A system to create, test, optimize, and deploy algorithmic trading strategies
- Combine simple conditions to form compound conditions. Combine compound conditions and create trading strategies.
- For example:
- Condition A: QQQ stock is 1 SD below its 5-day mean price
- Condition B: Buying power is above $8,000.
- Condition C: Condition A and condition B
- Strategy: If condition C, buy $3000 of SPY
- For example:
- Create unlimited portfolios with different combinations of strategies
- Backtest those strategies using historical data.
- Only stocks are currently supported, but cryptocurrency and options support is baked into the architecture
- Optimize the strategy's parameters using a genetic algorithm
- Choose hyperparameters like mutation rate, training period, validation period, and population size
- Choose to optimize percent gain, sortino ratio, sharpe ratio, or max drawdown
- Deploy the strategies live and see how it performs in real-time
Some architectural artifacts can be found at this link: https://drive.google.com/drive/folders/1TgZNGPd7TBWi47dWh0TI2nZ_9WUhv_P_?usp=sharing
- Clone the repository.
- Download MongoDB community edition. Turn on MongoDB. It is recommended that you turn it on in the background so that you can close the tab.
- Open your IDE to the NextTrade folder. It is recommended to use VSCode, but you can use any IDE that you want. Open a terminal window within the IDE.
- Install the dependencies:
npm run install-all - Make sure all tests pass:
cd app; npm t - Add secrets to the env file (in app folder) and rename the file to .env
To turn on the client and server:
- Open two terminal windows.
- In one window, turn on the client:
cd client; npm start - In the other window, turn on the server:
cd app; npm start