation, backward integration threat
- Threat of substitutes: Relative price/performance, switching costs, buyer propensity to substitute
- Rivalry among existing competitors: Number and size of competitors, industry growth, product differentiation, exit barriers, fixed costs
Sector examples:
| Force | Banking (High barriers) | SaaS (Network effects) | Retail Grocery (Low margins) |
| New entrants | Low (regulation, capital) | Medium (low capital, but network effects) | Medium (logistics, scale) |
| Supplier power | Low (depositors fragmented) | Low-Medium (cloud infra oligopoly) | Medium (branded goods) |
| Buyer power | Medium (switching costs) | Low-Medium (high switching costs) | High (price transparency) |
| Substitutes | Medium (fintech, BNPL) | Medium (alternative solutions) | Low (essential goods) |
| Rivalry | High (commoditized products) | High (winner-take-most) | Very high (price wars) |
Methodology
Sector Analysis Process
- Define the sector boundary: GICS classification, value chain positioning, adjacent sectors
- Map the industry structure: Key players, market shares, concentration (HHI), value chain
- Identify key drivers: Demand drivers (GDP, demographics, technology), supply dynamics (capacity, barriers)
- Assess competitive dynamics: Porter's Five Forces, competitive advantages by player
- Determine life cycle stage: Growth trajectory, margin trends, consolidation signals
- Select sector-appropriate metrics: Use metrics table above for the relevant sector
- Build peer comparison: Rank peers on key metrics, identify outliers and reasons
- Identify investment themes: Secular trends, disruption risks, regulatory changes
- Valuation framework: Apply sector-appropriate valuation multiples, cross-check with DCF
Peer Comparison
- Select 5-10 comparable companies (similar size, geography, business model)
- Standardize financials (calendar year alignment, currency, accounting policies)
- Calculate key metrics for all peers
- Rank and identify quartiles
- Analyze outliers: Why is company X above/below the peer median?
- Assess premium/discount justification
Templates
Sector Scorecard
Sector: _______________ Date: ___________
Industry Structure:
Market size (TAM): € ____________
Growth rate (5Y CAGR): ____________%
Top-5 market share: ____________%
HHI (concentration): ____________
Life cycle stage: [ ] Introduction [ ] Growth [ ] Maturity [ ] Decline
Porter's Five Forces (1=Low, 5=High):
New entrants: [_]
Supplier power: [_]
Buyer power: [_]
Substitutes: [_]
Rivalry: [_]
Overall intensity: [_]
Key sector metrics:
Metric 1 (________): Peer median ____ Range ____-____
Metric 2 (________): Peer median ____ Range ____-____
Metric 3 (________): Peer median ____ Range ____-____Peer Comparison Table
Company A Company B Company C Median Target Co.
Market cap (EURm) _______ _______ _______ _______ _______
Revenue growth ____% ____% ____% ____% ____%
Gross margin ____% ____% ____% ____% ____%
EBIT margin ____% ____% ____% ____% ____%
ROCE ____% ____% ____% ____% ____%
Sector metric 1 _____ _____ _____ _____ _____
Sector metric 2 _____ _____ _____ _____ _____
EV/EBITDA _____x _____x _____x _____x _____x
P/E _____x _____x _____x _____x _____x
Dividend yield ____% ____% ____% ____% ____%Quality Gate
- Sector boundary is clearly defined (GICS or custom definition)
- Industry structure is mapped (players, market shares, value chain)
- Key demand and supply drivers are identified
- Porter's Five Forces analysis is completed with sector-specific evidence
- Life cycle stage is assessed with supporting data
- Sector-appropriate metrics are selected (not generic ratios)
- Peer group is relevant (comparable size, geography, business model)
- Peer metrics are standardized for comparability
- Investment themes are identified with catalysts and risks
- Sector valuation approach matches industry convention
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

