Sungkyunkwan University
Using R for Regression and Machine Learning in Investment
Sungkyunkwan University

Using R for Regression and Machine Learning in Investment

Taught in English


Gain insight into a topic and learn the fundamentals

Youngju Nielsen

Instructor: Youngju Nielsen

Intermediate level

Recommended experience

17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understanding the basic common concept of machine learning

  • Familiarizing with most commonly used methodology, regression

  • Distinguishing in-sample and out-of-sample results and leading to well-performing models in a real-life

Details to know

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There are 2 modules in this course

Understand the characteristics of predictive models and various data in investment The instructor will give you the big picture of the algorithm-driven investment decision-making process. After you understand that, we will review the regression concept and connect it with the core concepts of machine learning methodologies.

What's included

5 videos9 readings

Use regression methodology for various investment analysis purpose and improve models by using ridge, lasso, and logistic regression. First of all, you will learn how you can gauge investment strategy using backtesting. You learned the first component of investment strategy, returns, in the first week. You will expand your study to assessing investment risks. To understand stocks' risks, you will calculate covariance and correlation matrix using historical time-series stock return data. You will extend this to market factor and three-factor models to understand the risk you are facing with your investment. Finally, you will calculate factor exposure using a 3-factor model from week 2 and separate common factor risk and idiosyncratic risk of the stock.

What's included

5 videos10 readings1 quiz


Instructor ratings
4.6 (5 ratings)
Youngju Nielsen
Sungkyunkwan University
3 Courses2,667 learners

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Recommended if you're interested in Finance

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