Course 3: Data Science for Finance

The course “Data Science for Finance” covers multivariate econometrics and advanced inference for stress-testing and portfolio construction.

In particular, this course covers the following topics:

• Dependence and copulas
• Multivariate discrete time processes: random walk, VARMA, linear state space models, GARCH
• Continuous time processes: Brownian motion, Poisson, Levy, Ornstein-Uhlenbeck, stochastic volatility
• Black-Litterman and minimum relative entropy

For a detailed list of topics, refer to the Syllabus here below (expand the dropdown).

You can choose to complete an optional project at the end of this course that will count as the Practical Project towards the attainment of the ARPM Certification.