**On this page, you will find the documents related to the course on time series analysis.**

The course will be decomposed into different topics. For each of these topics, you will find the related slides, the mathematical proofs and some R codes to put the theory into practice.

##### Topics

1. Linear regression for time series

- Slides (updated – January, 27)
- Mathematical proofs
- Empirical exercises: OLS assumptions, Chebyshev_application, Stochastic_processes, CLT_and_mds, Autocorrelation, Linear_regression_asymptotic_framework
- In html: Regression topic.

2. Linear dependence: Autoregressive and moving average models

- Slides
- Mathematical proofs
- Empirical exercises: MA_simulation, AR_simulation, AR_MA_with_predictions, AR_forecasting_exercise, AR_model_Autocorrelation_and_OLS_properties, AR_model_OLS_and_MLE, MA_ARMA_model_with_MLE.
- In html: ARMA topic

3. Volatility models

- Slides
- Mathematical proofs
- Empirical exercise: Volatility_models
- In html: Volatility_models