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In this course, you will :
- Discover how to create better GARCH models with more realistic assumptions.
- Learn how to use rolling window approaches to make more sophisticated volatility forecasts.
- introduces you to the data science modelling KISS principle
- Learn how to use p-values and t-statistics to simplify model configuration, how to use ACF plots and the Ljung-Box test to validate model assumptions, and how to use likelihood and information criteria to select a model.
- Learn how to apply the GARCH models you've already learned to real-world financial scenarios.
- As you become more familiar with VaR in risk management, dynamic covariance in asset allocation, and dynamic Beta in portfolio management, you will be able to improve your skills.
Syllabus :
- GARCH Model Fundamentals
- GARCH Model Configuration
- Model Performance Evaluation
- GARCH in Action
