In college, a friend and I explored whether a physics model—the Duffing Oscillator—could explain fluctuations in global wheat inventories from 1974 to 2012. Markets often seem chaotic, but we found that changes in inventory followed a predictable, nonlinear pattern. We started with basic oscillator models and built up to the Duffing oscillator, which captures complex but stable dynamics.

Our key finding: price changes respond cubically to inventory levels, and the system isn’t chaotic—it self-corrects over time. While our approach had limits, it showed how ideas from physics can help make sense of real-world economic behavior.