Is high kurtosis good or bad?
Kurtosis is only useful when used in conjunction with standard deviation. It is possible that an investment might have a high kurtosis (bad), but the overall standard deviation is low (good). Conversely, one might see an investment with a low kurtosis (good), but the overall standard deviation is high (bad).
What does a high kurtosis mean?
outliers
Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. A uniform distribution would be the extreme case.
What is good and bad kurtosis?
If the kurtosis is greater than 3, then the dataset has heavier tails than a normal distribution (more in the tails). If the kurtosis is less than 3, then the dataset has lighter tails than a normal distribution (less in the tails).
How high is too high for kurtosis?
Data with a skew above an absolute value of 3.0 and kurtosis above an absolute value of 8.0 are considered problematic.
Is positive kurtosis good?
The higher the kurtosis coefficient is above the normal level—or the fatter the tails on the return distribution graph—the more likely that future returns will be either extremely large or extremely small.
Why is high kurtosis bad?
The risk that does occur happens within a moderate range, and there is little risk in the tails. Alternatively, the higher the kurtosis, the more it indicates that the overall risk of an investment is driven by a few extreme “surprises” in the tails of the distribution.
How much kurtosis is acceptable?
Acceptable values of skewness fall between − 3 and + 3, and kurtosis is appropriate from a range of − 10 to + 10 when utilizing SEM (Brown, 2006).
Which kurtosis has fat tails?
Leptokurtic distributions are statistical distributions with kurtosis greater than three. It can be described as having a wider or flatter shape with fatter tails resulting in a greater chance of extreme positive or negative events.
Is negative kurtosis good?
A negative kurtosis means that your distribution is flatter than a normal curve with the same mean and standard deviation. This means your distribution is platykurtic or flatter as compared with normal distribution with the same M and SD. The curve would have very light tails.
What if kurtosis is negative?
A distribution with a negative kurtosis value indicates that the distribution has lighter tails than the normal distribution. For example, data that follow a beta distribution with first and second shape parameters equal to 2 have a negative kurtosis value.
How do you interpret kurtosis?
For kurtosis, the general guideline is that if the number is greater than +1, the distribution is too peaked. Likewise, a kurtosis of less than –1 indicates a distribution that is too flat. Distributions exhibiting skewness and/or kurtosis that exceed these guidelines are considered nonnormal.” (Hair et al., 2017, p.
What does positive kurtosis tell us?
Positive values of kurtosis indicate that distribution is peaked and possesses thick tails. An extreme positive kurtosis indicates a distribution where more of the numbers are located in the tails of the distribution instead of around the mean.