You can watch the first lecture for free! (See the video above).
Master Hierarchical Clustering: Identify hidden relationships between asset classes using advanced clustering algorithms, giving you a new edge in asset class due diligence and investment strategy development.
Decode Model Behavior with Shapley Values: Gain deep insights into the driving forces behind your models and discover how to better interpret and trust your results by using Shapley values for clearer explanations.
Enhance Factor Models with Lasso Regression: Improve your understanding of investment behavior by applying Lasso regression to sharpen factor models, helping you make more informed, data-driven investment decisions.
Optimize Tactical Asset Allocation with Deep Learning: Learn how to leverage cutting-edge deep learning techniques to anticipate market shifts and make smarter allocation decisions between bonds and equities.
In this section, we will introduce you to the course outline and what you will learn. We will also introduce you to our teaching method which includes quizzes, and teaching you how to think critically about what you will be learning.
In this case study, we show you how clustering analysis can help you understand how asset classes behave and if various asset classes behave in similar ways according to various risk and return metrics.
In this case study, we will show you how powerful Shapley values can be for identifying feature importance in machine learning models. We will apply these values to our results from the first case study.
Please make sure to download the needed files provided in this section.
In this case study, we demonstrate how you can create improved returns-based factor models by using an advanced regression technique called LASSO.
In our fourth case study, we will demonstrate how you can assess the probability of SPY going up or down the next day using deep learning. This is a great example of how we can alter our asset allocation based on signals derived from machine learning.
This short video ties everything together and shows how the case studies affect the portfolio matrix and investment management workflow.
This section contains the files needed for this course. Please make sure to watch the tutorial video on how to use the main_functions.py file and how to import them.
In this project, you will reinforce what you learned in case study 1 of our Introduction to Machine Learning in Portfolio Construction course.
You will classify various fixed income funds based on different risk and return features.