OUR ACADEMIC DEPARTEMENTS |
Lesson details
FINANCIAL ECONOMETRICS | |||
2023-2024 | EnIESEG School of Management
(
IÉSEG
)
| ||
Class code : | 2324-IÉSEG-MAC1S1-FIN-MACCE03UE | FINANCE |
Level | Year | Period | Language of instruction |
---|---|---|---|
MSc in Accounting, Audit and Control | 1 | S1 | EnEnglish |
Academic responsibility | F.CASALIN |
---|---|
Lecturer(s) | F.CASALIN |
- This class exists in these courses :
- IÉSEG > MSc in Accounting, Audit & Control > Semester 1 > 2,00 ECTS
Prerequisites
Students are expected to have a general understanding of the following concepts: random variables; basic probability distributions such as Gaussian, Student t, Chi-square and Fisher distributions; statistics such as expectation/mean, variance/standard deviation, correlation; hypothesis testing, p-values (i.e. critical thresholds for tests) and confidence intervals.
Learning outcomes
AACSB AoL 3C - Breakdown complex organizational problems using the appropriate methodology
AACSB AoL 5B - Construct expert knowledge from cutting-edge information
AACSB AoL 7A - Demonstrate an expertise on key concepts, techniques and trends in their professional field
AACSB AoL 7D - Be a reference point for expertise-related questions and ambiguities
Course description
Based on real datasets and practical applications (on Excel and Eviews), the lectures will cover the following topics:
- Correlation tests to check for linearity between variables;
- Simple linear regression;
- Multiple linear regression;
- Graphical investigation of breaks in time series and usage of dummy variables;
- Validation of regressions (i.e. fulfillment of key OLS assumptions, residuals’ autocorrelation and heteroskedasticity)
- Use and limitations of linear regressions.
Class type
Class structure
Type of course | Numbers of hours | Comments | |
---|---|---|---|
Independent work | |||
E-Learning | 8,00 | Through the use of Excel and Eviews | |
Independent study | |||
Estimated personal workload | 10,00 | ||
Group Project | 16,00 | ||
Face to face | |||
Interactive class | 16,00 | In class applications with Eviews and Excel | |
Total student workload | 50,00 |
Teaching methods
- Case study
- Coaching
- E-learning
- Interactive class
- Project work
- Tutorial
Assessment
1) Financial econometrics project (each group of students works on a selected dataset).
2) A final exam composed of problems, course questions (students can bring a two-sided A4 cheat sheet only devoted to valuation formulas), and in class applications using Eviews to analyse a given dataset.
Type of control | Duration | Number | Percentage break-down |
---|---|---|---|
Others | |||
Group Project | 0,00 | 1 | 50,00 |
Final Exam | |||
Written exam | 2,00 | 1 | 50,00 |
TOTAL | 100,00 |
Recommended reading
- R.A. DeFusco, D.W. McLeavey, J.E. Pinto, M.J.P. Anson, D.E. Runkle, 2015, Quantitative Investment Analysis, 3rd Edition, Wiley -
Internet resources
* This information is non-binding and can be subject to change