Inspiration
The inspiration came from the challenge Swissquote's challenge at the Hackathon. Some of us have previously traded crypto currencies, so the idea of creating a robot trading in such a volatile market was very intriguing.
What it does
Our algorithm bases itself on recent market data and observes its trends in order to predict any reocurring patterns in recent days of the market. The algorithm can be tweaked in order to optimize safety, risk, and accuracy.
How I built it
We decided to measure the average gradient resulting from similar gradients preceding it, in order to have an idea of how the market was going to react to any change in price.
Challenges I ran into
Being only in our first year of computer science, we had to learn certain concepts from scratch and tried to incorporate our theory without any complicated concepts such as machine learning.
Accomplishments that I'm proud of
Our algorithm performs with a great success rate and is consistently reliable.
What I learned
We learned how to use web API's, interact with web resources, and how to apply computer science to finance.
What's next for LauzHack2018
2019 :)
(We haven't uploaded any files below because we didn't work on our project on GitHub but our program did compete in the SwissQuote Bot race and was ranked fourth out of 9 competitors according to our calculations).
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