Global Industry Classification Benchmark (GICS) in Peer Analysis (CFA Level 1): Understanding the Role of GICS in Peer Analysis, GICS Classification Structure, and Why GICS Matters for Peer Analysis. Key definitions, formulas, and exam tips.
If you’ve ever wondered how analysts figure out which companies truly belong together in a “peer group,” you’re not alone. I remember my early days as a newbie investment professional, scanning through lists of companies and thinking, “Wait, how is that bank considered a peer of that tech company?” Well, that confusion often stems from inconsistent classification methods. Enter GICS, or Global Industry Classification Benchmark, a standardized system that helps solve this mismatch by categorizing companies by their principal business activities. Let’s explore how GICS works, why it’s important, and how you can use it to refine your peer analysis.
GICS was developed by MSCI and S&P Global to bring some order to the chaos. It’s exhaustive and goes from very broad “sectors,” like Energy or Financials, all the way down to specialized “sub-industries.” This structured approach promotes apples-to-apples comparisons, ensuring that you’re analyzing, say, cloud software firms alongside other cloud software firms, rather than grouping them with—who knows—an electric utility or two.
At its simplest, GICS assigns companies to the sector and industry that best reflect their main revenue source. It then dives deeper into narrower categories called industry groups, industries, and, at the most specific level, sub-industries. This four-tiered hierarchy is meant to capture the specialization and nuances of different business models.
Below is a simple Mermaid diagram to illustrate the GICS layer structure:
flowchart TB
A["Sector <br/>(e.g., Information Technology)"] --> B["Industry Group <br/>(e.g., Software & Services)"]
B --> C["Industry <br/>(e.g., Software)"]
C --> D["Sub-Industry <br/>(e.g., Application Software)"]
In practice, you’ll often see analysts zero in on the “sub-industry” level for really detailed peer analysis. This makes sense: comparing an application software company to a semiconductor manufacturer (both in the Information Technology sector) might still be too broad because their drivers, challenges, and valuations differ significantly.
Picture building a fantasy sports team. You’d group players by position to compare their stats. You wouldn’t compare your star quarterback to a placekicker. GICS is essentially doing that for stocks, grouping them by their principal activities so that you can compare the “quarterbacks” to other “quarterbacks.”
Many analysts rely on GICS sub-industries for benchmarking stock performance, building market indexes, or constructing sector-based Exchange Traded Funds (ETFs). For instance, sector-based funds might only include companies whose GICS classification lines up with that sector, preserving purity in the overall portfolio.
One interesting challenge arises with large conglomerates, which might easily straddle multiple GICS categories. Let’s say we have a global behemoth that manufactures aircraft engines, invests in real estate, and operates a media streaming service. Where do you put that?
GICS methodology generally considers the dominant revenue driver. So if 60% of that conglomerate’s revenue comes from aviation manufacturing, it might land under the Industrials sector, Aerospace & Defense industry, even if the real estate or media divisions are also significant. While this approach isn’t perfect, it does force an objective look at where the bulk of a company’s business lies.
For peer analysis, though, you should always peek at segment disclosures (discussed in Chapter 1.8 on Segment Reporting Requirements) to see how diversified the conglomerate is. If some segment is overshadowing the primary GICS classification, you might refine how you treat that company when you build your peer universe. This is especially relevant for evaluating synergy or “hidden value” in cross-segment operations.
Your analysis is only as good as the peers you choose. If your comparison set is random—one software-as-a-service platform, an oil producer, and a pharmaceutical giant—your “benchmark” metrics won’t hold a whole lot of meaning. Using GICS ensures that:
From an exam perspective, keep in mind that constructing relevant peer groups is a fundamental skill. The CFA exam might present scenario-based questions where you must identify the most appropriate set of comparables. A GICS-based approach helps you rationalize your selection.
