4th SeoulAI Hackathon for Trading

James Park

15 December 2018

Overview

Seoul AI is hosting our 4th AI hackathon on Saturday, 15th of December. This hackathon is based on a new toolkit from SeoulAI for developing AI algorithms: Seoul AI Gym. This gym simulates various environments and enables the use of any teaching techniques on an agent. The goal of every hackathon participant is to develop an agent that can trade cryptocurrency. Each participant will train an agent to compete to become the most successful trader. Participants are free to choose any machine learning algorithm of their choice. SeoulAI will provide the real-time dataset.

Competition

All agents will receive virtual 100,000,000KRW at 10:00. The agent with the highest revenue by 18:50 will be the winner of the competition.

We encourage you to participate in the competition from the start of the competition, but you can join at any time on December 15th.

Prizes

The winner will receive Apple AirPods.

Registration

All participants must register their hackathon_id (agent_id) through this Form

If you have any questions, feel free to ask us at seoul.ai.global@gmail.com

Judging Criteria

Revenue = (portfolio value /100,000,000 KRW) * 100 (%) (Revenue will be calculated to the 4th decimal place.)
Portfolio value = cash + balance amount * current price (at 18:50)
Agents with a return lower than 0% will be disqualified.
If there is a tie, the agent with the higher transaction number wins.

Important information

The hackathon_id (agent_id) you enter on Form must be the same as your agent class.
Order quantity, cash and balance will be calculated to the 4th decimal place.
Buy order’ll be concluded at the first sell price and Sell order’ll be concluded at the first buy price. The probability of conclusion’ll be 100%.
The buy and sell commissions are 0.05%.
If you have less than 1,000 KRW in cash, your order will automatically be changed to hold order (Minimum order amount is 1,000 KRW)
If your balance is 0, and you place an order to sell, it will automatically be changed to hold order.
There are no restrictions on trading methods. Reinforcement learning, rule based methods, direct trading and other methods are all possible.