不知不觉，时间序列分析一课已上了四分之一或三分之一，我称之为第一阶段，是进一步分析和解决时序问题的奠基性阶段。这课上起来是很有难度的，授课主要是搬运知识，并不创造知识，授课对象是本科生，如何深入浅出地使本科阶段的同学明白无误，却是不亚于知识创造的一个重大挑战。

第一阶段主要是前四讲（第一讲又分上下），第二阶段是对第一阶段的补充完善（待发布），第三、四阶段待定。

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Lec1: 4 Methods to Solve Linear Defference Equations

1.1 Solving DEs with Constant Coefficients and Constant Terms
1.2 Solving DEs with constant Coefficients and Variable Terms

Lec2: Covariance-Stationary ARMA Models

2.1 Stationary Restrictions for ARMA(p, q)
2.2 The Autocorrelation Function

Lec3: Covariance-Stationary Vector Processes

3.1 VAR(p)→VAR(1)
3.2 Stationary Restrictions for Vector Processes

Lec4: Forecasts Based on Conditional Expectation

4.1 Predicting ARMA
4.2 Forecasts from VAR

Lec5: Forecasts Based on Linear Projection

5.1 Linear Projection vs. Conditional Expectation
5.2 Linear Projection vs. OLS Regression
5.3 Wold Decomposition Theorem

Lec6: Calibration and Simulation

6.1 Parameter Calibration
6.2 Impulse-Response/Prediction Simulation

Lec7: OLS Estimation in Time Series Analysis

Lec8: ML Estimation in Time Series Analysis

Lec9: GMM Estimation in Time Series Analysis

Lec10: Bayesian Estimation in Time Series Analysis

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