마르코프 국면전환 모형을 이용한 확정급여형 퇴직연금제도의 부채연계투자전략

This study proposes a dynamic liability-driven investment strategy utilizing a Markov regime-switching model to enhance the financial soundness of defined benefit pension plans under a strengthened minimum funding ratio regulatory environment. Unlike prior studies that primarily focused on surplus volatility or solvency risk, this study sets contribution risk minimization as the core objective function, directly addressing the employer's actual financial burden. For the analysis, a hypothetical defined benefit pension plan is constructed, liabilities are evaluated using the projected unit credit method, and a Markov regime-switching model is applied to asset returns to identify normal and crisis regimes. Empirical results demonstrate that dynamic asset allocation strategies incorporating regime-switching outperform static strategies. Specifically, the dynamic strategy aimed at surplus maximization enhances performance by increasing the allocation to return-seeking assets during normal regimes while adopting a defensive position by expanding deposit holdings during crisis regimes, thereby effectively reducing maximum drawdown. In contrast, the contribution risk minimization strategy exhibits limited allocation adjustments across regime transitions due to its conservative asset allocation characteristics, yet demonstrates stable cash flow management. This study empirically identifies the trade-off between contribution risk and solvency risk, suggesting that flexible asset allocation responsive to market regimes can contribute to enhancing corporate financial stability and pension plan sustainability.