Formation/Cours

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.

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.