Kurtosis is a statistical measure that is used to describe the size of the tails on a distribution. Excess kurtosis helps determine how much risk is involved in a specific investment.
What is kurtosis in finance?
In finance, kurtosis is used as a measure of financial risk. A large kurtosis is associated with a high risk for an investment because it indicates high probabilities of extremely large and extremely small returns. On the other hand, a small kurtosis signals a moderate level of risk because the probabilities of extreme returns are relatively low.
What is the excess kurtosis in a platykurtic distribution?
The excess kurtosis in a platykurtic distribution is negative that is characterized by a flat-tail distribution. The minor outliers in a distribution are indicated by the flat tails. The platykurtic distribution of investment returns is advantageous for investors in the financial context as this would mean a higher return on investment.
What are the types of kurtosis?
The types of kurtosis are determined by the excess kurtosis of a particular distribution. The excess kurtosis can take positive or negative values as well, as values close to zero. Data that follows a mesokurtic distribution shows an excess kurtosis of zero or close to zero.
What is mesokurtic kurtosis?
If the kurtosis of data falls close to zero or equal to zero, it is referred to as Mesokurtic.
What does kurtosis mean for stocks?
Kurtosis is a statistical measure that is used to describe the size of the tails on a distribution. Excess kurtosis helps determine how much risk is involved in a specific investment.
What does the kurtosis tell you?
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 a good kurtosis level?
2.3. A standard normal distribution has kurtosis of 3 and is recognized as mesokurtic. An increased kurtosis (>3) can be visualized as a thin “bell” with a high peak whereas a decreased kurtosis corresponds to a broadening of the peak and “thickening” of the tails. Kurtosis >3 is recognized as leptokurtic and <3.
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 is high kurtosis?
High kurtosis in a data set is an indicator that data has heavy tails or outliers. If there is a high kurtosis, then, we need to investigate why do we have so many outliers. It indicates a lot of things, maybe wrong data entry or other things.
What does a kurtosis of 5 mean?
Definition of Kurtosis Distributions with large kurtosis exhibit tail data exceeding the tails of the normal distribution (e.g., five or more standard deviations from the mean). Distributions with low kurtosis exhibit tail data that are generally less extreme than the tails of the normal distribution.
Is negative kurtosis good?
Negative excess values of kurtosis (<3) indicate that a distribution is flat and has thin tails. Platykurtic distributions have negative kurtosis values. A platykurtic distribution is flatter (less peaked) when compared with the normal distribution, with fewer values in its shorter (i.e. lighter and thinner) tails.
Why is kurtosis so important?
Kurtosis is used as a measure to define the risk an investment carries. The nature of the investment to generate higher returns can also be predicted from the value of the calculated kurtosis. The greater the excess for any investment data set, the greater will be its deviation from the mean.
What is a large kurtosis?
A large kurtosis is associated with a high level of risk for an investment because it indicates that there are high probabilities of extremely large and extremely small returns. On the other hand, a small kurtosis signals a moderate level of risk because the probabilities of extreme returns are relatively low.
How is kurtosis determined?
The types of kurtosis are determined by the excess kurtosis of a particular distribution. The excess kurtosis can take positive or negative values, as well as values close to zero.
What is the difference between skewness and kurtosis?
However, the two concepts must not be confused with each other. Skewness essentially measures the symmetry of the distribution, while kurtosis determines the heaviness of the distribution tails. In finance, kurtosis is used as a measure of financial risk.
What is a leptokurtic distribution?
Leptokurtic indicates a positive excess kurtosis. The leptokurtic distribution shows heavy tails on either side, indicating large outliers. In finance, a leptokurtic distribution shows that the investment returns may be prone to extreme values on either side.
What does excess kurtosis mean?
Excess kurtosis closer to zero or a flat deviation from the mean depicts that the investment will have a lesser probability of generating high returns. This can be used to define the financial risk of the investment. For investment advisors, kurtosis is a crucial factor in defining the investment risk associated with the portfolio of the fund.
