Inspiration
We were interested in how trading algorithms work and how markets can be analysed to optimise our profits.
What it does
We use multiple algorithms to make profits. Our program constantly checks for possible arbitrage trades by checking if the market values of the two instruments are inconsistent. In addition, we analyse market trends using methods such as the Relative Strength Index (RSI) and Bollinger Bands. We also implemented a market maker strategy which provides liquidity by continuously putting up a bid-ask spread which follows the last purchase price.
How we built it
Python (Cloud 9 IDE)
Challenges we ran into
The biggest challenge was handling situations where we attempted to make a trade which didn't go through. For example, if we attempted to buy from one market and sell to the other, but only one of those trades succeeded, we would now either be short (negative position) or long (positive position). We had to implement functions to deal with this problem and ensure that we quickly returned to zero position to avoid risking the market value changing too much.
Accomplishments that we're proud of
Working together and problem solving as a team! In the end we managed to create an algorithm that (while not perfect) manages to at least survive in the market, and often take advantage of market differences to make some money too.
What we learned
We researched several different algorithmic trading strategies and considerations, in order to decide what algorithms we should implement. We also learned about market making; why it is essential to make markets more liquid and how to make money by exploiting the illiquidity in one market while simultaneously minimising risk by hedging our trades in the more liquid market, through a first hand experience of trading. The nature of dual listings and hedging our trades took advantage of the market neutral trading to protect our profits against any large swings in the market and make money independent of the trend in the market.
Market making
These flow diagrams illustrate our strategy for market making. It has been optimised to make money regardless of the current trend in the market. This was necessary as we initially saw that if the market was in a clear trend our positions would be skewed as arbitrage algorithms would selectively either buy or sell.
Market Maker Strategy
What's next for us
Using these algorithms to become billionaires
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