Background Risk Models and Stepwise Portfolio Construction

Alexandru V. Asimit (), Raluca Vernic () and Ricardas Zitikis ()
Additional contact information
Alexandru V. Asimit: City University
Raluca Vernic: Ovidius University of Constanta
Ricardas Zitikis: University of Western Ontario

Methodology and Computing in Applied Probability, 2016, vol. 18, issue 3, 805-827

Abstract: Abstract Assuming the multiplicative background risk model, which has been a popular model due to its practical applicability and technical tractability, we develop a general framework for analyzing portfolio performance based on its subportfolios. Since the performance of subportfolios is easier to assess, the herein developed stepwise portfolio construction (SPC) provides a powerful alternative to a number of traditional portfolio construction methods. Within this framework, we discuss a number of multivariate risk models that appear in the actuarial and financial literature. We provide numerical and graphical examples that illustrate the SPC technique and facilitate our understanding of the herein developed general results.

Keywords: Portfolio construction; Background risk; Systemic risk; Laplace transform; Risk management; Capital allocation; 62H05; 91B30; 44A10 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://link.springer.com/10.1007/s11009-015-9458-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:metcap:v:18:y:2016:i:3:d:10.1007_s11009-015-9458-3

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-015-9458-3

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().