Applying Artificial Intelligence to Trading

This post decomposes the broad problem of applying AI to trading into three distinct subproblems: Prediction, Optimization, and Execution. It analyzes the challenges of applying AI techniques from board games to trading, highlighting differences in zero-sum nature, rule knowledge, state observation, and data availability. For each subproblem, it outlines specific AI tasks and considerations relevant to financial markets, such as supervised learning for price prediction, financial mathematics for portfolio optimization, and reinforcement learning or other AI for trade execution.