Optimal tactics in community pension model for defined benefit pension plans

Area of Science:

• * Pension Economics
• * Game Theory
• * Financial Mathematics

Background:

• * Aging populations are increasing the relevance of community pension initiatives.
• * Defined benefit pension plans face challenges in balancing company investment strategies with employee preferences for community pension allocation.
• * Existing models often do not fully capture the dynamic interplay between employer investment control and employee demand for community-based retirement funds.

Purpose of the Study:

• * To formulate a stochastic differential game model for pension management under a community pension scheme.
• * To determine the Markov Perfect Nash Equilibrium strategy for optimal investment and allocation.
• * To analyze the influence of risk aversion on equilibrium outcomes in community pension plans.

Main Methods:

• * Development of a stochastic differential game model incorporating company investment rates and employee community pension allocation preferences.
• * Application of the Hamilton-Jacobi-Bellman equation to derive equilibrium strategies.
• * Numerical simulations to explore the impact of varying risk aversion levels and parameter values.

Main Results:

• * The study derives the Markov Perfect Nash Equilibrium solution for the defined benefit pension plan within the community pension framework.
• * Optimal portfolio strategies are identified, balancing company investment control and employee allocation desires.
• * Numerical simulations demonstrate how risk aversion influences equilibrium ratios and managerial risk tolerance.

Conclusions:

• * The research provides a robust framework for analyzing pension dynamics in community-based schemes.
• * Findings offer valuable insights for companies and policymakers navigating the complexities of modern pension management.
• * Understanding the impact of risk aversion is crucial for optimizing pension fund performance and employee satisfaction.