UEH Master Programs

This course focuses on the theory and applications of financial time series analysis, especially in volatility modeling and risk management. Students are expected to gain practical experience in analyzing financial and macroeconomic data. Real examples are used throughout the course. The topics discussed include the following: (1) Analysis of asset returns: autocorrelation, business cycles, stationarity, predictability and prediction, simple linear models and regression models with serially correlated errors; (2) Volatility models: GARCH-type models, GARCH-M models, EGARCH model, GJR model, stochastic volatility model, long-range dependence; (3) Forecasting evaluation: out-of-sample prediction and backtesting; (4) High-frequency data analysis (market microstructure): transactions data, non-synchronous trading, bid-ask bounce, duration models, logistic and ordered probit models for price changes, and realized volatility; (5) Nonlinearities in financial data: nonlinear and Markov switching models; (6) Continuous-time models: simple continuous-time and diffusion models, Black-Scholes pricing formulas and jump diffusion models; (7) Value at Risk and expected shortfall: Riskmetrics, extreme value analysis, peaks over threshold, and quantile regression; (8) Multivariate series: cross correlation matrices, simple VAR and VEC models, pairs trading, factor models and multivariate GARCH models.