Sum of a Random Number of Correlated Random Variables that Depend on the Number of Summands

Joel E. Cohen

The American Statistician, 2019, vol. 73, issue 1, 56-60

Abstract: The mean and variance of a sum of a random number of random variables are well known when the number of summands is independent of each summand and when the summands are independent and identically distributed (iid), or when all summands are identical. In scientific and financial applications, the preceding conditions are often too restrictive. Here, we calculate the mean and variance of a sum of a random number of random summands when the mean and variance of each summand depend on the number of summands and when every pair of summands has the same correlation. This article shows that the variance increases with the correlation between summands and equals the variance in the iid or identical cases when the correlation is zero or one.

Date: 2019
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DOI: 10.1080/00031305.2017.1311283

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