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econophysics

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An end-to-end Python implementation of Cao et al.'s (2025) HLPPL methodology for the identification of financial (asset price) bubbles. Implements 7-parameter Log-Periodic Power Law model fitting, confidence-weighted sentiment analysis, regime-dependent 'BubbleScore' fusion, and Transformer-based forecasting with a backtesting framework.

  • Updated Oct 16, 2025
  • Jupyter Notebook

Python implementation of advanced financial network analysis toolkit for creating multi-layered Digital Twins of market dynamics. Implements information-theoretic Transfer Entropy and stochastic Kramers-Moyal methods to map non-linear, directed relationships between assets during normal and crisis periods.

  • Updated Jul 16, 2025
  • Jupyter Notebook

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