What is a high kurtosis?
From the perspective of investors, high kurtosis of the return distribution implies that an investment will yield occasional extreme returns. This can swing both the ways that are either positive returns of extreme negative returns. Thus such an investment carried high risk. Such a phenomenon is known as kurtosis risk.
What does it mean when a kurtosis is negative?
When it is negative, it indicates that the deviation of the data set from the mean is flat.
What is a Platykurtic curve?
Whenever the kurtosis is less than zero or negative, it refers to Platykurtic. The distribution set follows the subtle or pale curve, and that curve indicates the small number of outliers in a distribution. An investment falling under platykurtic is usually demanded by investors because of a small probability of generating an extreme return.
What does it mean when a data set is a mesokurtic distribution?
If the kurtosis of data falls close to zero or equal to zero, it is referred to as Mesokurtic. This means that the data set follows a normal distribution. The blue line in the above picture represents a Mesokurtic distribution. In finance, such a pattern depicts risk at a moderate level.
What is the difference between a kurtosis and a curve shifted to the right?
If the curve shifts to the right, it is considered positive skewness, while a curve shifted to the left represents negative skewness. read more. is a measure of symmetry in distribution, whereas the kurtosis is the measure of heaviness or the density of distribution tails.
What is a leptokurtic distribution?
In terms of finance, a leptokurtic distribution shows that the return on investment may be highly volatile on a huge scale on either side. An investment following leptokurtic distribution is said to be a risky investment, but it can also generate hefty returns to compensate for the risk.
What is KURTOSIS?
The aggregate weight of a allotment's tails compared to the center of the distribution is measured by kurtosis. A bell peak is shown with most data within three standard deviations within + or - variations of the mean and can be seen when normal data is graphed using a histogram.
What are different types of Kurtosis?
The excess kurtosis of a given distribution determines the forms of kurtosis. Excess kurtosis can be either positive or negative, as well as near to zero.
What is excess kurtosis?
Kurtosis is a statistical measure that is used to describe the size of the tails on a distribution. Excess kurtosis helps determine how much risk is involved in a specific investment.
Why is excess kurtosis important?
It is an important consideration to take when examining historical returns from a particular stock or portfolio.
What is platykurtic distribution?
When applied to investment returns, platykurtic distributions—those with negative excess kurtosis—generally produce results that won't be very extreme, which are great for investors who don't want to take a lot of risk. When excess kurtosis is positive, it has a leptokurtic distribution.
How to calculate excess kurtosis?
Excess kurtosis can, therefore, be calculated by subtracting kurtosis by three. Since normal distributions have a kurtosis of three, excess kurtosis can be calculated by subtracting kurtosis by three. Excess kurtosis is an important tool in finance and, more specifically, in risk management.
What is the term for a distribution with a tail that's thinner than a normal distribution?
The values of excess kurtosis can be either negative or positive. When the value of an excess kurtosis is negative, the distribution is called platykurtic . This kind of distribution has a tail that's thinner than a normal distribution.
What is kurtosis in math?
Mathematically, the kurtosis of a distribution of a random variable X, ...
What is excess kurtosis?
Excess kurtosis. There exists one more method of calculating the kurtosis called ' excess kurtosis '. As kurtosis is calculated relative to the normal distribution, which has a kurtosis value of 3, it is often easier to analyse in terms of excess kurtosis. As the name suggests, it is the kurtosis value in excess of the kurtosis value ...
What is the second category of platykurtic distributions?
The second category is that of platykurtic distributions which have negative excess kurtosis values. Negative values of excess kurtosis indicate that distribution has short/thin tails. A good example of such a distribution is the continuous uniform distribution.
What is the distribution of a distribution called when the kurtosis is 3?
When the kurtosis of distribution is 3, i.e. the excess kurtosis is equal to 0, the distribution is called mesokurtic. This means the distribution is a normal distribution. (' meso ' stands for medium or middle).
