ROFL of Wall Street

An attempt at a trading bot that takes advantages of the price differences between ETFs and company stocks to make capital gains. Only it doesn't.

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Inspiration

We were intrigued by the challenge of solving the mathematical problem behind the market liquidity problem that Optiver presented. The fact that both members of the team are familiar with Python and that Optiver provided a real-time interactive environment were we could see the performance of our trading attempts instantly was an incentive to pick this challenge.

What it does

Our bot constantly monitors ETF and stock selling and buying orders, and looks for discrepancies between individual stock prices and ETFs in search for trading opportunities that result in a net profit. Sadly, we did not find a way to integrate the information properly to make the bot consistently net a profit.

How we built it

We used the Cloud9 development environment that Optiver provided to build a series of Python classes and functions, that were combined in a script running a trading loop, that every given amount of milliseconds makes an assessment of the market, calculates the optimal (according to our faulty algorithm) trading operations to performs and sends the corresponding selling or buying orders to Optiver trading platform.

Challenges we ran into

Lack of trading knowledge was definitely an issue. We struggled to implement an efficient way to link transaction volume to potential profit, and also couldn't find an optimal way to stay close to a neutral position respect to the green energy ETF, to avoid exposure and have margin to exploit potential advantageous trades. Instead, our bot either maximized it's position respect to the ETF or didn't want to trade at all.

Accomplishments that we're proud of

At least we could implement a loop that goes through a seemingly sound but ultimately money-losing logic. We successfully interacted with the market, making use of Optiver libraries to retrieve market information and buy and sell stock.

What we learned

Also, together with the Optiver staff we learned a lot about day-trading and derivative markets, as well as trading concepts such as hedging, retreating, quoting, market-making, bid-ask spread, etc.

What's next for ROFL of Wall Street

Not much, since it was a self-contained challenge that depends on Optiver software support. However it sparked a curiosity for automatic trading that we may explore in the future.

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