A normal random variable has a kurtosis of 3 irrespective of its mean or standard deviation. Buy Here – www.ajio.com. Below is the pictorial representation of the kurtosis (all three types, each one is explained in detail in the subsequent paragraph). A correlation is a statistical measure of the relationship between two variables. Kurtosis is measured by moments and is given by the following formula − Formula Therefore, an investment whose returns follow a leptokurtic distribution is considered to be risky. In the area of finance, this is used to measure the volume of financial risk associated with any instrument or transaction. You can learn more about from the following article –, Copyright © 2021. Kurtosis refers to a measure of the degree to which a given distribution is more or less ‘peaked’, relative to the normal distribution. When kurtosis is positive on in other terms, more than zero, the data falls under leptokurtic. This can be used to define the financial risk of the investment. A normal distribution has kurtosis exactly 3 (excess kurtosis exactly 0). Being platykurtic doesn’t mean that the graph is flat-topped. Negatively skewed distribution Symmetrical Distribution It is clear from the above diagram that in symmetrical distribution the value of mean, median and mode coincide (mean = median = mode). That is, data sets with high kurtosis tend to have heavy tails, or outliers. Types of Kurtosis There are three categories of kurtosis that can be displayed by a set of data. Based on the predictions, advisors will advise the strategy and investment agenda to the investor, and they will choose to go about the investment. There are three types of kurtosis that can be exhibited by any distribution: Leptokurtic or heavy-tailed distribution (kurtosis more than normal distribution) Mesokurtic (kurtosis same as the normal distribution) Platykurtic or short-tailed distribution (kurtosis less than normal distribution) The types of kurtosis are determined by the excess kurtosis of a particular distribution. Kurtosis is a measure of how differently shaped are the tails of a distribution as compared to the tails of the normal distribution. • Its tails are high and long. If a curve is less outlier prone (or lighter-tailed) than a normal curve, it is called as a platykurtic curve. Greater the deviation from the mean means the returns are also high for that particular investment. In probability theory and statistics, kurtosis (from Greek: κυρτός, kyrtos or kurtos, meaning \"curved, arching\") is a The parameters have been chosen to result in a variance equal to 1 in each case. Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. This is calculated on the data set of the investment; the value obtained can be used to depict the nature of the investment. The green curve on the above picture represents the leptokurtic distribution. Types of Skewness: Skewness may be three types 1. In the finance context, the platykurtic distribution of the investment returnsInternal Rate of Return (IRR)The Internal Rate of Return (IRR) is the discount rate that makes the net present value (NPV) of a project zero. 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 belongs to; the investment predictions can be made by the investment advisors. The blue line in the above picture represents a Mesokurtic distribution. The kurtosis reveals a distribution with flat tails. Example: When used, these Excel functions make your financial statement analysis more dynamic. CFA Institute Does Not Endorse, Promote, Or Warrant The Accuracy Or Quality Of WallStreetMojo. Kurtosis is useful in statistics for making inferences, for example, as to financial risks in an investment: The greater the kurtosis, the higher the probability of getting extreme values. Risk management encompasses the identification, analysis, and response to risk factors that form part of the life of a business. Therefore, the excess kurtosis is found using the formula below: The types of kurtosis are determined by the excess kurtosis of a particular distribution. The kurtosis coefficient is a measure of the shape of the tails. These categories are as follows: Mesokurtic distribution. How can I understand different types of kurtosis? While skewness focuses on the overall shape, Kurtosis focuses on the tail shape. • "Excess coefficient", Encyclopedia of Mathematics, EMS Press, 2001 [1994] By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, New Year Offer - All in One Financial Analyst Bundle (250+ Courses, 40+ Projects) View More, Financial Modeling Course (with 15+ Projects), 16 Courses | 15+ Projects | 90+ Hours | Full Lifetime Access | Certificate of Completion. A high kurtosis distribution has a sharper peak and longer fatter tails, while a low kurtosis distribution has a more rounded pean and shorter thinner tails. For investment advisors, kurtosis is a crucial factor in defining the investment risk associated with the portfolio of the fund. The excess kurtosis can take positive or negative values as well, as values close to zero. In finance, a leptokurtic distribution shows that the investment returns may be prone to extreme values on either side. The skewness measures the combined size of the two tails; the kurtosis measures the distribution among the values in these tails. … The Internal Rate of Return (IRR) is the discount rate that makes the net present value (NPV) of a project zero. This guide will teach you how to perform dynamic financial analysis in Excel using advanced formulas and functions. Kurtosis can reach values from 1 to positive infinite. This means that the data set follows a normal distribution. Mesokurtic (Kurtosis = 3) — This distribution shows kurtosis of 3 near zero. So, the further the tails are from the mean the higher the risk of getting an extremely low return and the higher the chance of getting an extremely high return. The concept of kurtosis is very useful in decision-making. Any distribution with kurtosis ≈3 (excess ≈0) is called mesokurtic . 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