- pip install -r requirements.txt
- Prosperity 2 Wiki
For the algorithmic trading challenge, you will be writing and uploading a trading algorithm class in Python, which will then be set loose on the island exchange. On this exchange, the algorithm will trade against a number of bots, with the aim of earning as many SeaShells (the currency of the archipelago) as possible. The algorithmic trading challenge consists of several rounds, that take place on different days of the challenge. At the beginning of each round, it is disclosed which new products will be available for trading on that day. Sample data for these products is provided that players can use to get a better understanding of the price dynamics of these products, and consequently build a better algorithm for trading them. While most days will feature new products, the old products will also still be tradable in the rounds after which they are introduced. This means that based on the result of the previous rounds, players also have the opportunity to analyse and optimise their trading strategies for these “old” products.
The format for the trading algorithm will be a predefined Trader class, which has a single method called run which contains all the trading logic coded up by the trader. Once the algorithm is uploaded it will be run in the simulation environment. The simulation consists of a large number of iterations. During each iteration the run method will be called and provided with a TradingState object. This object contains an overview of all the trades that have happened since the last iteration, both the algorithms own trades as well as trades that happened between other market participants. Even more importantly, the TradingState will contain a per product overview of all the outstanding buy and sell orders (also called “quotes”) originating from the bots. Based on the logic in the run method the algorithm can then decide to either send orders that will fully or partially match with the existing orders, e.g. sending a buy (sell) order with a price equal to or higher (lower) than one of the outstanding bot quotes, which will result in a trade. If the algorithm sends a buy (sell) order with an associated quantity that is larger than the bot sell (buy) quote that it is matched to, the remaining quantity will be left as an outstanding buy (sell) quote with which the trading bots will then potentially trade. When the next iteration begins, the TradingState will then reveal whether any of the bots decided to “trade on” the player’s outstanding quote. If none of the bots trade on an outstanding player quote, the quote is automatically cancelled at the end of the iteration.
Every trade done by the algorithm in a certain product changes the “position” of the algorithm in that product. E.g. if the initial position in product X was 2 and the algorithm buys an additional quantity of 3, the position in product X is then 5. If the algorithm then subsequently sells a quantity of 7, the position in product X will be -2, called “short 2”. Like in the real world, the algorithms are restricted by per product position limits, which define the absolute position (long or short) that the algorithm is not allowed to exceed. If the aggregated quantity of all the buy (sell) orders an algorithm sends during a certain iteration would, if all fully matched, result in the algorithm obtaining a long (short) position exceeding the position limit, all the orders are cancelled by the exchange.