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Asian Review of Financial Research Vol.39 No.1 pp.1-32 https://www.doi.org/10.37197/ARFR.2026.39.1.1
Dynamic Regime-Based Rebalancing Strategies : Empirical Evidence from Korean Investors
Junho Hwang Deputy Research Fellow, National Pension Research Institute, National Pension Service
Eunyoung Cho Assistant Professor, School of Business, Chungnam National University
Key Words : Regime-based Rebalancing,Hidden Markov Models,Portfolio Management,Dynamic Asset Allocation,Institutional Investors

Abstract

This study examines the performance of regime-based portfolio rebalancing strategies that utilize hidden Markov models (HMMs) to dynamically adjust asset allocations in response to volatility regime shifts. Based on a globally diversified portfolio reflecting the investment context of institutional investors with significant cross-border exposure, the analysis yields three key findings. First, regime-based strategies consistently outperform static strategic asset allocation (SAA) and buy-and-hold approaches in terms of risk-adjusted returns, while effectively reducing downside risk measures such as conditional value-at-risk (CVaR), maximum drawdown (MDD), and volatility. Second, the benefits of regime-based strategies are more pronounced at higher adjustment intensities, confirming their adaptability under shifting market conditions. Third, the performance advantages of regime-based strategies persist even after incorporating transaction costs. By integrating regime-based signals into the rebalancing process, this study provides empirical implications for institutional investors managing globally diversified portfolios in volatility-sensitive environments.
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