Syntax
KURT(value1, [value2, ...])
| Parameter | Description |
|---|---|
| value1 | Parameter of the KURT function. |
| [value2 | (Optional.) Parameter of the KURT function. |
| ...] | Parameter of the KURT function. |
Examples
Stock return kurtosis
Formula
=KURT(C2:C253)
Positive kurtosis for stock returns indicates fat tails — extreme gains and losses occur more often than a normal distribution would predict.
Manufacturing quality
Formula
=KURT(B2:B500)
Negative kurtosis means measurements cluster tightly around the mean with few outliers — indicating a well-controlled process.
Normality check
Formula
=ABS(KURT(D2:D1000)) < 1
Returns TRUE if excess kurtosis is near zero, suggesting the data is approximately normally distributed.
Common Errors
#DIV/0!
Fewer than 4 data points. Kurtosis requires at least 4 numeric values.
#VALUE!
Non-numeric direct arguments.
Tips
Excess kurtosis
KURT returns excess kurtosis (normal distribution = 0). Some texts use raw kurtosis where normal = 3. If you need raw kurtosis, add 3 to the result.
Risk management
High positive kurtosis (fat tails) means extreme events are more likely than normal assumptions predict. This is critical in financial risk models — ignoring fat tails led to underestimating risk in the 2008 crisis.
Pair with SKEW
Use SKEW and KURT together to characterize a distribution. Skewness tells you about asymmetry, kurtosis about tail heaviness.
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