What is the syntax for KURT in Excel?

The syntax for KURT is: =KURT(number1, [number2], ...)

What is kurtosis and what does KURT measure?

Kurtosis measures the 'tailedness' of a distribution - how much data is in the tails vs. the center. High kurtosis means heavy tails (more outliers), low kurtosis means light tails. Excel's KURT returns excess kurtosis (normal distribution = 0).

How do I interpret KURT values?

KURT=0: normal distribution tails. KURT>0 (leptokurtic): heavier tails, more outliers than normal. KURT<0 (platykurtic): lighter tails, fewer outliers. In finance, high kurtosis indicates higher risk of extreme events.

Why is kurtosis important in finance?

Financial returns often have high kurtosis ('fat tails'), meaning extreme gains/losses occur more often than normal distribution predicts. This is crucial for risk management - models assuming normal distribution underestimate tail risk.

Statistical

KURT Function in Excel

Q: What is the KURT function in Excel?

Returns the kurtosis of a data set, measuring the peakedness of the distribution.

Q: Why is kurtosis important in finance?

Financial returns often have high kurtosis ('fat tails'), meaning extreme gains/losses occur more often than normal distribution predicts. This is crucial for risk management - models assuming normal distribution underestimate tail risk.

Returns the kurtosis of a data set, measuring the peakedness of the distribution.

Syntax

=KURT(number1, [number2], ...)

Arguments

number1 (required): First number or range
number2 (optional): Additional numbers or ranges

Examples

=KURT(A1:A100) - Kurtosis - Result: Kurtosis value

KURT for data analysis

Confirm whether you need entire columns, filtered subsets, or distinct values.
Use [COUNTIFS](/functions/countifs/) and [SUMIFS](/functions/sumifs/) for multi-criteria metrics.
Pivot tables complement single-cell statistical formulas for exploration.

Common errors

Needs at least 4 data points

Use cases

Distribution shape
Risk analysis
Data characterization

Frequently asked questions

What is kurtosis and what does KURT measure? Kurtosis measures the 'tailedness' of a distribution - how much data is in the tails vs. the center. High kurtosis means heavy tails (more outliers), low kurtosis means light tails. Excel's KURT returns excess kurtosis (normal distribution = 0).
How do I interpret KURT values? KURT=0: normal distribution tails. KURT>0 (leptokurtic): heavier tails, more outliers than normal. KURT<0 (platykurtic): lighter tails, fewer outliers. In finance, high kurtosis indicates higher risk of extreme events.
Why is kurtosis important in finance? Financial returns often have high kurtosis ('fat tails'), meaning extreme gains/losses occur more often than normal distribution predicts. This is crucial for risk management - models assuming normal distribution underestimate tail risk.

Editorial review

Reviewed by Excel.Directory Editorial Team. Updated May 2026.