Direct Answer

The Herfindahl concentration index is the sum of the squared portfolio weights. It rises as capital concentrates in fewer positions and equals 1 divided by n when n holdings are weighted equally. It ranges from 1/n (equal weights) to 1 (one holding).

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Herfindahl Concentration Index: Formula, Meaning, Signals, Examples and How to Use It

How Is Herfindahl Concentration Index Calculated?

The Herfindahl concentration index is the sum of the squared portfolio weights. It rises as capital concentrates in fewer positions and equals 1 divided by n when n holdings are weighted equally.

Formula: HHI = sum of w_i^2, with weights w_i summing to 1; effective number of holdings = 1 / HHI

Inputs:

Worked example. Weights of 40%, 30%, 20% and 10% give a Herfindahl index of 0.30. The inputs are illustrative numbers, not market data.

Reading it. It ranges from 1/n (equal weights) to 1 (one holding). Taking 1 / HHI gives an effective number of equally weighted holdings, so an index of 0.30 behaves like about 3.3 positions.

Limits. It measures weight concentration only, not risk concentration: two holdings can have small weights yet be highly correlated. Weights depend on whether cash and derivatives are included.

What is Herfindahl Concentration Index?

The Herfindahl concentration index is the sum of the squared portfolio weights. It rises as capital concentrates in fewer positions and equals 1 divided by n when n holdings are weighted equally.

How to use Herfindahl Concentration Index

It ranges from 1/n (equal weights) to 1 (one holding). Taking 1 / HHI gives an effective number of equally weighted holdings, so an index of 0.30 behaves like about 3.3 positions. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.

Strengths

Weaknesses and limitations

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 Herfindahl Concentration Index a buy or sell signal?

No. It ranges from 1/n (equal weights) to 1 (one holding). It measures weight concentration only, not risk concentration: two holdings can have small weights yet be highly correlated. 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 Herfindahl Concentration Index?

Herfindahl Concentration Index is computed from portfolio weights summing to 100%; number of holdings, so the choices that matter are the data convention and the window it is read over. Test those across instruments, regimes and out-of-sample periods instead of fitting one historical winner.

Can Herfindahl Concentration Index be used by itself?

It measures weight concentration only, not risk concentration: two holdings can have small weights yet be highly correlated. Weights depend on whether cash and derivatives are included. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.

Does Herfindahl Concentration Index work on every timeframe?

The calculation (HHI = sum of w_i^2, with weights w_i summing to 1; effective number of holdings = 1 / HHI) 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 Herfindahl Concentration Index give false signals?

The index has a floor of 1/n set by the number of holdings, so it must be read with the holdings count rather than as an absolute level. Because it uses weights at one date, drift from market moves changes the value without any trading. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.

How should Herfindahl Concentration Index be backtested?

Rebuild Herfindahl Concentration Index from portfolio weights summing to 100% 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.

Swoopr Editorial Team

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