Optiver Basket Trading Challenge

Strategy

Our strategy is to introduce liquidity into the market was simply to place an ask order slightly above the mid market value for the TECH_BASKET and then a bid order slightly below the mid market value for the TECH_BASKET

How we built it

We were given credentials for cloud9 server and our team (team-09) coded the strategy using phython3. First the the algorithm was validated by calculating the number of open orders for each instruments. It wouldn't allow it to exceed the maximum allowed limit. Also it would check if the open positions were exceeded the maximum allowed limit. Now we get the price for each of the instruments and arrays of asks and bids of every instrument. It is also made sure that there are asks and bids for each instrument which can be executed without violating the first set of validation defined earlier. Then the Volume Weighted Average Price for the basket is calculated and liquidity is created in the basket instrument. We calculated the best ask and bid for the basket instrument and similarly fetched the best ask and bid of Google and Amazon instruments. Using this we calculated the inconsistencies between the basket price and combined price of individual components. This in turn resulted in two chances for making profit, i.e, If the basket price is more than the combined price of the other instruments, and if the basket price is less than the combined price of the other instruments.

Accomplishments that we're proud of

At first we had a lot of errors that didn't allow us to even run our code. Now, having a good strategy and our code up and running is a great achievement for us.

What we learned

Most of our team being hackathon newbies. It was an exhilarating experience. Taking up a challenge that required us to understand how the market works and how strategies can be implemented. to make maximum profit. It was also a new for some of us to code in python3.