Dynamic risk resonance between crude oil and stock market by econophysics and machine learning

DOI10.1016/J.PHYSA.2022.128212OpenAlexW4296905779MaRDI QIDQ2096786

Chen Tao, Ming-Zhe Xu, Jiang-Cheng Li, X. Han

Publication date: 11 November 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2022.128212

zbMATH Keywords

stochastic resonancemachine learningeconophysicsdynamic predictionsignal power amplification

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Uses Software

• GenSA

Cites Work

• Role of noise in a market model with stochastic volatility
• Estimating the dimension of a model
• Stochastic resonance in an interacting-agent model of stock market.
• Geometry of quantum phase transitions
• Linking agent-based models and stochastic models of financial markets
• Simple and Globally Convergent Methods for Accelerating the Convergence of Any EM Algorithm
• VOLATILITY EFFECTS ON THE ESCAPE TIME IN FINANCIAL MARKET MODELS
• On quantumness in multi-parameter quantum estimation
• Introduction to Econophysics

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