Econometrics II (Time Series Analysis)

Introduction

Syllabus
Computer Setup

Lectures

Introduction
- 1. Time series vs cross-section
- 2. Time Series concepts and models
Multivariate normal distribution
- 1. Multivariate normal distribution
Review of maximum likelihood estimation
- 1. Maximum likelihood estimation
- 2. Maximum likelihood estimation of Gaussian models
ARMA models
Non-stationarity
- 1. Non-stationarity and unit root processes
Conditional Heteroskedasticity
- 1. ARCH processes
Multivariate models
Other topics

Assignments

Homework 0
- README HW0
Homework 1
- README HW1
- HW1-empty
Homework 2
Homework 3
- Readme HW3
- HW 3 Part 2-2
Homework 4
- README HW4
- Part 1
- Part 2
Homework 5
- README HW5
- HW 5 part 1
Homework 6
Homework 7
Homework 8
- HW8 Part 2
Homework 9
Homework 10

Projects

Midterm project
Final project

Tutorials

1. Python
- Intro
- Functions
- Modules
- Paths
2. Numpy
3. Pandas
- Intro
- Pandas for time series data
4. Matplotlib
Other tools

Data

1. APIs

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Multivariate models

Multivariate models¶

1. VARs
2. State space models
3. Applications of state space models

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By Nikolay Iskrev
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