Michael Kearns: Algorithmic Trading and the Role of AI in Investment at Different Time Scales

Financial markets currently utilize algorithms for high-speed execution and statistical arbitrage, yet long-term investment strategies remain resistant to full automation due to the complex, human-centric nature of navigating geopolitical shifts and economic cycles. A workshop co-sponsored by the speaker and the Federal Reserve Bank of Philadelphia highlighted that machine learning is still in its early stages for macroeconomic prediction, failing to replicate the synthesis of diverse data over decades. Consequently, experts assert that roles demanding long-term risk appetite and nuanced political judgment are secure from imminent algorithmic displacement, with no "robo Warren Buffett" emerging in the near future.