Market Regimes And Portfolio Allocation: Evidence From The Romanian Equity Market Using Hidden Markov Models And Xgboost

This study examines whether the Romanian equity market exhibits persistent risk regimes, whether these regimes can be forecast at short horizons, and whether such forecasts can improve portfolio allocation. The analysis uses daily BET index data over 2016–2025 and applies a two-step empirical framework. A Hidden Markov Model is first used to identify latent market states based on returns and realised volatility, followed by an XGBoost classifier that predicts regimes one day ahead using market, volatility, domestic macro-financial, and global indicators. The results reveal three distinct regimes, interpreted as calm, stress, and panic, each reflecting different levels of market risk. The forecasting model performs well in the calm and stress regimes, while predictions for the panic state are less precise but remain informative from a risk-management perspective. Most classification errors occur between neighbouring regimes rather than between extreme states. The economic evaluation shows that a regime-probability portfolio strategy with volatility targeting outperforms a passive Buy-and-Hold investment in the BET index, generating higher cumulative performance and lower drawdowns. Overall, the findings indicate that risk regimes in the Romanian equity market are persistent, short-term predictable, and economically useful for systematic portfolio allocation.