EconPapers    
Economics at your fingertips  
 

Robust scenario-based value-at-risk optimization

Oleksandr Romanko () and Helmut Mausser
Additional contact information
Oleksandr Romanko: IBM
Helmut Mausser: IBM

Annals of Operations Research, 2016, vol. 237, issue 1, No 11, 203-218

Abstract: Abstract This paper develops and tests a heuristic algorithm for scenario-based value-at-risk (VaR) optimization. Due to the high computational complexity of VaR optimization, conditional value-at-risk-based proxies are utilized for VaR objectives. It is shown that our heuristic algorithm obtains robust results with low computational complexity.

Keywords: Risk management; Value-at-risk; Optimization; Algorithms; Robustness (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-015-1822-8 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:annopr:v:237:y:2016:i:1:d:10.1007_s10479-015-1822-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-015-1822-8

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:237:y:2016:i:1:d:10.1007_s10479-015-1822-8