Attempting to demystify the world of trading and the numerous strategies that can be used.

What it does

This app allows a prospective trader to quickly test out basic trading algorithms to understand how they would have performed using historical data. Results can be used within the app or sent to your phone via SMS.

How I built it

Using a combination of Python and Google Cloud Platform services, as well as access to a large-scale financial database via the DarwinEx FTP server. We use the streamlit framework to build a front-end that allows a user to input parameters, which are then simulated against historical data. The Twilio API allows a summary report to be sent to mobile phone.

Challenges I ran into

Being able to quickly aggregate years of financial data along with the financial indicators without the user waiting for too long. Ensuring the application is reactive without being prone to errors, as changing some parameters could result in unexpected results.

Accomplishments that I'm proud of

Deploying to Heroku, dynamically visualising trading strategies.

What I learned

How to deploy to Heroku, the hidden difficulties with easy-to-use frameworks.

What's next for

Adding more instruments and trading strategies. Enable the user to add and define more complex trading strategies and understand their success or failure in more depth.

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