ETH Zürich - D-MATH - SFG (Stochastic Finance Group) - HOME - update on 2017-11-01

Interest rate theory for CAS 2017

As a main reference for this lecture we shall use the comprehensive book Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging. The book contains of course much more information and is by no means a pre-requisite.

As a preparation for the lecture course please just get acquainted with Jupyter notebooks: I shall use notebooks for the presentation based on my lectures slides on interest rate theory, and several pieces of code from the relevant notebook be found under CAS_interest_rates_20171130 in html version of under CAS_interest_rates_20171130 as ipythin notebook, also yield curve data to run the yield curve experiments are provided. Further notebooks on yield curve bootstrapping, calibration and simulation will follow and be linked on this webpage. If you need information on the current Euro area yield curves, please take a look at the webpage of ECB.

The goal of the lecture to provide a basic knowledge in interest rate modeling as well as concrete, high level and industry relevant implementations of this knowledge. Even if one is not in programming Python so far, it will help to sharpen intuition on the material and cover the relevant ideas by going through the course notebooks.

A notebook for the exam preparation with typical exam questions can be found here. If there are any further questions do not hesitate to contact me.