This class exists in these courses :
• IÉSEG > MSc in Finance > Semester 1 > 2,00 ECTS

Prerequisites

No special preprequisites apply.

Learning outcomes

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.

Course description

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.

Class type

Class structure

Teaching methods

• E-learning
• Interactive class
• Project work

Assessment

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.

Recommended reading

• Richard A. DeFusco, CFA, Dennis W. McLeavey, Jerald E. Pinto, David E. Runkle, CFA. Quantitative Investment Analysis (2011). John Wiley & Sons, 2nd edition. 600p. -

Internet resources

• IESEG Online