From explanatory linear regression to simple linear regression and multiple linear regression.
The derivation of OSL and various hypothesis tests related to OSL include autocorrelation test (BG test, DW test), heteroscedasticity test (QG test, White test), multiple * * * linear test, normal distribution test (B-J test), parameter stability test, crepe test and predictive failure test. The parameters of OSL, the derivation process of Rsquare, F-stat (this part is in the problem set and in the exam), and of course there is the parameter t-test.
Empirical study on CAPM and multi-factor model.
ARIMA model, derivation of ACF, white noise test (Ljung-box test), unit root test (feeling unit root is particularly important, not only the focus of the exam, but also the unit root will be deduced from the perspective of difference equation in the second semester), AIC and BIC rules.
The GARCH family models (ARCH, GARCH, EGACH, Threshold GARCH, GARCH-M and multivariate GARCH) and the special pit VaR(Value-at-risk) are not mentioned by the teacher, but the group work needs to be calculated.
Co-integration (introduction but no exam). More in-depth measurement model (VAR, VECM) will be discussed in the second semester of advanced time series modeling. Therefore, this course is also the leading course of advanced time series modeling.