Exact Results for the Distribution of Randomly Weighted Sums

Thomas Hitchen and Saralees Nadarajah ()
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Thomas Hitchen: Department of Mathematics, University of Manchester, Manchester M13 9PL, UK
Saralees Nadarajah: Department of Mathematics, University of Manchester, Manchester M13 9PL, UK

Mathematics, 2024, vol. 12, issue 1, 1-22

Abstract: Dependent random variables play a crucial role in various fields, from finance and statistics to engineering and environmental sciences. Often, interest lies in understanding the aggregate sum of a collection of dependent variables with random weights. In this paper, we provide a comprehensive study of the distribution of the aggregate sum with random weights. Expressions derived include those for the cumulative distribution function, probability density function, conditional expectation, moment generating function, characteristic function, cumulant generating function, moments, variance, skewness, kurtosis, cumulants, value at risk and the expected shortfall. Real data applications are discussed.

Keywords: conditional expectation; copulas; cumulative distribution function; probability density function (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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