Ementorhub

What you'll 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

Skills you'll gain

Asset Management

Statistical Methods

Portfolio Management

Financial Modeling

Financial Market

Estimation

Time Series Analysis and Forecasting

Risk Management

Return On Investment

Investment Management

Regression Analysis

Risk Analysis

Python Programming

There are 4 modules in this course

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.

Robust estimates for the covariance matrix

Robust estimates for expected returns

Portfolio Optimization in Practice