Which distribution has a positive excess kurtosis?
The last category is that of leptokurtic distributions which have positive excess kurtosis. A large positive kurtosis indicates a distribution where more of the values are located away from the mean i.e. in the tails of the distribution. Thus, leptokurtic distributions are characterized by fatter tails.
Does Kurtosis measure peak?
Contrary to popular perception, kurtosis does not measure the peakedness of the distribution, and the only unambiguous interpretation of kurtosis is with regard to the heaviness or lightness of tails of the distribution, relative to a normal distribution (we will see an example of this in a subsequent section).
What does kurtosis tell us?
What kurtosis tells us? Kurtosis is a statistical measure used to describe the degree to which scores cluster in the tails or the peak of a frequency distribution. The peak is the tallest part of the distribution, and the tails are the ends of the distribution. There are three types of kurtosis: mesokurtic, leptokurtic, and platykurtic.
What are the three types of kurtosis?
There are three types of kurtosis: mesokurtic, leptokurtic, and platykurtic. Mesokurtic: Distributions that are moderate in breadth and curves with a medium peaked height.
What is extreme positive kurtosis?
An extreme positive kurtosis indicates a distribution where more of the values are located in the tails of the distribution rather than around the mean. Further Information.
What does negative kurtosis mean?
Negative values of kurtosis indicate that a distribution is flat and has thin tails. Platykurtic distributions have negative kurtosis values. A platykurtic distribution is flatter (less peaked) when compared with the normal distribution, with fewer values in its shorter (i.e. lighter and thinner) tails.
When is kurtosis equal to zero?
When kurtosis is equal to 0, the distribution is mesokurtic. This means the kurtosis is the same as the normal distribution, it is mesokurtic (medium peak). The kurtosis of a mesokurtic distribution is neither high nor low, rather it is considered to be a baseline for the two other classifications.
Explanation
- Like skewness, kurtosis is a statistical measure that is used to describe distribution. Whereas skewness differentiates extreme values in one versus the other tail, kurtosis measures extreme values in either tail. Distributions with large kurtosis exhibit tail data exceeding the tails of the normal distribution (e.g., five or more standard deviatio...
Types of Kurtosis
Significance
Advantages
Conclusion
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What Is Excess kurtosis?
Understanding Excess Kurtosis
- Below is the pictorial representation of the kurtosis (all three types, each one is explained in detail in the subsequent paragraph) You are free to use this image on your website, templates etc, Please provide us with an attribution linkHow to Provide Attribution?Article Link to be Hyperlinked For eg: Source: Kurtosis(wallstreetmojo.com)
Types of Excess Kurtosis
- From the perspective of investors, high kurtosis of the return distribution implies that an investment will yield occasional extreme returns. This can swing both the ways that are either positive r...
- When the kurtosis distribution is calculated on any data set of a particular investment, the risk of the investment against the probability of generating returns, depending on its value and ty…
- From the perspective of investors, high kurtosis of the return distribution implies that an investment will yield occasional extreme returns. This can swing both the ways that are either positive r...
- When the kurtosis distribution is calculated on any data set of a particular investment, the risk of the investment against the probability of generating returns, depending on its value and type it...
Example of Excess Kurtosis
- This is calculated on the data set of the investment; the value obtained can be used to depict the nature of the investment. Greater the deviation from the mean means the returns are also high for...
- When the excess kurtosis in flat, it means the probability of generating a high return from the investment is low and will generate high returns in only a few scenarios, regularly the return i…
- This is calculated on the data set of the investment; the value obtained can be used to depict the nature of the investment. Greater the deviation from the mean means the returns are also high for...
- When the excess kurtosis in flat, it means the probability of generating a high return from the investment is low and will generate high returns in only a few scenarios, regularly the return is not...
- High excess kurtosis means that the return on the investment can swing both ways. It means the generated returns can either be very high or very low as per the outliers in the distribution. When it...