Rate My Professor Yong Song

Song's research encompasses Bayesian nonparametric modelling, financial econometrics, and empirical macroeconomics, with applications to market dynamics, forecasting, and structural changes. Key publications include 'Components of bull and bear markets: bull corrections and bear rallies' in the Journal of Business & Economic Statistics (2012); 'Oil price shocks and economic growth: The volatility link' in the International Journal of Forecasting (2020); 'Identifying speculative bubbles using an infinite hidden Markov model' in the Journal of Financial Econometrics (2015); 'A new structural break model, with an application to Canadian inflation forecasting' in the International Journal of Forecasting (2014); 'Markov switching' (2020); 'Measuring Inflation Expectations Uncertainty Using High-Frequency Data' in the Journal of Money, Credit and Banking (2018); 'An efficient Bayesian approach to multiple structural change in multivariate time series' and 'Sparse change-point VAR models' in the Journal of Applied Econometrics (2018 and 2021); and 'Bull and bear markets during the COVID-19 pandemic' in Finance Research Letters (2021). He contributes as Chief Investigator to Australian Research Council grants, including Discovery Project DP230100959 and Linkage Project LP240100101 on predictive analytics for water consumption.