What does the kurtosis tells about the distribution?
Kurtosis is a statistical measure that defines how heavily the tails of a distribution differ from the tails of a normal distribution. In other words, kurtosis identifies whether the tails of a given distribution contain extreme values.
What does positive kurtosis value indicates?
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.
Is high or low kurtosis good?
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).
Why is high kurtosis bad?
High kurtosis is most likely to imply a distribution fatter tailed than the normal, so some very high (+ or -) residuals. Even if there are many near zero, that is only the good news, and it is the possible bad news that needs attention.
Does high kurtosis mean fat tails?
Positive excess kurtosis means that distribution has fatter tails than a normal distribution. Fat tails means there is a higher than normal probability of big positive and negative returns realizations.
What type of kurtosis if it has a normal distribution?
The standard normal distribution has a kurtosis of 3, so if your values are close to that then your graph’s tails are nearly normal. These distributions are called mesokurtic. Kurtosis is the fourth moment in statistics.
What does a negative kurtosis indicate?
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.
Which kurtosis has fatter tails?
What Is Leptokurtic? 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. It is one of three major categories found in kurtosis analysis.
What causes positive kurtosis?
Positive excess values of kurtosis (>3) indicate that a distribution is peaked and possess thick tails. Leptokurtic distributions have positive kurtosis values. A leptokurtic distribution has a higher peak (thin bell) and taller (i.e. fatter and heavy) tails than a normal distribution.
What does high skewness mean?
Positive Skewness means when the tail on the right side of the distribution is longer or fatter. The mean and median will be greater than the mode. Negative Skewness is when the tail of the left side of the distribution is longer or fatter than the tail on the right side. The mean and median will be less than the mode.
Why kurtosis of a normal distribution is 3 instead of 0?
When I look at a normal curve, it seems the peak occurs at the center, a.k.a at 0. So why is the kurtosis not 0 and instead 3? It so happens that for the normal distribution, μ4=3σ4 so β2=3. The excess kurtosis usually denoted by γ2 is γ2=β2(Normal)−3.
What is an example of a Platykurtic distribution?
An example of a platykurtic distribution is the uniform distribution, which does not produce outliers. Distributions with a positive excess kurtosis are said to be leptokurtic.
What value of kurtosis is Leptokurtic?
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.
What is the excess kurtosis of a normal distribution?
Excess kurtosis means the distribution of event outcomes have lots of instances of outlier results, causing fat tails on the bell-shaped distribution curve. Normal distributions have a kurtosis of three. Excess kurtosis can, therefore, be calculated by subtracting kurtosis by three.
What does a negative kurtosis mean?
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.
What does Platykurtic kurtosis mean?
The term “platykurtic” refers to a statistical distribution in which the excess kurtosis value is negative. For this reason, a platykurtic distribution will have thinner tails than a normal distribution will, resulting in fewer extreme positive or negative events.
Which distribution is Leptokurtic?
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. It is one of three major categories found in kurtosis analysis.
What is Leptokurtic and Platykurtic?
A platykurtic distribution would, therefore, have thinner tails than a normal distribution, leading to less extreme positive or negative events. A leptokurtic distribution is the opposite of a platykurtic distribution. It has an excess kurtosis that is positive.
What is the kurtosis value of a distribution?
A distribution that is less peaked and has thinner tails than normal distribution has kurtosis value between 1 and 3. Such distribution is called platykurtic or platykurtotic.
Which data shows excess kurtosis of zero or close to zero?
Data that follows a mesokurtic distribution shows an excess kurtosis of zero or close to zero. It means that if the data follows a normal distribution, it follows a mesokurtic distribution.
What is the meaning of high excess kurtosis?
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 is negative, it indicates that the deviation of the data set from the mean is flat.
What is a kurtosis histogram?
Kurtosis is a measure of the combined weight of a distribution’s tails relative to the center of the distribution. When a set of approximately normal data is graphed via a histogram, it shows a bell peak and most data within three standard deviations (plus or minus) of the mean.