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Entropy and Chaos-Based Modeling of Nonlinear Dependencies in Commodity Markets
Irina Georgescu1, Jani Kinnunen2
1Department of Economic Informatics and Cybernetics, Bucharest University of Economics, Calea Dorobanți, 010552 Bucharest, Romania.
Entropy (Basel, Switzerland)
|September 27, 2025
Summary
This study reveals complex, nonlinear dynamics in Gold, Oil, Natural Gas, and Silver markets using chaos theory. Findings show time-varying relationships crucial for portfolio diversification and risk assessment.
Area of Science:
- * Financial econometrics and complex systems analysis.
- * Application of chaos theory and information theory to market dynamics.
Background:
- * Major commodity markets (Gold, Oil, Natural Gas, Silver) exhibit intricate interdependencies.
- * Traditional linear models may fail to capture the complex, nonlinear relationships within these markets.
Purpose of the Study:
- * To investigate the nonlinear dynamics and interdependencies among Gold, Oil, Natural Gas, and Silver markets.
- * To apply advanced chaos theory and information-theoretic tools for a deeper understanding of market behavior.
- * To assess the implications for portfolio diversification and systemic risk management.
Main Methods:
- * Utilized daily data from 2020-2024.
- * Employed chaos theory measures: Lyapunov exponents, correlation dimension, Shannon entropy, Rényi entropy, and mutual information.
- * Applied stochastic SO(2) Lie group method for dynamic correlation modeling and wavelet coherence for time-frequency analysis.
Main Results:
- * Evidence of low-dimensional deterministic chaos identified in commodity market dynamics.
- * Significant time-varying nonlinear relationships detected, particularly between Gold-Silver and Oil-Gas pairs.
- * Non-traditional methods successfully uncovered hidden market structures and co-movement dynamics.
Conclusions:
- * Nontraditional analytical approaches are essential for understanding complex commodity market behavior.
- * Identified nonlinear dynamics and interdependencies offer valuable insights for financial strategies.
- * Findings support improved portfolio diversification and systemic risk assessment in commodity markets.
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