Offered By

Using R for Regression and Machine Learning in Investment

Sungkyunkwan University

About this Course

In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning. 
The course is designed with the assumption that most students already have a little bit of knowledge in financial economics and R programming. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. Students are also expected to know of the instructors' 1st course, 'Fundamental of data-driven investment.'

The instructor will explain the detail of R programming. It will be an excellent course for you to improve your programming skills but you must have basic knowledge in R. If you are very good at R programming, it will provide you with an excellent opportunity to practice again with finance and investment examples.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

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Coursera Labs

Includes hands on learning projects.

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Intermediate Level

Introductory statistics, introductory financial economics, and R programming

Approx. 17 hours to complete

English

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What you will 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

Skills you will gain

Investment Management
Machine Learning
R Programming
regression

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

Introductory statistics, introductory financial economics, and R programming

Approx. 17 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Youngju Nielsen

1,842 Learners

2 Courses

Offered by

Sungkyunkwan University

Sungkyunkwan University (SKKU) was established in 1398 as the highest national educational institute in the early years of Joseon Dynasty in Korea. At present with the support of the world-renowned global company Samsung, SKKU is leading the development of higher education in Korea. SKKU actively encourages international collaboration through developing cutting-edge research and educational programs with its global partners.

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Syllabus - What you will learn from this course

Week1

Week 1

7 hours to complete

Understanding the big picture of the algorithm-driven investment decision-making process using machine learning and review of regression methodology

7 hours to complete

5 videos (Total 82 min), 9 readings

5 videos

L1. Brief History on Investing, Machine Learning and Alternative Data13mL2. Ingredients for Maching Learning Based Investment14mL3. Big Picture of Alorithm-Driven Investment17mL4. Understanding the Characteristics of Factors19mL5. Understanding Machine Learning Concepts15m

9 readings

Learning Content1hReferences10mLearning Content1hReferences10mLearning Content1hLearning Content1hReferences10mLearning Content1hReferences10m

Week2

Week 2

10 hours to complete

Regression and beyond

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.

10 hours to complete

5 videos (Total 96 min), 10 readings, 1 quiz

5 videos

L6. Handling Data with Different Frequencies19mL7. Analyzing Data Using Fama-Macbeth Regression18mL8. Predictive Models20mL9. Making a Model that Performs Well in Real Life20mL10. Logistic Regression - Solving Classification Problems17m

10 readings

Learning Content1hReferences10mLearning Content1hReferences10mLearning Content1hReferences10mLearning Content1hReferences10mLearning Content1hReferences10m

1 practice exercise

Macro factor model3h

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Is financial aid available?
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Using R for Regression and Machine Learning in Investment

Using R for Regression and Machine Learning in Investment

About this Course

What you will learn

Skills you will gain