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Establishment
Language of instruction
English
Teaching content
FINANCE
Training officer(s)
J.LEFEBVRE, R.BEAUPAIN
Stakeholder(s)
R.BEAUPAIN, Jérémie LEFEBVRE
Présentation
Prerequisite
Probability and statistics, namely:
- Random variables (discrete, continuous), probability distributions, conditional and unconditional probability
- Sample average, variance and standard deviation of a random variable (e.g. average and standard deviation of daily stock returns)
- Hypothesis testing on the mean of a random variable (e.g. testing whether the average daily return of a stock is different from zero)
- The main distribution functions: normal (Gaussian) and Student T distribution; Ability to read a statistical table for those distributions
Students who do not have these prerequisites should expect to spend more time reading the reference book and doing extra exercises.
- Random variables (discrete, continuous), probability distributions, conditional and unconditional probability
- Sample average, variance and standard deviation of a random variable (e.g. average and standard deviation of daily stock returns)
- Hypothesis testing on the mean of a random variable (e.g. testing whether the average daily return of a stock is different from zero)
- The main distribution functions: normal (Gaussian) and Student T distribution; Ability to read a statistical table for those distributions
Students who do not have these prerequisites should expect to spend more time reading the reference book and doing extra exercises.
Goal
At the end of the course, the student should be able to:
- Breakdown complex organizational problems using the appropriate methodology
- Construct expert knowledge from cutting-edge information
- Employ state-of-the-art management techniques
- Make effectual organizational decisions
- Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
- Effectively apply in-depth specialized knowledge to take advantage of contemporary opportunities in their professional field
- Conduct an empirical quantitative, financial analysis: specifying, estimating and interpreting (statistically and economically) the output of a regression model
- Use the Thomson Reuters Eikon terminal to find appropriate data and retrieve and manipulate historical records in Excel
- Breakdown complex organizational problems using the appropriate methodology
- Construct expert knowledge from cutting-edge information
- Employ state-of-the-art management techniques
- Make effectual organizational decisions
- Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
- Effectively apply in-depth specialized knowledge to take advantage of contemporary opportunities in their professional field
- Conduct an empirical quantitative, financial analysis: specifying, estimating and interpreting (statistically and economically) the output of a regression model
- Use the Thomson Reuters Eikon terminal to find appropriate data and retrieve and manipulate historical records in Excel
Presentation
The purpose of this course is to give a sufficient background to students for them to apply statistics and econometrics techniques to analyze markets and companies.
The course includes a thorough learning of the use of Thomson Reuters financial data terminals.
In addition, the package R is used for running quantitative analyses. R is a free and open source software widely used in the industry and by academics for quantitative analysis, and it has a vast community of users (see https://cran.r-project.org/). The professor will offer coaching sessions to help students learn the software.
The course includes the following activities:
- 8 hours of interactive courses to learn Thomson Reuters and preprate financial data sets
- 3 hours of coaching to get hands on R
- 18 hours of interactive courses about econometrics and quantitative analysis
- 6 hours of computer tutorials on Thomson Reuters terminals to work on applications
The content of the course is the following:
1 Data download, manipulation and cleaning on Thomson Reuters terminals
2 Correlation analysis
Applications: Analysis of co-movements of stock markets around the world
3 Simple OLS regressions
Applications: Estimate the beta of the CAPM (Capital Asset Pricing Model)
4 Multiple OLS regressions
Application: Multifactor models for pricing stocks
5 Assumptions of the OLS regressions and diagnostic tests
Application: Analyzing corporate financial decisions of listed companies
6 Issues in multiple OLS regressions
a) Dummy variables for discrete or qualitative observations
Application: Analysis of seasonality on stock markets
b) Time series data
Application: Analysis and forecasting of real estate prices
The course includes a thorough learning of the use of Thomson Reuters financial data terminals.
In addition, the package R is used for running quantitative analyses. R is a free and open source software widely used in the industry and by academics for quantitative analysis, and it has a vast community of users (see https://cran.r-project.org/). The professor will offer coaching sessions to help students learn the software.
The course includes the following activities:
- 8 hours of interactive courses to learn Thomson Reuters and preprate financial data sets
- 3 hours of coaching to get hands on R
- 18 hours of interactive courses about econometrics and quantitative analysis
- 6 hours of computer tutorials on Thomson Reuters terminals to work on applications
The content of the course is the following:
1 Data download, manipulation and cleaning on Thomson Reuters terminals
2 Correlation analysis
Applications: Analysis of co-movements of stock markets around the world
3 Simple OLS regressions
Applications: Estimate the beta of the CAPM (Capital Asset Pricing Model)
4 Multiple OLS regressions
Application: Multifactor models for pricing stocks
5 Assumptions of the OLS regressions and diagnostic tests
Application: Analyzing corporate financial decisions of listed companies
6 Issues in multiple OLS regressions
a) Dummy variables for discrete or qualitative observations
Application: Analysis of seasonality on stock markets
b) Time series data
Application: Analysis and forecasting of real estate prices
Modalités
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 18,00 | In normal classroom | |
| Travaux dirigés | 14,00 | In Financial Markets Lab | |
| Coaching | 3,00 | Coaching to learn R | |
| Autoformation | |||
| Lecture du manuel de référence | 8,00 | Mandatory book reading | |
| Travail personnel | |||
| Group Project | 15,00 | Case studies | |
| Charge de travail personnel indicative | 20,00 | Studying and solving exercises | |
| Individual Project | 22,00 | Thomson Reuters certification and individual assignments | |
| Overall student workload | 100,00 | ||
Evaluation
It is mandatory to complete successfully the Thomson Reuters Certification to validate this course.
The final grade will be composed of selected exercises to do at home, two case studies to do in teams, an individual take-home assignment and a written final exam.
The final grade will be composed of selected exercises to do at home, two case studies to do in teams, an individual take-home assignment and a written final exam.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Examen (final) | |||
| Examen écrit | 2,00 | 1 | 30,00 |
| Autres | |||
| Etude de cas | 3,00 | 1 | 30,00 |
| Rapport écrit | 1,00 | 1 | 20,00 |
| Contrôle continu | |||
| Exercices | 1,00 | 1 | 20,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliography
CFA Institute, "Quantitative Investment Analysis", 3rd Edition, Wiley -
Internet resources