Financial Econometrics Case Study

URL study guide

https://studiegids.vu.nl/en/courses/2024-2025/E_EORM_FECS

Course Objective

To learn to work with bad datasets of high-frequency trade data. To learn to compute and understand realized volatility measures. To learn to implement advanced time series models and to use these for forecasting. To learn to write a report on advanced methods and models. To learn to give an oral presentation about the most important aspects. To learn to work as a group.

Course Content

The student uses high-frequency trade data to compute realized measures of volatility. These daily measures of realized volatility are used to estimate time series models
- realized GARCH (realized Generalized Autoregressive Conditional Heteroskedasticy) and realized GAS (realized Generalized Autoregressive Score)
- which are used for forecasting future volatility. The performance of these advanced models is compared with simpler models such as regular GARCH and GAS models. Financial risk measures such as Value-at-Risk are also considered.

Teaching Methods

Introductory lecture, discussions per groups, plenary sessions of final presentations.

Method of Assessment

Groups of students need to submit a written report, their programming code and an oral presentation. At the end of the course all students need to assess the quality and quantity of the inputs of their groupmates and themselves, using FeedbackFruits Group Member Evaluation (or a similar system). Based on the report, code and presentation of the group, and these individual inputs from FeedbackFruits Group Member Evaluation, students will get an individual grade.