Data Science & Machine Learning for Asset Management Specialization

Deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions

Course 1: Intro. to Portfolio Construction and Analysis with Python

The first course will give you a foundational understanding of modern computational methods in investment management and a practical mastery in the implementation of those methods.

Week 1: Analysing Returns

• Fundamentals of risk and return
• Beyond the Guassian Case: Extreme risk estimates

Week 2: An Intro. to Portfolio Optimization

• Intro. to Optimization and the Efficient Frontier
• Implementing Markowitz

Week3: Beyond Diversification

• Calibration and Implementation Challenge
• Monta Carlo Simulation

Week4: Into. to Asset Liability Management

• Liability Driven Inverting
• Liability Driven Investing Paradigm in terms of a liability-hedging portfolio and a performance-seeking portfolio

Course 2: Advanced Portfolio Construction and Analysis with Python

Week 1: Style & Factors

Week 2: Robust Estimate for the Covariance Matrix

Week 3: Robust Estimates for Expected Returns

Week 4: Portfolio Optimization in Practice

Course 3: Python and Machine Learning for Asset Management

Week 1: Fundamentals of Machine Learning

Week 2: Machine Learning Techniques for robust estimation of factor models

Week 3: Machine Learning Techniques for efficient portfolio diversification

Week 4: Machine Learning Techniques for regime analysis

Week 5: Identifying Recessions, Cash Regimes and Feature Selection

Course 4: Python and Machine Learning for Asset Management with Alternative Data Sets

Week 1: Consumption

Week 2: Textual Analysis for Finacial Applications

Week 3: Processing Corporate Filings

Week 4: Using Media-Derived Data