EP19: Igor Halperin: On the application of reinforcement learning in Finance

This podcast episode explores the transition of physics experts to finance, shares insights on risk assessment and embraces uncertainty in financial systems, delves into concepts and applications of reinforcement learning in finance and trading, discusses the impact of machine learning in financial services and the implications of AI on financial professionals, and examines the potential implications of automation on the future of work and society. Takeaways • Transitions from academia to finance offer mathematical challenges and complexity. • Recognizing and embracing uncertainty is essential for financial forecasting. • Reinforcement learning models can help understand market dynamics and strategies. • Machine learning provides more insights into market dynamics but has limitations. • AI and automation bring risks and challenges to financial stability and employment. • Automation may lead to societal transformations, requiring social preparedness.