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Crossover from antipersistent to persistent behavior in time series possessing the generalyzed dynamic scaling law
Alexander S Balankin1, Oswaldo Morales Matamoros, Ernesto Gálvez
1Sección de Posgrado e Investigación, ESIME, Instituto Politécnico Nacional, México D.F. 07738, Mexico and Instituto Mexicano de Petróleo, México D.F. 07730, Mexico.
Summary
Crude oil price volatility exhibits persistent long-horizon behavior and mean-reverting short-horizon behavior, driven by complex market dynamics. This study reveals insights into financial markets and physical systems governed by avalanche dynamics.
Area of Science:
- * Physics
- * Financial Markets
- * Complex Systems
Background:
- * Crude oil price volatility analysis is crucial for economic stability.
- * Existing models may not fully capture the complex dynamics of market behavior.
- * Understanding scaling laws in financial data is an active research area.
Purpose of the Study:
- * To analyze crude oil price volatility using kinetic roughening principles.
- * To identify and characterize scaling laws governing short- and long-horizon volatilities.
- * To explore the relationship between market dynamics and volatility distributions.
Main Methods:
- * Application of kinetic roughening framework to crude oil price data.
- * Analysis of persistent and mean-reverting volatility behaviors.
- * Investigation of dynamic scaling laws and volatility distributions.
Main Results:
- * Long-horizon volatilities follow the Family-Viscek dynamic scaling ansatz.
- * Short-horizon volatilities obey a generalized scaling law with varying exponents.
- * A shift in volatility distribution accompanies the crossover from antipersistent to persistent behavior.
Conclusions:
- * Crude oil markets exhibit complex avalanche dynamics influencing price volatility.
- * The observed phenomena align with principles of kinetic roughening and scaling laws.
- * Similar behaviors may be present in other physical systems driven by avalanche dynamics.