Data-driven stock quant investment with Python Part 2
This lecture is a follow-up lecture to 'Python Data-Based Stock Quant Investment Part 1'. If Part 1 was more of an introduction, Part 2 is an in-depth lecture that focuses on the entire flow of practical strategy implementation and quantitative investment development. This class focuses on advanced Pandas techniques for handling time series data, and how to implement signal-based strategies and static/dynamic asset allocation strategies that require adjusting asset weights at various intervals based on this. Furthermore, it goes beyond strategy implementation and learns about 'code framework' that directly verifies and backtests various investment strategies with minimal code modifications, how to extend this to improve it so that it can lead to actual investment, and what to watch out for in this process. In addition to the programming component, you can experience the best Python quant investment flow that you cannot find in investment books, blogs, YouTube, etc. by deeply covering theoretical contents such as the two types of return concepts (simple return, log return) and evaluation indicators related to backtesting.
[20% discount on all classes] Celebrating the 1st anniversary of the course launch
Hello. This is Deepingsauce, Infraon knowledge sharer.
It seemed like the hot summer would never end, but autumn is quickly approaching as the morning air becomes chilly.
I vaguely remember opening the first lecture (Python that anyone can learn, whether they are a liberal arts student or a non-major) last year around the time the weather was getting chilly, and when I checked the calendar, I saw that the first anniversary was really approaching^^ (October 15, 2020)
A month ago, I finished the main curriculum for 'Python Quant Investment' by finishing the part 2 class. In the short period after the release, many people showed interest, so I had the honor of being featured on the main banner of the Infraon homepage. Accordingly, the total number of cumulative students is now approaching 4,800.
To thank you for your support, we have prepared a 20% discount event for all lectures to celebrate the 1st anniversary of the opening of the first lecture (until 23:59 on Friday, October 15, 2021)
<Go to lecture>
1. Python that anyone can learn, whether they are a liberal arts student or a non-major!
2. Python Web Crawling & Automation to Replace My Work (feat. Stock, Real Estate Data / Instagram)
3. Data-based stock quant investment with Python Part 1
4. Data-based stock quant investment with Python Part 2
I hope that through this opportunity, we can further improve the quality of life of our students at a slightly lower price.
We will continue to strive to provide better content in the future.
thank you