Direct Answer
Breadth counted across market sectors, commonly the percent of the 11 sectors whose index or ETF trades above a moving average, or has a positive return over a set period. It shows how widely strength is spread across the economy. A high percentage means most sectors are trending up together, while a low one shows narrow leadership.
Sector Breadth: Formula, Meaning, Signals, Examples and How to Use It
How Is Sector Breadth Calculated?
Breadth counted across market sectors, commonly the percent of the 11 sectors whose index or ETF trades above a moving average, or has a positive return over a set period. It shows how widely strength is spread across the economy.
Formula: Sector breadth % = sectors meeting the positive condition / total sectors x 100
Inputs:
- Sector index or ETF price series
- Condition test, for example above the 50-day average
- Number of sectors in the classification
Worked example. If 8 of 11 sectors are above their 50-day averages, sector breadth is 72.7%. The inputs are illustrative numbers, not market data.
Reading it. A high percentage means most sectors are trending up together, while a low one shows narrow leadership. Because there are only about a dozen sectors, each one moves the figure by roughly nine points.
Limits. With so few components the series is coarse and jumps in large steps. Sector indexes are cap-weighted, so a few giant stocks can set the trend of a whole sector.
What is Sector Breadth?
Breadth counted across market sectors, commonly the percent of the 11 sectors whose index or ETF trades above a moving average, or has a positive return over a set period. It shows how widely strength is spread across the economy.
How to use Sector Breadth
A high percentage means most sectors are trending up together, while a low one shows narrow leadership. Because there are only about a dozen sectors, each one moves the figure by roughly nine points. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- With one yes-or-no test per sector, the percentage maps cleanly to a count, such as 8 of 11 sectors above their 50-day average.
- Sector ETFs or indexes cover the full market in a handful of series, which makes the calculation compact and easy to verify by hand.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- A sector's single vote is the same whether it is a small or a very large share of the market, so a minor sector can offset a major one.
- The sector composition of an index changes when the classification scheme is revised, which can alter history without any price move.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance.
Frequently Asked Questions
Is Sector Breadth a buy or sell signal?
No. A high percentage means most sectors are trending up together, while a low one shows narrow leadership. With so few components the series is coarse and jumps in large steps. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Sector Breadth?
Sector Breadth takes these inputs: sector index or ETF price series; condition test, for example above the 50-day average; number of sectors in the classification. There is no universal best setting for the tunable ones, so test them across instruments, regimes and out-of-sample periods and favor stable parameter regions over one historical winner.
Can Sector Breadth be used by itself?
With so few components the series is coarse and jumps in large steps. Sector indexes are cap-weighted, so a few giant stocks can set the trend of a whole sector. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Sector Breadth work on every timeframe?
The calculation (Sector breadth % = sectors meeting the positive condition / total sectors x 100) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Sector Breadth give false signals?
A sector's single vote is the same whether it is a small or a very large share of the market, so a minor sector can offset a major one. The sector composition of an index changes when the classification scheme is revised, which can alter history without any price move. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Sector Breadth be backtested?
Rebuild Sector Breadth from sector index or ETF price series using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.