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Investigates the impact of solar activity on economic indices, suggesting complex interactions.
Forecasts of economic indices are important for mitigating the risks of unexpected stresses in the global or local economy. However, the numerous factors that influence the resulting economic index create a complex picture that complicates determining a cyclical pattern. We studied the relationship between solar activity and the Dow Jones Industrial Average from 1896 to 2021. We used correlation and cross-correlation methods with a sliding time window and a wavelet coherency approach to analyze the data. The study revealed that the relationship between the events is not simple and evolves over time. Various synchronization periods, as well as variation in the coherence of these synchronizations over time, were identified. We discovered that the correlation with the 11-year periodicity is greater than 0.5 during the 1906–1936 and 1964–2000 time periods and is visible with a 95 $$%$$ confidence level during the 1910–1930 and 1990–1994 time periods. This correlation is supported by the found 95 $$%$$ confidence in the coherence between the cosmic ray data and the Dow Jones index during the same time periods (1964–2000), when the correlation between the sunspot number and this index is high, albeit with other phase differences. Furthermore, the correlation between the cosmic ray data and the Dow Jones is stronger. This could imply that the influence of solar activity on global economy fluctuations is mediated by the Sun’s modulation of cosmic rays.
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Japaridze et al. (2026) studied this question.
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