EconPapers    
Economics at your fingertips  
 

Optimal pension fund composition for an Italian private pension plan sponsor

Sebastiano Vitali (), Vittorio Moriggia () and Miloš Kopa ()
Additional contact information
Sebastiano Vitali: University of Bergamo
Vittorio Moriggia: University of Bergamo
Miloš Kopa: Charles University in Prague

Computational Management Science, 2017, vol. 14, issue 1, No 8, 135-160

Abstract: Abstract We address the problem of a private pension plan sponsor who has to find the best pension funds for its members. Starting from a descriptive analysis of the pension plan members we identify a set of representative subscribers. Then, the optimal allocation for each representative will become a pension fund of the pension plan. For each representative, we propose a multistage stochastic program (MSP) which includes a multi-criteria objective function. The optimal choice is the portfolio allocation that minimizes the average value at risk deviation of the final wealth and satisfies a wealth target in the final stage and other constraints regarding pension plan regulations. Stochasticity arises from the investor’s salary process and from asset returns. Numerical results show the optimal dynamic portfolios with respect to the investor’s preferences and then the best pension funds the sponsor might offer.

Keywords: Pension fund; Optimal policy; Multistage stochastic programming; Cluster analysis; 90C15; 91B30 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://link.springer.com/10.1007/s10287-016-0263-4 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:comgts:v:14:y:2017:i:1:d:10.1007_s10287-016-0263-4

Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2

DOI: 10.1007/s10287-016-0263-4

Access Statistics for this article

Computational Management Science is currently edited by Ruediger Schultz

More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:comgts:v:14:y:2017:i:1:d:10.1007_s10287-016-0263-4