Week 1
Overview #
This week, we will cover the following topics:
- Introduction to the course (Module 1): what are the broader questions we will answer in this subject, and how are they connected?
We will then more specifically introduce the Time Series component of the subject, which corresponds to the Section 2 of the CS2 syllabus. In particular, we will:
- explore some examples of time series which we will further analyse later in the time series modules
- introduce some basic models (which we will review in full detail in Module 9)
- discuss the concept of “Stationarity”
- finally, discuss the estimation of “correlation” in the context of time series (the presence of which, really, is the whole point of time series analysis)
See also detailed learning outcomes 2.2.1-2.1.3 and 2.1.5-2.1.6 of the CS2 syllabus
here
.
Main references and lectures #
Prerequisite knowledge #
Please review the
Prerequisite knowledge
page for this course. This is not exhaustive by any means, but provides minimum knowledge you should be comfortable with. Note that Tutorials in Week 1 are your opportunity to ask about those topics.
Module 1: Introduction #
Read:
Module 1: Introduction
SLIDES
Note: Typos and issues are being updated continuously throughout the semester. The online notes are always up-to-date, and can easily be read on a mobile device (version date is at the bottom). If you download a pdf version of the slides, a version date is also available on the first page. If you click on the link “latest slides” you will download the latest version. You can then compare the date and work out if it was updated.
annotated slides (UG)
|
annotated slides (PG)
Watch: refer to your lecture recording under “Lecture Capture” (
UG
/
PG
). This is where annotated slides will be made available, too.
Module 7 #
annotated slides (UG)
|
annotated slides (PG)
Watch: refer to your lecture recording under “Lecture Capture” (
UG
/
PG
). This is where annotated slides will be made available, too.
Additional preparation and resources #
Mandatory #
- Read the
Subject Guide
. - As outlined
above
, review the mathematical background and revisions as well as associated tutorial questions. - Chapter 1 of Wuthrich (2023) (for Module 1 and revisions)
- Chapter 1.0–1.5 of Shumway and Stoffer (2017)
- S6 (CS2 Time Series notes)
Optional #
- nil
Tutorials #
Note that a full list of exercises is available
here
. Please let us know of any mistake or required update on
Ed
.
Pre-Tutorial work #
Please study those questions before the tutorial.
Pre-Tutorial exercises are available in the
Pre-Tutorial book
, which already includes solutions. It is recommended to attempt the questions before looking at the solutions
Tutorial materials #
Some questions have been especially selected for the tutorials. Students should review and attempt those questions prior to their scheduled tutorial, after they complete the pre-tutorial work.
The
Tutorial book
includes all questions for the whole semester already, but solutions will only be added sequentially at the end of each week, as we work our way through the set.
Note that solutions will be gradually added to that same document. Hence it is not recommended to print it, as it will regularly change (typos will also dynamically be corrected).
This week #
The whole of Modules 1 and 7 are in scope for the week 1 tutorials. These cover a broad range of revisions, as well as Module 7. Note that the focus will be on Module 7 unless there are questions on Module 1.
Next week (week 2) #
Next week, we will discuss Module 8.
Additional questions #
The
additional questions
are here for reinforcement or revision, but are not the main focus of the tutorials. Solutions for those exercises are already available.
Preparation for assessment #
Mid-semester (15%) and final (60%) exams #
- Nothing to do for now - just don’t fall behind 😄.
Assignment (25%) #
- Nothing to do for now. Note that the assignment is on Module 7-9 and is due relatively early, so it’s worth paying attention!
References #
Shumway, Robert H., and David S. Stoffer. 2017. Time Series Analysis and Its Applications: With r Examples. Springer.
Wuthrich, Mario V. 2023. “Non-Life Insurance: Mathematics & Statistics.” Lecture notes. RiskLab, ETH Zurich; Swiss Finance Institute.