Data is an essential tool for every sector, including investments. With data analytics, investment strategies, portfolio management, and decision-making are algorithm and data-driven, reducing the risk factors associated with investment.

This two-week course from Sungkyunkwan University (SKKU) will introduce you to fundamental machine learning and regression methodologies and help you improve your R programming skills to use data analysis in solving investment problems.

Understand how to use regression for data analysis of investments

This course will guide you through using regression methodology for various investment analysis purposes by using Ridge, Lasso, and logistic regression.

You’ll begin by gauging investment strategy using backtesting and learn about regression methodology, how to solve classification problems with logistic regression, and analyse data using the Fama-Macbeth Regression method.

Create a machine learning model to predict the movement of the stock market

On this course, you’ll take the first step toward using machine learning methodologies in solving investment problems.

Not only will you develop a firm grasp on the core concepts of machine learning, but you’ll also learn about machine learning models that are used to predict the movement of the stock market and create your own macro factor model using R programming.

Learn with the experts at Sungkyunkwan University

The instructor of this course has more than 15 years of experience with algorithmic trading and investment portfolio management experience in the G10 markets at Wall Street major firms.

With her expertise and guidance, you’ll be well-equipped to apply regression and machine learning methods to real data and improve your investment strategies.