Actualités et agenda
Nos formations
Établissement
Langue d'enseignement
English
Matières
QUANTITATIVE METHODS
Responsable(s)
J.SIANI
Intervenant(s)
Joseph Siani
Présentation
Prérequis
No special preprequisites apply.
Objectifs
At the end of the course, the student should be able to :- define a random variable, an event, mutually exclusive and exhaustive events;
- distinguish between unconditional and conditional probabilities;
- master the probabilistic tools used in investment analysis (learning objective AACSB)
- define, calculate and interpret the main descriptive statistics (mean, standard deviation, skewness and kurtosis);
- describe and explain the main properties of common probability distributions (uniform, binomial, normal and lognormal distributions);
- calculate and interpret a confidence interval for a population mean;
- identify appropriate test statistics and interpret the results of hypothesis testing concerning population means and variances.
- distinguish between unconditional and conditional probabilities;
- master the probabilistic tools used in investment analysis (learning objective AACSB)
- define, calculate and interpret the main descriptive statistics (mean, standard deviation, skewness and kurtosis);
- describe and explain the main properties of common probability distributions (uniform, binomial, normal and lognormal distributions);
- calculate and interpret a confidence interval for a population mean;
- identify appropriate test statistics and interpret the results of hypothesis testing concerning population means and variances.
Présentation
Topic 1. Probability concepts (unconditional and conditional probabilities, Bayes' formula)
Topic 2. Probability distributions and descriptive statistics (mean, standard deviation, skewness, kurtosis).
Topic 3. Application of probability distributions: simulation analysis (Monte Carlo simulation).
Topic 4. Sampling and estimation.
Topic 5. Hypothesis testing.
Topic 2. Probability distributions and descriptive statistics (mean, standard deviation, skewness, kurtosis).
Topic 3. Application of probability distributions: simulation analysis (Monte Carlo simulation).
Topic 4. Sampling and estimation.
Topic 5. Hypothesis testing.
Modalités
Organisation
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 16,00 | ||
| Autoformation | |||
| Lecture du manuel de référence | 10,00 | ||
| Travail personnel | |||
| Group Project | 8,00 | ||
| Individual Project | 8,00 | ||
| Charge de travail personnel indicative | 8,00 | ||
| Overall student workload | 50,00 | ||
Évaluation
The course assessment is based on five equally-weighted home assignments (individual and group projects) and a final exam accounting for 40% of the final grade.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Examen (final) | |||
| Examen écrit | 2,00 | 1 | 50,00 |
| Autres | |||
| Projet Collectif | 0,00 | 4 | 40,00 |
| Contrôle continu | |||
| Participation | 16,00 | 1 | 10,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliographie
Richard A. DeFusco, CFA, Dennis W. McLeavey, Jerald E. Pinto, David E. Runkle, CFA. Quantitative Investment Analysis (2011). John Wiley & Sons, 2nd edition. 600p. -
Ressources Internet