Platykurtic definition
The term “platykurtic” describes a statistical distribution with a negative excess kurtosis value. The opposite of a platykurtic distribution is a leptokurtic distribution. It features a positive excess of kurtosis. Investors will analyze which statistical distributions are connected with various sorts of assets when deciding where to invest. Platykurtic-distributed assets and markets may appeal to risk-averse investors since they are less likely to produce extreme outcomes.
What does it mean to be platykurtic?
A statistical distribution in which the extra kurtosis amount is negative is referred to as “platykurtic.” As a result, the tails of a platykurtic distribution are thinner than those of a normal distribution, leading to fewer extreme positive or negative events. A leptokurtic distribution, in which excess kurtosis is positive, is the polar opposite of a platykurtic distribution.
When determining where to invest, investors will analyze which statistical distributions are connected with certain sorts of investments. Assets and markets with platykurtic distributions may appeal to risk-averse investors since they are less likely to deliver severe results.
Further Takeaways
Most investors believe that a leptokurtic distribution resembles stock market returns better than a platykurtic distribution. That is, while most returns will be near to the market’s average return, yields will frequently diverge significantly from the mean. In platykurtic markets, such dramatic and surprising events, commonly known as “black swans,” are less likely to occur.
As a result, most conservative investors may avoid investing in leptokurtic markets and instead focus on investments that produce platykurtic returns. Some investors, on the other hand, are actively seeking leptokurtic return investments, anticipating that their extreme positive returns will outweigh their extreme negative returns.
Platykurtic Distribution in the Real World
Between February 1994 and June 2011, Morningstar issued a study paper that included data on the excess kurtosis levels of various asset classes as observed between February 1994 and June 2011. The investments on the list ranged from domestic and foreign shares to real estate, commodities, cash, and bonds. 1
Excess kurtosis levels varied widely as well. Cash and international bonds have excess kurtosis of -1.43 and 0.58, respectively, at the low end of the spectrum. Excess kurtosis of 9.33 and 22.59.2 were offered by U.S. high-yield bonds and hedge-fund arbitrage techniques, respectively.
International real estate, equities from international emerging nations, and commodities were among the asset classes with intermediate degrees of excess kurtosis. Given their tolerance for potential black swan events, an investor looking at this data could rapidly determine what types of assets they want to invest in. Low-kurtosis investments are suitable for risk-averse investors who want to reduce the possibility of severe events, whereas high-kurtosis investments are suitable for investors who are comfortable with extreme events.
Kurtosis Meaning
Kurtosis is a statistical measure of distribution that is used to characterize it. Unlike skewness, which distinguishes extreme values in one tail from those in the other, kurtosis assesses extreme values in both tails. Tail data exceeds the tails of the normal distribution in distributions with strong kurtosis.
For investors, a high kurtosis of the return distribution means that they will see more extreme returns than the typical + or – three standard deviations from the mean that the normal distribution of returns predicts. Kurtosis risk is the name given to this phenomenon.
Types of Kurtosis
A collection of data may be shown in one of three kurtosis categories. All kurtosis metrics are compared to a conventional normal distribution, often known as a bell curve.
A mesokurtic distribution is the first kind of kurtosis. The kurtosis statistic of this distribution is comparable to that of a normal distribution, implying that the distribution’s extreme value characteristic is close to that of a normal distribution.
A leptokurtic distribution is the second kind. A leptokurtic distribution has a higher kurtosis than a mesokurtic distribution. This distribution has lengthy tails as one of its characteristics. The word “lepto-” signifies “thin,” which helps people recall the form of a leptokurtic distribution. Outliers extend the horizontal axis of the histogram graph, making the majority of the data appear in a narrow vertical range, giving a leptokurtic distribution its “skinniness.” As a result, leptokurtic distributions are frequently described as “concentrated near the mean,” but the more important problem (particularly for investors) is that this “concentration” look is caused by occasional severe outliers. T-distributions with tiny degrees of freedom are examples of leptokurtic distributions.
A platykurtic distribution is the last form of distribution. The tails of these distributions are short. The word “platy-” means “wide,” and it refers to a short, broad-looking peak, however this is a historical misconception. Uniform distributions have wide peaks and are platykurtic, while the beta distribution is platykurtic and has an indefinitely pointed peak. Because their extreme values are fewer than those of the normal distribution, both of these distributions are platykurtic. Platykurtic return distributions are steady and predictable for investors in the sense that extreme returns are infrequent.
