# Kurtosis

Kurtosis is a measure of the return distribution. In a similar way to the concept of skewness, kurtosis is a descriptor of the shape of a return distribution. There are various interpretations of kurtosis, and of how particular measures should be interpreted; these are primarily peakedness (width of peak), tail weight, and lack of shoulders (distribution primarily peak and tails, not in between).The Kurtosis Technical Analysis lookup allows you to check this and other technical indicators across multiple equities. You can select from a set of available technical indicators by clicking on the link to the right. Please note, not all equities are covered by this module due to inconsistencies in global equity categorizations and data normalization technicques. Please check also Equity Screeners to view more equity screening tools
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Kurtosis is a measure of the return distribution. In a similar way to the concept of skewness, kurtosis is a descriptor of the shape of a return distribution. There are various interpretations of kurtosis, and of how particular measures should be interpreted; these are primarily peakedness (width of peak), tail weight, and lack of shoulders (distribution primarily peak and tails, not in between).

## Kurtosis  = 4PM STD4

A high kurtosis typically shows a distribution of returns with fat tails, whereas a low kurtosis portrays a distribution with skinny tails or a distribution concentrated toward the mean.

## Kurtosis In A Nutshell

Data is usually distributed normally which means if you take a visual depiction of the data it would look like a bell shaped curve. If looking at statistics, a normal distribution is desired because this will give you best opportunity to find where standard deviations are along with other measures depending on the data.

When looking at data, it is important to understand how it is laid out and if everything seems appropriate. Skewness and distribution of data around the mean is key and Kurtosis helps with measuring that.

## Closer Look at Kurtosis

There are a few different kinds of Kurtosis, so let us start with Leptokurtic. Visually, this is when the bell shape is skinny and tall compared to a normal bell curve distribution. What this can indicate is that the data is really close together and data falls off drastically sooner in relation to the mean.

Secondly there is Mesokurtic, and this appears with a fatter and shorter bell curve, indicate the data may be spread out further. Standard deviations and other statistical data will be different but that does not mean it will be incorrect.

Lastly, there is Platykurtic, which means the bell in the middle is really evened out and that could indicate data is further dispersed than all the other variations. However, just like the others, this does not mean it is positively or negatively affecting the research.

With Kurtosis, it allows people to view data and the skewness and begin taking it apart. Be sure to fully understand the statistical data and what you are searching for because it will vary between each investor and trader. Take a look through Macroaxis as well as other Internet articles as this may not be for all investors. Test it out on a demo account and see if it fits your current investing style. Kurtosis has been around for quite some time and will continue to be a tool in the toolbox of finance.