Python Quantitative Finance Practice by Wall Street Masters

Introduction to Wall Street Master-level Python Quantitative Finance Practical Resources:

Intraday high-frequency trading is an extremely challenging trading method, and if we want to master it through scientific and quantitative methods, we must have powerful tools. The course teaches students to use two development languages, Python and C++. The instructor teaches students to use Python for data analysis and sampling, which can help us conduct data research and strategy testing for mean regression. Using C++ to improve our trading strategies and verifying them through mature models, high-frequency C++ real-time strategy writing can make it easier for us to understand and master the essence of the strategy.

Course Catalog

Part I

1. Course preparation and data sources.mp4

2. Introduction to the concept of mean reversion.mp4

3. Data Research on Mean Reversion-Part 1.mp4

4. Data Research on Mean Reversion-Part 2.mp4

5. Historical data statistics program for mean reversion.mp4

6. Analysis of historical data statistical results of mean reversion.mp4

7. Write a simple strategy for testing.mp4

Part 2

8. Order imbalance and average transaction price mean reversion-Part 1.mp4

9. Order imbalance and average transaction price mean reversion-medium.mp4

10. Order imbalance and average transaction price mean reversion - next screenshot video.mp4

11. Model 1: Simple linear model y=wx+b Video capture.mp4

12. Model 2: Naive Bayes.mp4

13. Model 3 - Support Vector Machine SVM, Random Forest RF.mp4

14. Model 5: Hidden Markov Model (Model 4 is not available on the official website) Video capture.mp4

15. Write a simple strategy for testing.mp4

Part 3

16. High-frequency C++ real-time strategy writing: mean reversion interception video.mp4

17. High-frequency C++ real-time strategy writing: mean reversion - Part 2 (1) Intercepted video.mp4

18. High-frequency C++ real-time strategy writing: prediction strategy.mp4

19. High-frequency C++ real-time strategy writing: prediction.mp4

20. Conclusion.mp4

Courseware.zip