# Leptokurtic Distributions Explained: Features, Examples, and Comparisons

![Leptokurtic Distributions](https://www.investopedia.com/thmb/r_KjyGDcgrHXKrHKF6cykj8Swuo=/1500x0/filters:no_upscale():max_bytes(150000):strip_icc()/leptokurtic-final-3a34f0dd24ad48b4a2c3d636f97a2b35.png)

*— Investopedia / Zoe Hansen*

## What Is Leptokurtic?

A leptokurtic distribution is a tool used in technical analysis. It is a type of data distribution with a high peak and fatter tails, meaning its kurtosis is greater than three. This shows a higher chance of extreme events compared to a normal distribution, which has a kurtosis of three (or a [platykurtic](https://www.investopedia.com/terms/p/platykurtic.asp) distribution), which is flatter with thinner tails. Understanding leptokurtic distributions is important for investors because it highlights the potential for unusual or extreme outcomes.

### Key Takeaways

*   Leptokurtic distributions have a kurtosis greater than three, indicating fatter tails and more extreme events compared to a normal distribution.
*   They present a higher probability of extreme outlier values, which can mean more risk for investors analyzing historical returns.  
    
*   Leptokurtic distributions can impact the value at risk, often resulting in lower confidence levels for risk assessments.  
    
*   Mesokurtic distributions have kurtosis near three, while platykurtic distributions have thinner tails and less kurtosis than normal distributions.  
    
*   Risk-seeking investors might prefer leptokurtic distributions, as they increase the chances of experiencing rare, high-impact events.

## How Leptokurtic Distributions Work

Leptokurtic distributions are distributions with positive kurtosis larger than that of a normal distribution. A normal distribution has a kurtosis of exactly three. Therefore, a distribution with kurtosis greater than three would be labeled a leptokurtic distribution.

In general, leptokurtic distributions have heavier tails or a higher probability of extreme outlier values when compared to mesokurtic or platykurtic distributions.

When analyzing [historical returns](https://www.investopedia.com/terms/h/historical-returns.asp), kurtosis can help an investor gauge an asset's level of risk. A leptokurtic distribution means that the investor can experience broader fluctuations (e.g., three or more standard deviations from the mean) resulting in greater potential for extremely low or high returns.

![Kurtosis](https://www.investopedia.com/thmb/zXm_GDtdwbGKWuk08ic2eowce_c=/1500x0/filters:no_upscale():max_bytes(150000):strip_icc()/Clipboard01-2a6874226cc84d7da3ffb407b3e1ae1c.jpg)

*Kurtosis.*

## Analyzing Value at Risk with Leptokurtic Distributions

Leptokurtic distributions can be involved when analyzing [value at risk (VaR)](https://www.investopedia.com/terms/v/var.asp) probabilities. A [normal distribution](https://www.investopedia.com/terms/n/normaldistribution.asp) of VaR can provide stronger result expectations because it includes up to three kurtoses. In general, the fewer the kurtosis and the greater the confidence within each, the more reliable and safer a value at risk distribution is.

Leptokurtic distributions are known for going beyond three kurtoses. This typically decreases the confidence levels within the excess kurtosis, creating less reliability. Leptokurtic distributions can also show a higher value at risk in the left tail due to the larger amount of value under the curve in the worst-case scenarios. Overall, a greater probability for negative returns farther from the mean on the left side of the distribution leads to a higher value at risk.

## Comparing Leptokurtosis to Mesokurtosis and Platykurtosis

While leptokurtosis refers to greater outlier potential, mesokurtosis and platykurtosis describe lesser outlier potential. Mesokurtic distributions have kurtosis near 3.0, meaning that their outlier character is similar to that of the normal distribution. Platykurtic distributions have kurtosis less than 3.0, thus exhibiting less kurtosis than a normal distribution.

Investors will consider which statistical distributions are associated with different types of investments when deciding where to invest. More [risk-averse](https://www.investopedia.com/terms/r/riskaverse.asp) investors might prefer assets and markets with platykurtic distributions because those assets are less likely to produce extreme results, while risk-seekers may seek leptokurtosis.

## Real-World Example of Leptokurtic Distributions

Let's use a hypothetical example of excess positive kurtosis. If you track the closing value of [stock](https://www.investopedia.com/terms/s/stock.asp) ABC every day for a year, you will have a record of how often the stock closed at a given value. If you build a graph with the closing values along the X-axis and the number of instances of that closing value that occurred along the Y-axis of a graph, you will create a bell-shaped curve showing the distribution of the stock's closing values. If there are a high number of occurrences for just a few [closing prices](https://www.investopedia.com/terms/c/closingprice.asp), the graph will have a very slender and steep bell-shaped curve. If the closing values vary widely, the bell will have a wider shape with less steep sides. The tails of this bell will show you how often heavily deviated closing prices occurred, as graphs with lots of outliers will have thicker tails coming off each side of the bell.

## The Bottom Line

Leptokurtic distributions are technical trading tools with high peaks and heavy tails. This means they are more likely to produce extreme values than normal (mesokurtic) or flatter (platykurtic) distributions. These distributions are important for investors because they show the potential for big gains or losses. Investors can use leptokurtic distributions to assess risk and choose investments that match their risk tolerance, whether they prefer safer options or are willing to take chances for higher returns.