Bitcoin Orderbook Collection and Implemention of Lasso Regression on Feature Data

Notice

This repo was created as a student project for the "AI와 암호화폐이야기" lecture in HYU.

💬 Description

This directory does the following things:

1. Gather & organize the orderbook from the bithumb exchange.
2. calculate essential & meaningful feature data for them, such as
   • mid price, market mid price, weighted mid price
   • book imbalance
3. Implement Lasso regression model on these data and calculate PnL

⚙️ Modules/Packages Used

• pandas: python module for data manipulation
• stringr: string operations in R
• glmnet: for fitting regularized regression models, such as lasso and elastic net, across a wide range of model types, including linear, logistic, Poisson, and Cox regression

These are listed in requirements.txt in the Docs folder. Use the below command to install these dependencies.

• pip install -r requirements.txt

🛐 How to run

• pip install -r requirements.txt
• python combine_book.py
• Then, just run the files you want to try out.

🤖 Contributors

• 김민승 <Github>
• 장선우 <Github>