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“Climatic, financial, and economic systemic risk in the Spanish stock market: An analysis based on artificial intelligence and complex networks”

Author

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  • Fernández Fernández, José Alejandro
  • Gómez, Guillermo López
  • Gómez, Sonia Quiroga

Abstract

This study proposes an innovative approach to measuring systemic risk in the Spanish stock market by constructing three sentiment indices (climatic, financial, and economic) using KeyBERT and text mining. These indices, derived from the analysis of over 150,000 news articles from major Spanish newspapers between 2019 and 2023, are examined using wavelet transforms to capture multiscale interactions and temporal influence shifts. Additionally, complex networks based on CoVaR allow for the assessment of risk propagation and interdependencies within IBEX 35.

Suggested Citation

  • Fernández Fernández, José Alejandro & Gómez, Guillermo López & Gómez, Sonia Quiroga, 2026. "“Climatic, financial, and economic systemic risk in the Spanish stock market: An analysis based on artificial intelligence and complex networks”," The North American Journal of Economics and Finance, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:ecofin:v:84:y:2026:i:c:s1062940826000446
    DOI: 10.1016/j.najef.2026.102622
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    Keywords

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    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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