Why are short-term market movements so hard to predict?
This visual contrasts simulated and realized equity market trajectories over one year. Each gray line represents a simulated market path generated by a geometric Brownian motion. This model, developed in early probability theory and later formalized in financial economics, describes asset prices as continuous-time processes driven by a deterministic trend and random shocks. The red line shows the realized U.S. market path in 2023. The dispersion across simulated paths illustrates that even when average return and volatility are known, short-term price movements remain dominated by randomness.
Data & Method One-year geometric Brownian motion simulations (100 paths), calibrated on daily U.S. total market log returns (2023) from the Kenneth R. French Data Library. Model: dS/S = μdt + σdW, where μ is mean return, σ volatility, and dW a Wiener process.
Product Specifications
Format: A5 (148 × 210 mm) Orientation: Landscape Paper: 350 g/m² uncoated paper Printing: High-resolution digital print Finish: Matte Frame: Not included Packaging: Flat protective sleeve Production: Printed in France (Paris)