Analysts who manage sector-specific portfolios (like a Technology ETF) lean heavily on GICS to define their investable universe. GICS is often integrated directly into screens run by portfolio managers or quantitative analysts, who might use a code snippet similar to the following in Python to filter a database of equities:
1import pandas as pd
2
3data = {
4 'company': ['TechAlpha Inc', 'RetailMax Corp', 'EnergyNow LLC', 'CloudNinja Co'],
5 'gics_sector': ['Information Technology', 'Consumer Discretionary', 'Energy', 'Information Technology'],
6 'gics_industry_group': ['Software & Services', 'Retailing', 'Oil, Gas & Consumable Fuels', 'Software & Services'],
7 'gics_industry': ['Software', 'Broadline Retail', 'Integrated Oil & Gas', 'Software'],
8 'gics_sub_industry': ['Application Software', 'Department Stores', 'Integrated Oil & Gas', 'Application Software']
9}
10
11df = pd.DataFrame(data)
12
13tech_filtered = df[df['gics_sector'] == 'Information Technology']
14print(tech_filtered)
In this simple scenario, you’re instantly honing in on the relevant industry or sub-industry. For deeper peer analysis, you might filter for the exact sub-industry, like “Application Software,” to ensure that you’re comparing businesses with similar models (e.g., subscription-based software revenues, intangible R&D-driven assets, etc.).
Imagine you’re evaluating a potential investment in a medical device manufacturer. Let’s call them MediEquip Inc. Suppose you want to find a peer universe to compare revenue growth, operating margins, and R&D spend:
This process helps you develop more accurate valuations and more robust investment theses.
Even though GICS is standardized, make sure to watch out for:
Maybe this is obvious, but keep in mind that the classification is a starting point, not the final word. If you notice that your target firm’s business model is trending toward, say, clean energy, but it’s still listed under traditional Utilities, you might question if the classification is going to change soon. That’s often a key forward-looking question that can help you spot early investment opportunities or risks.
It also pays to think about how GICS aligns with the segment data you see in a company’s financial disclosures. Chapter 1.8 in this volume covers segment reporting requirements, and segment-level data might reveal shifts in revenue composition that GICS hasn’t caught up with yet. A seasoned analyst knows to read between the lines.
To grasp how two companies that share a GICS sector can vastly differ, here’s a simplified diagram:
flowchart LR
A["Tech Sector"] --> B["Software & Services Industry Group"]
A --> C["Tech Hardware & Equipment Industry Group"]
B --> D["Software Industry"]
C --> E["Technology Hardware, Storage & Peripherals Industry"]
D --> F["Application Software (Sub-Industry)"]
D --> G["Systems Software (Sub-Industry)"]
E --> H["Computer Hardware (Sub-Industry)"]
E --> I["Electronic Equipment (Sub-Industry)"]
Two companies might be in the same “Tech Sector,” but if one is in “Application Software” and the other is in “Computer Hardware,” their profit margins, capital expenditure needs, and R&D intensity may be worlds apart.
As environmental, social, and governance (ESG) considerations become increasingly integral (covered broadly in Chapter 15), GICS itself might adapt. Certain industries—like renewable energy integrators—fall into existing GICS buckets but carry different ESG risk profiles. While GICS wasn’t originally designed around ESG metrics, many data providers combine GICS with ESG overlays. Keep in mind that a “Utilities” classification could include both high-carbon-emitting traditional power companies and greener alternatives, which might require further sub-categorization in your analysis.
It’s funny—I learned about GICS classification almost by accident, while dealing with an index reconstitution that forced me to re-check a bunch of companies’ sector assignments. Initially, I was skeptical. Why not just pick companies that “felt” like they belonged together? Yet after some near-misses—like grouping a media streaming service with a music publisher—I realized that the systematic approach of GICS saved me from big analytical blind spots. Now I rely on GICS from the start, and it’s made my peer analysis a heck of a lot more robust.
Although GICS is a powerful tool, it’s not the only approach. Various classification systems (like NAICS, ICB, or Thomson Reuters Business Classification) exist. If you ever cross paths with them, keep the same spirit: look for systematic, revenue-driven sorting. The magic is in consistency. As an analyst, you need a stable framework to evaluate a company’s competitive position and performance metrics.
GICS is a globally recognized classification system that unites equities under broad sectors, narrower industry groups, even narrower industries, and the most specific sub-industries. It streamlines the process of forming peer groups, setting up industry benchmarks, and building sector-based investment strategies. Just remember the practical considerations: conglomerates, evolving business models, and classification timing can influence how accurate GICS designations are.
If you’re itching to learn more or confirm the details:
A thorough understanding of GICS is extremely helpful for both the CFA program and real-world financial analysis. It ensures that you, your team, and the broader investment community speak the same language when talking about “peer groups.”
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