Teacher(s)
Language
English
> French-friendly
> French-friendly
Prerequisites
Mastery of English at the level of LANGL1330 course.
Mastery of basic concepts in statistics and probability calculation, at the level of courses in the FSA1BA, INGE1BA, MATH1BA programs or the access minor in statistics, actuarial sciences and data science.
Mastery of basic concepts in statistics and probability calculation, at the level of courses in the FSA1BA, INGE1BA, MATH1BA programs or the access minor in statistics, actuarial sciences and data science.
Main themes
Statistical risk analysis in financial and alternative markets. Estimation of risk measures. Empirical properties of financial time series. Volatility and dependence models. Extreme value theory.
Content
Statistical risk analysis in financial and alternative markets. Estimation of risk measures. Empirical properties of financial time series. Volatility and dependence models. Extreme value theory.
Teaching methods
The class comprises theoretical sessions, exercises, and real world data examples demonstrated on a statistical platform.
Evaluation methods
70% Written exam
30%: Two projects, 15% each, using empirical data and a statistical software. The use of Artificial Intelligence software such as ChatGPT is not allowed for these projects.
30%: Two projects, 15% each, using empirical data and a statistical software. The use of Artificial Intelligence software such as ChatGPT is not allowed for these projects.
Online resources
MOOC Introduction to econometrics (in french) on edx: https://learning.edx.org/course/coursev1:
LouvainX+Louv14x+3T2024/home, to acquire the prerequisites in probability, econometrics and statistics
Optional multiple choice tests, not evaluated, to check for each chapter if the student has acquired the material of that chapter.
R code and scripts, and the data of the examples shown in class
Analytical and numerical exercises, discussed in class
LouvainX+Louv14x+3T2024/home, to acquire the prerequisites in probability, econometrics and statistics
Optional multiple choice tests, not evaluated, to check for each chapter if the student has acquired the material of that chapter.
R code and scripts, and the data of the examples shown in class
Analytical and numerical exercises, discussed in class
Bibliography
Main reference:
McNeil, A., Frey, R. and Embrechts, P. (2015) Quantitative
Risk Management, revised edition, Princeton UP.
Complementary literature
Bauwens, L., Hafner, C.M. and Laurent, S. (2012)
Volatility Models and Their Applications, Handbook in
Financial Engineering and Econometrics, Wiley. (in particular
the first review chapter of this handbook)
Franke, J., H¨ardle, W. and Hafner, C.M. (2015)
Statistics of financial markets, 4th ed., Springer.
Ruppert, D. (2011) Statistics and Data Analysis for
Financial Engeneering, Springer.
Tsay, R.S. (2010) Analysis of Financial Time Series, Wiley.
Tsay, R.S. (2013) An Introduction to Analysis of Financial
Data with R, Wiley.
McNeil, A., Frey, R. and Embrechts, P. (2015) Quantitative
Risk Management, revised edition, Princeton UP.
Complementary literature
Bauwens, L., Hafner, C.M. and Laurent, S. (2012)
Volatility Models and Their Applications, Handbook in
Financial Engineering and Econometrics, Wiley. (in particular
the first review chapter of this handbook)
Franke, J., H¨ardle, W. and Hafner, C.M. (2015)
Statistics of financial markets, 4th ed., Springer.
Ruppert, D. (2011) Statistics and Data Analysis for
Financial Engeneering, Springer.
Tsay, R.S. (2010) Analysis of Financial Time Series, Wiley.
Tsay, R.S. (2013) An Introduction to Analysis of Financial
Data with R, Wiley.
Teaching materials
- transparents sur moodle
Faculty or entity
