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COVID-19 Media Chatter and Macroeconomic Reflectors on Black Swan: A Spanish and Indian Stock Markets Comparison

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  • Indranil Ghosh

    (IT & Analytics Area, Institute of Management Technology Hyderabad, Shamshabad, Hyderabad 501218, Telangana, India)

  • Esteban Alfaro-Cortés

    (Quantitative Methods and Socio-Economic Development Group, Institute for Regional Development (IDR), University of Castilla-La Mancha (UCLM), 02071 Albacete, Spain)

  • Matías Gámez

    (Quantitative Methods and Socio-Economic Development Group, Institute for Regional Development (IDR), University of Castilla-La Mancha (UCLM), 02071 Albacete, Spain)

  • Noelia García-Rubio

    (Faculty of Economics and Business Administration, University of Castilla-La Mancha (UCLM), 02071 Albacete, Spain)

Abstract

Predictive analytics of financial markets in developed and emerging economies during the COVID-19 regime is undeniably challenging due to unavoidable uncertainty and the profound proliferation of negative news on different platforms. Tracking the media echo is crucial to explaining and anticipating the abrupt fluctuations in financial markets. The present research attempts to propound a robust framework capable of channeling macroeconomic reflectors and essential media chatter-linked variables to draw precise forecasts of future figures for Spanish and Indian stock markets. The predictive structure combines Isometric Mapping (ISOMAP), which is a non-linear feature transformation tool, and Gradient Boosting Regression (GBR), which is an ensemble machine learning technique to perform predictive modelling. The Explainable Artificial Intelligence (XAI) is used to interpret the black-box type predictive model to infer meaningful insights. The overall results duly justify the incorporation of local and global media chatter indices in explaining the dynamics of respective financial markets. The findings imply marginally better predictability of Indian stock markets than their Spanish counterparts. The current work strives to compare and contrast the reaction of developed and developing financial markets during the COVID-19 pandemic, which has been argued to share a close resemblance to the Black Swan event when applying a robust research framework. The insights linked to the dependence of stock markets on macroeconomic indicators can be leveraged for policy formulations for augmenting household finance.

Suggested Citation

  • Indranil Ghosh & Esteban Alfaro-Cortés & Matías Gámez & Noelia García-Rubio, 2023. "COVID-19 Media Chatter and Macroeconomic Reflectors on Black Swan: A Spanish and Indian Stock Markets Comparison," Risks, MDPI, vol. 11(5), pages 1-27, May.
    • Handle: RePEc:gam:jrisks:v:11:y:2023:i:5:p:94-:d:1148464
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    References listed on IDEAS

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    Cited by:

    1. Ghosh, Indranil & Jana, Rabin K., 2024. "Clean energy stock price forecasting and response to macroeconomic variables: A novel framework using Facebook's Prophet, NeuralProphet and explainable AI," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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