Slides
A comprehensive set of class tested slides is available below
This is the ninth version (2024) of the slides, and there are bound to be typos and other issues. I very much appreciate any comments.
I am grateful to Olafur Arnason, Yiying Zhong, Agne Stengeryte and Athanasios Dimisioris for their fantastic assistance in making the 2015 version of the slides. Yuyang Lin gave me valuable comments on the 2022 version of the slides.
| Chapter number | Chapter name | Download | Latest update |
|---|---|---|---|
| 0 | Introduction to Course | Download | Version 9.1 September 2024 |
| 1 | Financial Markets, Prices and Risk | Download | Version 9.1 September 2024 |
| 2 | Univariate Volatility Modeling | Download | Version 9.0 August 2024 |
| 3 | Multivariate Volatility Models | Download | Version 9.0 August 2024 |
| 4 | Risk Measures | Download | Version 9.0 August 2024 |
| 5 | Implementing Risk Forecasts | Download | Version 9.0 August 2024 |
| 6 | Analytical Value-at-Risk for Options and Bonds | Download | Version 9.1 September 2024 |
| 7 | Simulation Methods for VaR for Options and Bonds | Download | Version 9.0 August 2024 |
| 8 | Backtesting and Stress Testing | Download | Version 9.0 August 2024 |
| 9 | Extreme Value Theory | Download | Version 1.0 August 2015 |
| 10 | Endogenous Risk | Download | Version 9.1 September 2024 |
| 11 | Market Risk Regulations | Download | Version 9.0 August 2024 |
| 11 | Machine Learning and Artificial Intelligence | Download | Version 9.0 August 2024 |
Financial Risk Forecasting
Market risk forecasting with R, Julia, Python and Matlab. Code, lecture slides, implementation notes, seminar assignments and questions.© All rights reserved, Jon Danielsson,