Platykurtic Stocks (Market Close, May 15, 2023)
Which stocks have a platykurtic distribution? What is a stock with a platykurtic distribution in price changes?
We share a list of US-listed stocks with a platykurtic distribution and a low variance.
There are fewer platykurtic and low variance stocks in today's data than we have seen in a while. Risk off markets and now fewer stocks with lower than normal outlier risk.
Stocks that are platykurtic, or that have a platykurtic distribution with a standardized kurtosis score </= a parameter and a variance that is </= the variance of the total population in this run (multiplied by a parameter ~ 1.0). In other words, stocks that are platykurtic with a low variance.
A platykurtic distribution of daily stock price changes have fewer results in the tails (or > 2 standard deviations) than a normal distribution. They have a flatter frequency distribution than a normal distribution, so their typical results are spread across the high potential scores and are not as frequently returning the expected return, or mean.
A perfect example of a platykurtic distribution is the results of rolling a fair, 6-sided dice, or flipping a fair coin. There are no outliers because there are few, knowable scores (discrete scores), and no possible outliers. These are a uniform distribution.
For stocks, this could be returns that are in the typical range (say within one standard deviation), and fewer surprises.
We share a list of US-listed stocks with a platykurtic distribution and a low variance.
There are fewer platykurtic and low variance stocks in today's data than we have seen in a while. Risk off markets and now fewer stocks with lower than normal outlier risk.
Stocks that are platykurtic, or that have a platykurtic distribution with a standardized kurtosis score </= a parameter and a variance that is </= the variance of the total population in this run (multiplied by a parameter ~ 1.0). In other words, stocks that are platykurtic with a low variance.
A platykurtic distribution of daily stock price changes have fewer results in the tails (or > 2 standard deviations) than a normal distribution. They have a flatter frequency distribution than a normal distribution, so their typical results are spread across the high potential scores and are not as frequently returning the expected return, or mean.
A perfect example of a platykurtic distribution is the results of rolling a fair, 6-sided dice, or flipping a fair coin. There are no outliers because there are few, knowable scores (discrete scores), and no possible outliers. These are a uniform distribution.
For stocks, this could be returns that are in the typical range (say within one standard deviation), and fewer surprises.
More formally, a platykurtic distribution has a standardized kurtosis score that is < 1.250, where a normal distribution = 3.0. These stocks also have a variance that is </= the variance of the population, held evenly. You may notice that money-losing stock populations have a much higher variance, so their resulting platykurtic results likely do too.
Kurtosis is the fourth central movement of a distribution. It is one way to measure whether a random variable has a normal distribution. We use the kurtosis of a year's worth of adjusted, daily stock price changes, along with the variance of those changes, to better understand how a stock might perform in the future.
If you can visualize it, the distribution is flattening the bell-shaped curve (or frequency distribution) down onto the X-axis, giving less room in the tails for observations greater than 2 standard deviations from the mean. In some cases, the tails seem longer, but there are fewer outliers in the expected observations. Another visualization is that the center of the bell is stretched out to be fatter and shorter than a bell shaped curve, which seems to spread out the observations around the mean.
A stock that is platykurtic and low variance are safer when compared to a normally distributed stock. Options premia may be higher than fair value since it prices in a normal occurance of outliers. This is actually a safer stock in highly volatile market situations. We see energy services companies, healthcare, financial services and industrial companies that are not economically sensitive, nor do they seem to be subject to normal business cycles in this category.
Kurtosis is the fourth central movement of a distribution. It is one way to measure whether a random variable has a normal distribution. We use the kurtosis of a year's worth of adjusted, daily stock price changes, along with the variance of those changes, to better understand how a stock might perform in the future.
If you can visualize it, the distribution is flattening the bell-shaped curve (or frequency distribution) down onto the X-axis, giving less room in the tails for observations greater than 2 standard deviations from the mean. In some cases, the tails seem longer, but there are fewer outliers in the expected observations. Another visualization is that the center of the bell is stretched out to be fatter and shorter than a bell shaped curve, which seems to spread out the observations around the mean.
A stock that is platykurtic and low variance are safer when compared to a normally distributed stock. Options premia may be higher than fair value since it prices in a normal occurance of outliers. This is actually a safer stock in highly volatile market situations. We see energy services companies, healthcare, financial services and industrial companies that are not economically sensitive, nor do they seem to be subject to normal business cycles in this category.
All stock run (ticker, standard kurtosis score, variance over past year)
The stocks that are platykurtic and low variance:
The stocks that are platykurtic and low variance:
Platykurtic and low variance stocks:
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A short film to describe our platykurtic stock service.