Data-driven stock quant investment with Python Part 1
In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.
1,849 learners
Level Basic
Course period Unlimited
[New lecture open] The last lecture of the ‘Python + Stock Quant Investment’ curriculum has opened.
Hello. This is Deepingsauce, Infraon knowledge sharer.
Finally, we have opened the 'Data-based Stock Quant Investment with Python Part 2' course that many of you have been eagerly waiting for.
- Link: Data-based stock quant investment with Python part 2 (click to go)
In this class, I have included the content that I ultimately wanted to convey to students when I decided to createa Python + Stock Quant Investment curriculum about a year ago, and this content marks the end of the curriculum.
Even though it has not even been a year since the first lecture was opened, 4,200 people have shown interest in the lecture. In order to repay that favor, we have organized the lecture with even more substantial content.
I hope that this lecture, as well as the lectures in this curriculum, will provide you with an opportunity to further improve the quality of your life.
Have a happy Chuseok holiday, and we will work hard to come back with better content in the future.
thank you