Regime switching models are statistical models that are often used in finance and economics to capture changes in the underlying structure or behavior of financial markets. The switching regimes corresponding to different periods when changes in regulation, policy, and other secular events occur. These changes can be identified from data by an econometric estimation procedure. The switching regime can be present in stochastic process of means, volatilities, autocorrelations, and cross-covariances of asset returns. The regime switching models are able to capture the stylized behavior of many financial series including fat tails, heteroskedasticity, skewness, and time-varying correlations. They can also detect changes in regimes in consumption or dividend growth, or the dynamic properties of equilibrium asset prices which can affect non-linear risk-return trade-offs, and their potentially large consequences for investors' optimal portfolio choice. The goal of a potential dissertation thesis on this topic would be to design models that are able to identify structural changes in economic and financial processes and to quantify the size of these changes, then to propose adequate estimation technique and finally to verify them on real economic/financial data. The results will be submitted for publication in journals like Physica A, Finance Research Letters, International Journal of Forecasting.
References:
- Segnon, M., Gupta, R., Wilfling, B. (2024). Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks. International Journal of Forecasting, 40(1), 29-43.
- Yu, M., Song, J. (2018). Volatility forecasting: Global economic policy uncertainty and regime switching. Physica A: Statistical Mechanics and Its Applications, 511, 316-323.
- Liu, Y., Sun, H., Zhang, J., Taghizadeh-Hesary, F. (2020). Detection of volatility regime-switching for crude oil price modeling and forecasting. Resources Policy, 69, 101669.
- Ang, A., Timmermann, A. (2012). Regime changes and financial markets. Annu. Rev. Financ. Econ., 4(1), 313-337.
- Shi, Y., Ho, K. Y. (2015). Long memory and regime switching: A simulation study on the Markov regime-switching ARFIMA model. Journal of Banking & Finance, 61, S189-S204.
