Coursepage of ESTIMATING VOLATILITY IN HIGH-FREQUENCY DATA/FINANCIAL ECONOMETRICS(GPP)

Information

Course ID: 41554

Location: Room 542 Mita campus

Time slot: Wednesday 4th period 14:45-16:15

Semester: Spring 2024

Description of the class

The main objective of this course is to develop the skills needed to do work in the industry or research with financial data. The course aims to provide students with techniques and receipts for estimation and assessment of quality of financial models. Each student is expected to choose a project related to the field of financial econometrics, and to make a report and a final presentation to the class. In addition, the student is expected to discuss about the advancement of the project at least once during the semester. The presentation can include theory, numerical simulations and/or data analysis.

Evaluation

The evaluation will be based on the report (50% of the final grade) and the final presentation (50% of the final grade). The report is expected to be typed in Latex, and should be around 15-20 page long. It should look as much as a reasearch paper as possible, with different sections and including a bibliography. The presentation will be 15 minute long, including 5 minutes for questions. Tentatively, this presentation will be held in a room on Keio campus (but it may also be conducted over Skype). You can use Overleaf where you can code directly online (and even share it with a friend). Also, you will have information for documentation and/or installing Latex at The Latex Project. There is no need to install Latex if you use Overleaf, so this is the simplest way to use it.

Choice of project

Students can choose by themselves a project in any aera closely related or not to volatility estimation. Note that this is my area of expertise (and also the title of this class), so of course I encourage students to choose a project related to volatility estimation. For those who do not have any background or any specific idea for their projects, I provide those two types of models to choose from:

  1. continuous-time stochastic processes: Here you can find the notes of Per Mykland.
  2. time series: You can also find the original paper on ARCH model from Robert Engle. Finally, you can also get the paper on GARCH model from Tim Bollerslev. Note that you need to be on Keio campus to download those papers for free.
Those are highly advanced Ph.D. level course notes and research papers, and this is expected that students are completely lost at first glance.

Lectures