Description
This is a course about statistical inference and its applications to problems from finance. It consists of theory based lectures, homework problem sheets and a computational project.
The course covers classical topics from statistical inference such as point estimation, confidence sets and hypothesis testing. Subsequently parametric and non-parametric statistical models will be discussed, as well as the Bayesian approach to inference. Time permitting we will also cover some elements of modern machine learning techniques. Examples from finance will be given throughout the course.
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Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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