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.
The Fundamental of Data-Driven Investment
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The Fundamental of Data-Driven Investment
Instructor: Youngju Nielsen
2,020 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
18 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Build an investment factor model using regression methodology
Employ optimization algorithm using R standard library
Explain the portfolio performance
Skills you'll gain
Details to know
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Assessments
5 assignments
Taught in English
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There are 4 modules in this course
You will learn how to read stock price time-series data from CSV file and analyze the past return data. After you understand the past return data, you will determine what impacts stocks' return and make a future return forecasting model using regression.
What's included
6 videos10 readings2 assignments
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 videos9 readings1 assignment
In this week, This week, you will download various global ETFs and make global asset allocation portfolio using mean-variance optimization.
What's included
3 videos6 readings1 assignment
You will learn about various portfolios other than a mean-variance optimized portfolio. Additionally, you will add a constraint to your portfolio optimization. In reality, you might need to consider more than volatility measured by return standard deviation. You will grasp the concepts of VaR, maximum drawdowns and CvaR, etc.
What's included
5 videos10 readings1 assignment
Instructor
Offered by
Recommended if you're interested in Data Analysis
Sungkyunkwan University
EDHEC Business School
University of Michigan
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