30188 - INTRODUCTORY FINANCIAL ECONOMETRICS
Course taught in English
Go to class group/s: 31
Class-group lessons delivered on campus
Students are expected to have already attended a core course in statistics and to be familiar with undergraduate calculus and linear algebra. Prior exposure to financial courses (financial markets and institutions, investments and corporate finance) is also recommended to understand the applications covered in class.
The objective of this course is to introduce the main econometric methods and techniques used in empirical finance. This is an ambitious task that brings together different type of knowledge: finance theory, statistics, programming. You learn how to use software(s) to specify, estimate and simulate model of financial data to be used for asset allocation, risk measurement and risk management. The teaching strategy is based on providing inputs (learning opportunities) to students that are supposed to active elaborate them to produce their knowledge. The course is designed to give opportunities. The decision of how many opportunities to take and how to take them is left to course participants. The final assessment is designed to evaluate the solidity of the foundation in the relevant tools for financial time-series modelling achieved by the students at the end of the course.
After going over `The introduction to the course’ lecture, we address the following:
- Basic knowledge in finance, statistics, probability.
- Introduction to programming.
- Returns: definitions, interpretation; measurement; data collection; analysis.
- Modeling and Simulating Returns.
- Estimating Linear Models of Returns.
- Interpreting Regression Results.
- TBA.
- High-order risk sources.
- The objective of this course is to introduce the main econometric methods and techniques used in empirical finance. This is an ambitious task that brings together different type of knowledge: finance theory, statistics, programming. You learn how to use software, to specify, estimate and simulate model of financial data to be used for asset allocation, risk measurement and risk management. The course is designed to give opportunities. The decision of how many opportunities to take and how to take them is left to course participants.
- Apply econometric techniques to study returns both in the time-series and in the cross section.
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Individual assignments
The main inputs provided to the students are references, slides, notes, draft Python codes and exercises designed to provide challenges that stimulate learning. The empirical applications are based on databases freely available on the web.
Continuous assessment | Partial exams | General exam | |
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Their final grade will be a weighted average of:
-- their homeworks;
-- their in-class quiz ( provided in the middle of the semester);
and
-- their final exam.
This computation of the grade applies to students taking the exam in December or January. In all other cases, the final grade will depend solely on the performance in the final exam.
All homeworks can be delivered online. Hence non-attending students can deliver their HWs as attending students. Their final grade will be a weighted average of both their homeworks and their final exam. This computation of the grade applies to students taking the exam in December or January. In all other cases, the final grade will depend solely on the performance in the final exam.
- MAIN BOOK: “Introductory Econometrics for Finance” by Chris Brooks, 2nd Edition
- J. COCHRANE, Asset pricing. Revised Edition. (only 2 chapters)