Convergence of sums of dependent Bernoulli random variables: an application from portfolio theory
Madelyn Houser and
Pak-Wing Fok
Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 23, 5673-5681
Abstract:
Generalizations of the Central Limit Theorem to N dependent random variables often assume that the dependence falls off as N→∞. In this paper we present an example from mathematical finance where convergence is independent of N. Specifically, we consider N≫1 dependent Bernoulli variates that represent N loans and probabilistic dependence among loans is based on an underlying economic model for default. A simple model for correlated default is the Vasicek Asymptotic Single Risk Factor (ASRF) framework. Our results showcase an example of “fast” convergence of dependent variates to this limiting non normal distribution with rate O(N−1).
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2018.1517891 (text/html)
Access to full text is restricted to subscribers.
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:taf:lstaxx:v:48:y:2019:i:23:p:5673-5681
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2018.1517891
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().