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ForecastingForecasting
  • Article
  • Open Access

16 August 2026

56 Pages

Regime-Dependent Sectoral Information Transmission in S&P 500 Forecasting

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and
1
Department of Marketing and Supply Chain Analysis, Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, 7400 Kaposvár, Hungary
2
Department of Statistics, Finances and Controlling, Széchenyi István University, 9026 Győr, Hungary
3
Doctoral School of Management and Business Administration, John von Neumann University, 1117 Budapest, Hungary
*
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Abstract

Understanding which segments of the economy drive aggregate stock market movements is central to risk management. This study traces how the economic drivers of the Standard & Poor’s 500 Index (S&P 500) changed across two episodes: the 2020 COVID-19 shock and the 2025 technology-led period, using eleven sector indices and nine deep learning architectures. During COVID-19, forecasting power concentrated in Consumer Discretionary, Health Care, and Industrials before reorganizing sharply around Information Technology, consistent with a disruptive break. In 2025, Information Technology and market momentum dominated throughout, with no comparable reorganization, consistent with a gradual adjustment rather than a disruptive shift. This distinction, invisible from accuracy metrics alone (Gated Recurrent Unit: Mean Absolute Percentage Error = 3.41% and 2.16%), shows that information-concentration diagnostics can complement forecast-accuracy and risk-monitoring frameworks.

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