Financial series can show chaotic behavior due to interactions between different investors. The study used a model to demonstrate how changing investors' homogeneity can lead to chaotic price evolution. Tests were conducted on Paris Stock Exchange returns to identify underlying processes, including long-memory components and chaotic structures. Forecasting methods were also applied. The presence of chaotic structures in stock markets has implications for future research on relationships between ARCH and chaotic models.