Fundamental analysis · Intermediate

Sector and Industry Analysis

A number that looks alarming in one industry is unremarkable in the next, which is the whole reason sector comes before ratios.

Last reviewed 15 September 2026 by the MarketPro research desk · Editorial policy

In short

Sector analysis groups companies by what they do and asks how each group responds to the same economic conditions. It matters because the same financial ratio carries different risk in different industries, and because sectors respond in opposite directions to the same interest rate move. Its most reliable use is checking whether your positions are genuinely independent rather than one sector bet held in several instruments.

What to remember

Leverage of 4x EBITDA is routine for a regulated utility and dangerous for a software company. The ratio is identical, the consequence is not.
Utilities are defensive against a demand shock and highly exposed to a rate shock, because they are valued like bonds.
Rotation models require knowing where in the cycle you are, which is the hard part of the problem rather than a given.
Five technology holdings are one position at five times the size, and correlations rise exactly when diversification is most needed.

Lesson 15 of 24 in Fundamental analysis

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Sector analysis groups companies by what they do, then asks how each group responds to the same economic conditions. It exists because the answer differs enormously. A rate rise that squeezes one sector's earnings can expand another's, and a number that looks alarming in one industry is unremarkable in the next.

Why net debt of 4x earnings is fine in one sector and alarming in another

A regulated water utility carries net debt of four times EBITDA. Its revenue is set by a regulator for five years at a time, demand does not fall in a recession, and its assets are pipes that will exist in fifty years. Lenders price that predictability, so it borrows cheaply and long.

A software company with the same 4x leverage is in a different situation entirely. Its revenue depends on customers renewing contracts, its main asset is people who can resign, and a 20% revenue decline is possible in a way it simply is not for a water supplier. Same ratio, different exposure.

Run the arithmetic on a downturn. Suppose EBITDA falls 25%. The utility's leverage goes from 4.0x to 5.3x and it renegotiates with lenders who have seen this before. The software company's leverage goes from 4.0x to 5.3x as well, but its covenant was set assuming growth, its cost base is mostly salaries it must cut publicly, and its equity is priced on a growth multiple that now has to reset. The ratio moved identically. The consequence did not. This is the entire practical argument for looking at sector before looking at ratios.

Cyclical and defensive, and what the labels actually predict

Type	Examples	Behaviour
Cyclical	Industrials, consumer discretionary, materials, banks	Amplifies the economic cycle in both directions
Defensive	Utilities, consumer staples, healthcare	Demand persists through downturns, smaller drawdowns
Rate-sensitive	Real estate, utilities, long-duration growth	Reprices on bond yields more than on earnings
Commodity-linked	Energy, mining	Tracks the underlying commodity more than the equity market

Note that a sector can appear in two rows. Utilities are defensive against a demand shock and highly exposed to a rate shock, because they are valued like bonds and carry large debt loads. In 2022 that combination meant a defensive sector fell alongside everything else, which surprised people who had learned the label and not the mechanism.

The commodity row carries a similar warning. An energy producer is often described as an equity holding, but over most periods its share price correlates more closely with the price of crude than with the equity index it sits in. That makes it a commodity position wearing an equity label, and if you already hold exposure to oil elsewhere you have doubled a bet you may believe you have diversified. The label describes what the company does. It does not describe what the share price responds to, and those are different questions.

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Rotation is a description, not a schedule

Sector rotation describes the observed tendency for money to move between sectors as conditions change: cyclicals early in a recovery, energy and materials late in an expansion, defensives into a slowdown. As a description of what has happened it is reasonable. As a timing tool it is close to useless.

The reason is that the cycle is only datable in hindsight. You do not know you were in a late expansion until the slowdown has arrived, by which point the rotation has already happened. Anyone selling a sector rotation model is implicitly claiming to know where in the cycle you currently are, and that is the hard part of the problem, not the mapping from cycle stage to sector.

The classification problem nobody mentions

A large online retailer is classified as consumer discretionary, while a large part of its profit comes from cloud computing. Its sector label describes less than half its earnings.
Classification providers reshuffle sectors periodically. Communication services was created in 2018 by moving companies out of technology and consumer discretionary, which broke every historical sector comparison across that date.
Many large companies operate across several sectors, so the label reflects the largest revenue line rather than the driver of the share price.

The practical response is to check what actually drives a company's earnings rather than trusting the label. That takes five minutes with a revenue breakdown and it prevents the more common error of assuming a diversified portfolio because the sector tags differ.

Using sector as a correlation check

The most reliable use of sector analysis has nothing to do with picking winners. It is a check on whether your positions are actually independent. Holding five technology companies is not five positions, it is one position on the technology sector at five times the size, and it will behave that way on the day the sector moves.

The same trap appears across asset classes. Long an oil-linked currency, long an energy producer and long crude is one trade in three instruments. Correlations also tend to rise in stressed conditions, so the diversification you measured in calm markets is weakest exactly when you need it. Counting correlated positions once is the rule that follows from this, and the drawdown calculator shows what happens when it is ignored.

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Written and reviewed by the MarketPro research desk

MarketPro is a trading-signal and trading-education app operated by Harajuku Holdings LTD (Cyprus). Our signal desk publishes and tracks every trade idea in-app, and every page here is checked against the app's live behaviour before publishing. Last reviewed 15 September 2026. How we produce signals and content · About MarketPro

FAQ

Sector and Industry Analysis: questions

What is the difference between a sector and an industry?

A sector is the broad grouping, such as technology or healthcare. An industry is a subdivision within it, such as semiconductors or pharmaceuticals. The distinction matters because companies in the same sector can have very different economics: a semiconductor manufacturer is highly cyclical and capital-intensive while a software company in the same technology sector is neither.

Which sectors do well when interest rates rise?

Banks often benefit, because they can widen the gap between what they charge borrowers and pay depositors, though that reverses if higher rates cause loan losses. Sectors that suffer most are those valued on distant future cash flows and those carrying heavy debt, including real estate, utilities and unprofitable growth companies. These are tendencies with plenty of historical exceptions rather than rules.

Is sector rotation a reliable strategy?

The pattern it describes is real in historical data, but acting on it requires knowing which stage of the economic cycle you are currently in, and that is only clear in hindsight. By the time a slowdown is confirmed, the rotation into defensive sectors has usually already happened. It is more useful as an explanation of past moves than as a forward-looking allocation tool.

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