Navigating the Commodities Landscape

This chapter explores the speaker's transition from academia into the commodities sector, detailing their work at Goldman Sachs and the significance of client interactions. It emphasizes the evolution of commodities research methodologies, incorporating both qualitative and quantitative data while highlighting the growing importance of Python alongside traditional tools like Excel. The discussion also addresses the implications of AI on market dynamics, forecasting, and the essential balance between technology and human insight in commodities trading.