Robust analysis for premium-reserve models in a stochastic nonlinear discrete-time varying framework

Rong Li, Athanasios A. Pantelous*, Lin Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


The effective management of uncertainty and complexity in premium pricing and reserve accumulation processes provide new challenges to the decision- and policy-makers. In this regard, the implementation of complex mathematical tools and advanced statistical techniques is highly acquired. Over the last three decades, methodologies and applications of robust control theory to finance and economics have received strong attention among researchers and practitioners. However, relatively scant research has been carried out so far in relation to insurance. This paper proposes a stochastic, nonlinear time-varying premium-reserve (P-R) system with Lipschitz-type conditions in discrete-time to explore P-R system's stability, stabilization and H-control properties. In our case, as an extension of the classical quadratic condition, the one-side Lipschitz conditions are also considered and a nonconvex feasibility problem is formulated and solved. In addition, both robust stochastic stability and a pre-specified disturbance attenuation level can be guaranteed. Finally, numerical examples are presented to illustrate the applicability of theoretical treatment.

Original languageEnglish
Article number112592
JournalJournal of Computational and Applied Mathematics
Publication statusPublished - Apr 2020


  • (one-side) Lipschitz conditions
  • H-control
  • Nonlinear uncertainties
  • Premium-reserve process
  • Systems stability


Dive into the research topics of 'Robust analysis for premium-reserve models in a stochastic nonlinear discrete-time varying framework'. Together they form a unique fingerprint.

Cite this