Advanced Portfolio Construction and Analysis with Python (Coursera)

As we cover the theory and math in lecture videos, we'll also implement the concepts in Python, and you'll be able to code along with us so that you have a deep and practical understanding of how those methods work. By the time you are done, not only will you have a foundational understanding of modern computational methods in investment management, you'll have practical mastery in the implementation of those methods. If you follow along and implement all the lab exercises, you will complete the course with a powerful toolkit that you will be able to use to perform your own analysis and build your own implementations and perhaps even use your newly acquired knowledge to improve on current methods.

Course 2 of 4 in the Investment Management with Python and Machine Learning Specialization.

What You Will Learn

- Analyze style and factor exposures of portfolios

- Implement robust estimates for the covariance matrix

- Implement Black-Litterman portfolio construction analysis

- Implement a variety of robust portfolio construction models

Syllabus

WEEK 1: Style & Factors

WEEK 2: Robust estimates for the covariance matrix

WEEK 3: Robust estimates for expected returns

WEEK 4: Portfolio Optimization in Practice