A multistage risk-averse stochastic programming model for personal savings accrual: the evidence from Lithuania

  • Audrius KabašinskasEmail author
  • Francesca Maggioni
  • Kristina Šutienė
  • Eimutis Valakevičius
Original Research


In this paper we consider the problem of choosing the optimal pension fund in the second pillar of Lithuanian pension system by providing some guidelines to individuals with defined contribution pension plans. A multistage risk-averse stochastic optimization model is proposed that can be used to plan a long-term pension accrual under two different cases: minimum and maximum accumulation plans as possible options in the system. The investment strategy of personal savings is based on the optimal solutions over possible scenario realizations generated for a particular participant. The concept of the risk-averse decision-maker is implemented by choosing the conditional value at risk as the risk measure defined by a nested formulation that guarantees the time consistency in the multistage model. The paper focuses on three important decision-making moments corresponding to the duration of periods to be modelled. The first period is a short-term accumulation, while the second period is a long-term accumulation with possibly high deviation of objective function value. The third period is designed to implement the concept of target date fund in the second pillar pension scheme as the subsequent need to protect against potential losses at risky pension funds. The experimental findings of this research provide insights for individuals as decision-makers to select pension funds, as well as for policy-makers by revealing the vulnerability of pension system.


Pension system modeling Multistage stochastic integer programming Alpha-stable distribution Time consistency CVaR Target date funds 

Mathematics Subject Classification

91B28 90C15 60E07 91B30 


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Authors and Affiliations

  1. 1.Department of Mathematical ModelingKaunas University of TechnologyKaunasLithuania
  2. 2.Department of Management, Economics and Quantitative MethodsUniversity of BergamoBergamoItaly

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