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Investopedia explains 'Platykurtic'
Referred to as the "volatility of volatility", kurtosis gauges the level of fluctuation within a distribution. High levels of kurtosis represent a low level of data fluctuation, as the observations cluster about the mean. Lower values of kurtosis mean that data has a larger degree of variance.
For example, when looking at past stock returns, analysts will want to determine the likelihood of extreme returns (or losses) in the future. If past stock data results in a platykurtic distribution, analysts will expect more volatility in future returns. This means that there is a higher probability than usual for extreme price movements to occur.
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