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Didier Sornette is Emeritus Professor of Entrepreneurial Risks at ETH Zurich and Chair Professor and Dean of the Institute of Risk Analysis, Prediction, and Management (Risks-X) at the Southern University of Science and Technology (SUSTech) Shenzhen. Since 2022, Professor Sornette has also worked with the private sector in Medtech and dynamic financial risk management.

Expertise

Professor Sornette uses data-driven mathematical statistical analysis to study the predictability and control of crises and extreme events in complex systems. His key contributions include discovering the "dragon-king" concept for extreme events and developing the log-periodic power law singularity framework to predict failures and crises, with applications spanning all fields of natural hazards and social sciences. Applied to financial economics, his methods help us to better understand financial markets' overall stability and instabilities.

Expertise Fields

  • Financial Markets
    • Central Banks and Monetary Policy
    • Financial Crises
    • Financial Forecasting
    • Information and Market Efficiency
    • International Financial Markets and Emerging Markets
    • Systemic Risk and Regulation
  • Portfolio Management and Asset Classes
    • Asset Pricing
    • Behavioral Finance and Neurofinance
    • Commodities
    • Equities
    • Foreign Exchange
    • Options and Other Derivatives
    • Portfolio Management
    • Real Estate
  • Corporate Finance and Governance
    • Financial Risk and Risk Management
    • Financial Valuation
  • Frontier Topics
    • Big Data and Fintech
    • Operations Research and Decision Theory
    • Sustainable Finance

Current Publications:

N°24-51: Analysis of the Leading Bitcoin Forum with Large Language Models Highlights the Enduring and Substantial Carbon Footprint of Bitcoin

N°24-48: Multiple Outlier Detection in Samples with Exponential & Pareto Tails

N°24-33: Deep LPPLS: Forecasting of Temporal Critical Points in Natural, Engineering and Financial Systems

N°24-02: Scaling Laws And Statistical Properties of The Transaction Flows And Holding Times of Bitcoin

N°23-41: A Parsimonious Inverse Cox-Ingersoll-Ross Process for Financial Price Modeling

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