📖 For detailed documentation, please visit our Documentation Page 📖
To gain an advantage and competitive edge, strategies must consistently outperform quarterly benchmark returns. For instance, envision a momentum-centric approach applied to BTCUSDT. If trained on 2018-2019 data and tested on FY'2020_21_22_23 (16 quarters), it should surpass benchmark returns in at least 75% of quarters, equating to 12 out of 16 quarters.
You can send us the logs of any basic strategy to get a hold of how conversations go on here with respect to metrics and the suggestions that we send along for you to incorporate.
- Jupyter.untrade.io - It's our platform to develop, test, refine, and push code.
- GitHub - Quant Template README - This is the doc for assessing the functionality of Jupyter Hub.
- Telegram Community - Join us on Telegram
Within this Jupyter_untrade, you will find an SDK library which can be used for backtesting your strategy. Kindly shift your activity to this so that we are in sync with respect to cutting time and be on the same page during every aspect of backtest/front-run monitoring.
This project is an innovative platform where multiple teams collaborate and compete to develop the most profitable quantitative trading strategies. The essence of the project lies in its focus on creating algorithms capable of front-testing or front-running in trading scenarios to maximize returns.
This project is an innovative platform where multiple teams collaborate and compete to develop the most profitable quantitative trading strategies. The essence of the project lies in its focus on creating algorithms capable of front-testing or front-running in trading scenarios to maximize returns.
- Visit jupyter.untrade.io to create an account.
- Complete the signup form with your details.
- Once registered, you will receive a confirmation email. Follow the instructions to verify your account.
- Log in to your account on jupyter.untrade.io.
- Upon your first login, please wait for about a minute as the system prepares your workspace.
- After the setup is complete, navigate to the work folder in your dashboard. You will find a template main.py file and any necessary directory structure already created for you.