Identification of Colombian coffee price dynamics.

Area of Science:

• Complex Systems
• Economic Modeling
• Chaos Theory

Background:

• Daily Colombian coffee prices exhibit chaotic behavior, indicative of a complex underlying economic system.
• Understanding and predicting these price fluctuations is crucial for stakeholders in the coffee industry.

Purpose of the Study:

• To model the dynamics of daily Colombian coffee prices.
• To explore the application of multiscroll Chua systems for price signal reconstruction and forecasting.

Main Methods:

• Utilized a single multiscroll Chua system and a coupled system of two Chua systems to model coffee price dynamics.
• Employed an artificial bee colony optimization algorithm for fine-tuning the model parameters.
• Evaluated model performance based on statistical reconstruction of the price signal.

Main Results:

• The proposed Chua system models effectively reconstructed the chaotic Colombian coffee price signal.
• The models demonstrated accuracy in capturing key statistical properties of the price data.
• The approach shows promise for enabling long-term forecasting of coffee prices.

Conclusions:

• Complex systems modeling, specifically using multiscroll Chua systems, provides a viable framework for analyzing chaotic economic signals like coffee prices.
• The optimized models offer a potential pathway for improving the predictability of coffee market fluctuations.