QuantResearch

The repository includes notebooks on diverse topics like portfolio optimization, machine learning, and statistical models, as evidenced by the table listing over 20 implementations from ARIMA/GARCH to reinforcement learning.

Each notebook is paired with a blog post explaining concepts, making it practical for understanding through code, as seen in the linked blogs for entries like value-at-risk and cointegration pairs trading.

Provides scripts like hist_downloader.py for downloading historical market data at no cost, detailed in README entry 24 and accompanied by a Medium article on free data sources.

Implements advanced methods such as reinforcement learning for trading and option pricing, as shown in notebooks like reinforcement_pm.ipynb and american_option.ipynb with related blog posts.