Build. Deploy. Trade. Compete.
Design and deploy AI-driven trading strategies in a fair, standardized global simulation. Compete worldwide. Present in Singapore.
About the Competition
The SoAI 2026 AI Algorithmic Trading Competition invites participants worldwide to design and deploy AI-driven trading strategies. Open to all backgrounds — AI, finance, computer science, mathematics, and beyond.
All strategies compete in a fair, standardized simulation environment: centralized execution, identical data feeds, zero hardware bias.
Key Dates
Process
lumibot.strategies.Strategyrequirements.txtMarkets
Trade across two major asset classes with unrestricted access.
Developer Guide
Strategy class must inherit from lumibot.strategies.Strategy. The template provides the base scaffold.initialize() for one-time setup and on_trading_iteration() for each trading cycle — fetch data, compute signals, submit orders.from lumibot.strategies import Strategy class Strategy(Strategy): def initialize(self): # One-time setup self.sleeptime = "1D" # "1M" | "1H" | "1D" def on_trading_iteration(self): # Runs every sleeptime cycle bars = self.get_historical_prices( "BTC/USDT", 30, "day" ) # Compute signal... order = self.create_order( "BTC/USDT", quantity=0.01, side="buy" ) self.submit_order(order)
Judging Criteria
Prize Pool
Reasons to Compete
Registration