- Level Professional
- المدة 18 ساعات hours
- الطبع بواسطة Sungkyunkwan University
-
Offered by
عن
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.الوحدات
L1. Brief History on Investing, Machine Learning and Alternative Data
1
Videos
- L1. Brief History on Investing, Machine Learning and Alternative Data
2
Readings
- Learning Content
- References
L2. Ingredients for Maching Learning Based Investment
1
Videos
- L2. Ingredients for Maching Learning Based Investment
2
Readings
- Learning Content
- References
L3. Big Picture of Alorithm-Driven Investment
1
Videos
- L3. Big Picture of Alorithm-Driven Investment
1
Readings
- Learning Content
L4. Understanding the Characteristics of Factors
1
Videos
- L4. Understanding the Characteristics of Factors
2
Readings
- Learning Content
- References
L5. Understanding Machine Learning Concepts
1
Videos
- L5. Understanding Machine Learning Concepts
2
Readings
- Learning Content
- References
L6. Handling Data with Different Frequencies
1
Assignment
- Macro factor model
1
Videos
- L6. Handling Data with Different Frequencies
2
Readings
- Learning Content
- References
L7. Analyzing Data Using Fama-Macbeth Regression
1
Videos
- L7. Analyzing Data Using Fama-Macbeth Regression
2
Readings
- Learning Content
- References
L8. Predictive Models
1
Videos
- L8. Predictive Models
2
Readings
- Learning Content
- References
L9. Making a Model that Performs Well in Real Life
1
Videos
- L9. Making a Model that Performs Well in Real Life
2
Readings
- Learning Content
- References
L10. Logistic Regression - Solving Classification Problems
1
Videos
- L10. Logistic Regression - Solving Classification Problems
2
Readings
- Learning Content
- References
Auto Summary
"Using R for Regression and Machine Learning in Investment" is a professional-level course designed for individuals with a basic understanding of financial economics and R programming. Taught by an expert instructor, this course focuses on applying various regression methodologies and machine learning concepts to solve investment problems. With a duration of 1080 minutes, it offers hands-on practice in R, covering topics like logistic, Lasso, and Ridge regressions. Ideal for those looking to enhance their investment analysis skills, the course is available through Coursera with Starter and Professional subscription options.

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