A note on portfolios of averages of lognormal variables

Phelim Boyle and Ruihong Jiang

Insurance: Mathematics and Economics, 2023, vol. 112, issue C, 97-109

Abstract: This paper establishes conditions under which a portfolio consisting of the averages of K blocks of lognormal variables converges to a K-dimensional lognormal variable as the number of variables in each block increases. The associated block covariance matrix has to have a special structure where the correlations and variances within the block submatrices are equal. We show why the variance homogeneity assumption plays a key role in the derivation.

Keywords: Lognormal distribution; Sum of lognormals; Block covariance matrix; Limiting distribution; Moment formulae (search for similar items in EconPapers)
JEL-codes: C46 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167668723000562
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:112:y:2023:i:c:p:97-109

DOI: 10.1016/j.insmatheco.2023.06.001

Access Statistics for this article

Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

More articles in Insurance: Mathematics and Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().