STATISTICAL DESIGN AND EVALUATION OF HYBRID PENSION SCHEMES USING REGIME-SWITCHING GEOMETRIC BROWNIAN MOTION (RS-GBM) AND MARKOV CHAIN MODELS: A CASE OF NIGERIA WITH A GLOBAL PERSPECTIVES

Abstract
This study evaluates hybrid pension schemes in Nigeria using Regime-Switching Geometric Brownian Motion (RS-GBM) and Markov Chain models to account for economic regime shifts. By simulating pension fund trajectories and income sustainability across Growth, Stagnation, and Recession scenarios, the research shows that hybrid schemes provide better resilience and benefit adequacy than pure Defined Benefit (DB) or Defined Contribution (DC) models. Survey data from 673 respondents reinforce these findings, highlighting the critical roles of annuity literacy and flexible contributions. Policy recommendations include integrating hybrid schemes into Nigeria's pension framework and adopting stochastic modeling for fund management Keywords - Hybrid Pension, RS-GBM, Markov Chain, Regime-switching, Annuity, Retirement Income Adequacy.