- Level Foundation
- Duration 19 hours
- Course by Sungkyunkwan University
-
Offered by
About
In this course, the instructor will discuss the fundamental analysis of investment using R programming. 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 do the elemental analysis for investment management that you might need to do in your job every day. Additionally, the study note to do using Python programming will be provided. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics. 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. The instructor will explain the detail of R programming for beginners. It will be an excellent course for you to improve your programming skills. If you are very good at R programming, it will provide you an excellent opportunity to practice again with finance and investment examples. Professor Youngju Nielsen creates the course with the assistants of Keonwoo Lim and Jeeun Yuen. =========================================================================================== Coursera Course recommendations before this course for those who are not familiar with basic R programming:Modules
L0. Course Introduction
1
Videos
- Course Introduction
L1. What is Quantitative Investing?
1
Assignment
- Checking Your Basic R Knowledge
1
Videos
- What is Quantitative Investing?
L2. Description of the Stock Price Data
1
Videos
- Description of the Stock Price Data
3
Readings
- Python Script for Lecture 2
- [Optional] R Script for Lecture 2
- DIS Data
L3. How to Analyze Asset Returns
1
Videos
- How to Analyze Asset Returns
2
Readings
- Python Script for Lecture 3
- [Optional] R Script for Lecture 3
L4. What Do Determine Future Investment Returns?
1
Videos
- What Do Determine Future Investment Returns?
3
Readings
- Python Script for Lecture 4
- [Optional] R Script for Lecture 4
- SP500 Data
L5. Forecasting Investment Returns with Factors
1
Videos
- Forecasting Investment Returns with Factors
2
Readings
- Python Script for Lecture 5
- [Optional] R Script for Lecture 5
Practice Project Week 1
1
Assignment
- Practice Project Week 1
L6. How to Evaluate Investment Strategies?
1
Videos
- How to Evaluate Investment Strategies?
2
Readings
- Python Script for Lecture 6
- [Optional] R Script for Lecture 6
L7. How to Assess the Risk?
1
Videos
- How to Assess the Risk?
2
Readings
- Python Script for Lecture 7
- [Optional] R Script for Lecture 7
L8. Analyzing Market Risk Using CAPM
1
Videos
- Analyzing Market Risk Using CAPM
2
Readings
- Python Script for Lecture 8
- [Optional] R Script for Lecture 8
L9. How to Create a 3 Factor Model with the Tidyverse Package
1
Videos
- How to Create a 3 Factor Model with the Tidyverse Package
2
Readings
- Python Script for Lecture 9-10
- [Optional] R Script for Lecture 9
L10. What is Risk Factor Analysis and Idiosyncratic Risk Analysis?
1
Videos
- What is Risk Factor Analysis and Idiosyncratic Risk Analysis?
1
Readings
- [Optional] R Script for Lecture 10
Practice Project Week 2
1
Assignment
- Practice Project Week 2
L11. How to Get Data to Make a Portfolio of Multiple Assets
1
Videos
- How to Get Data to Make a Portfolio of Multiple Assets
2
Readings
- Python Script for Lecture 11
- [Optional] R Script for Lecture 11
L12. How to preparing Data for Portfolio Optimization
1
Videos
- How to preparing Data for Portfolio Optimization
2
Readings
- Python Script for Lecture 12
- [Optional] R Script for Lecture 12
L13. How to Create an Optimized Portfolio using Historical Data
1
Videos
- How to Create an Optimized Portfolio using Historical Data
2
Readings
- Python Script for Lecture 13
- [Optional] R Script for Lecture 13
Practice Project Week 3
1
Assignment
- Practice Project Week 3
L14. Drawing and Comparing Multiple Portfolios
1
Videos
- Drawing and Comparing Multiple Portfolios
2
Readings
- [Optional] R Script for Lecture 14
- SP500MonthlyExcel Data
L15. How to Summarize the Result from Optimization
1
Videos
- How to Summarize the Result from Optimization
2
Readings
- Python Script for Lecture 15
- [Optional] R Script for Lecture 15
L16. How to Add Constraints to Portfolio Optimization
1
Videos
- How to Add Constraints to Portfolio Optimization
2
Readings
- Python Script for Lecture 16
- [Optional] R Script for Lecture 16
L17. Evaluate Asset Performance Using PerformanceAnalytics Package
1
Videos
- Evaluate Asset Performance Using PerformanceAnalytics Package
2
Readings
- Python Script for Lecture 17
- [Optional] R Script for Lecture 17
L18. How to Compare Constrained and Unconstrained Portfolios
1
Videos
- How to Compare Constrained and Unconstrained Portfolios
2
Readings
- Python Script for Lecture 18
- [Optional] R Script for Lecture 18
Final Project
1
Assignment
- Final Project
Auto Summary
Discover the essential techniques of "The Fundamental of Data-Driven Investment," a comprehensive course in Big Data and Analytics tailored for aspiring finance professionals. Guided by Professor Youngju Nielsen, with support from assistants Keonwoo Lim and Jeeun Yuen, this course delves into investment analysis fundamentals using R programming, offering practical, hands-on experience. Designed for those with a basic understanding of financial economics, this course covers core topics like stocks, bonds, balance sheets, and earnings, and integrates introductory statistics concepts such as mean, median, distribution, and regression. Beginners in R programming will benefit from detailed explanations, while those proficient in R can sharpen their skills through finance and investment examples. Additionally, study notes for Python programming are provided to broaden your analytical toolkit. This 1140-minute foundational course is available through a Coursera Starter subscription, making it accessible for those eager to enhance their data-driven investment strategies. Ideal for professionals looking to advance their careers in finance, this course is both informative and engaging, equipping you with the necessary skills for everyday investment management tasks. For those new to R programming, Coursera recommends the following preparatory courses: - [Getting Started with R](https://www.coursera.org/projects/getting-started-with-r) - [Introduction to Business Analytics with R](https://www.coursera.org/learn/business-analytics-r) - [Statistics with Python](https://www.coursera.org/specializations/statistics-with-python) Embark on this learning journey to master data-driven investment analysis and elevate your financial acumen with expert guidance.

Youngju Nielsen