https://github.com/austin-starks/NextTrade
I created a framework for creating automated trading strategies using a UI. Using this framework, users can create trading strategies, combine them to form complex strategies, and optimize them to find the best set of hyperparameters. This project is intended for people who want to create strategies using a UI, but don’t want to use an online service like Pluto. It provides a great baseline for a fully functional trading platform. Lastly, the system is extensible enough to create custom strategies by extending the AbstractCondition class.
Walkthrough Example
This example assumes you’ve read the README, cloned the repo, set the environment variables, and turned the system on. You will also need to get an API key from Tradier. Navigate to localhost:3000 and do the following to create a strategy
Register or login
You first need to create an account. An important thing to note is that all account information is saved locally. You can put the email as [email protected] and the password as 12345678. It doesn’t matter, as long as you create the account.
Register for an Account
Creating a simple buy-only strategy
Navigate to My First Portfolio, then click Edit Strategies
Home Page
Dashboard Page
Our strategy will spend 100% of our buying power on SPY when any of its buying conditions are met. This looks like the following picture:
Simple Strategy
Adding buying conditions
Our buying conditions in this example will be simple, but in real-life, can be extended to be a lot more complex. Our strategy will trigger if
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We have not bought a stock in 30 days
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SPY is 1 standard deviation below its 30 day average price
Click on 0 Buying Conditions -> New Compound Condition -> And Condition. Afterwards, add the two simple conditions like the following:
Adding Buying Conditions
Click create, then voila! Your first trading strategy was created.
Backtest your strategy
Click the backtest button, set a date range, and click Run
Backtest the strategy
Optimize your strategy using a Genetic Algorithm
Click the optimizer, choose the default settings, and click Submit
Optimization Page
Update the portfolio with an optimized portfolio
Expand an Optimization Vector that has the best evaluation metrics. Click on Buy Spy, then click Edit to update your portfolio’s hyperparameters
Deploy it for paper-trading
Once we found the best strategy possible, go back to the Portfolio Page, click Settings, click Active, then click Save. Now, your strategy is deployed for paper trading!
Deploy the Portfolio
So what did we just did?
Using this platform, we were able to create a simple trading strategy and optimize its hyperparameters. The optimizer does this by running hundreds of backtests in the backend, and continuously evolving the hyperparameters. We were then able to deploy the strategy for real-time paper trading.
Final thoughts
While this example was overtly simple, we are able to add conditions together, create complex strategies, and optimize all of them together.
This system is over 25,000 lines of open-source code and took me over 2 years to develop. It was developed primarily for myself, but I thought this system can provide some high quality content for this sub because there’s really nothing like it.
There you go! I hope you guys found this example useful. Thank you so much!
