The Green Frequency: How Biodiversity Impacts High‐Tech Stocks Across Time Scales and Market Conditions

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ABSTRACT This paper uses wavelet coherence, wavelet quantile correlation (QC), wavelet local multiple correlation, and rolling window wavelet QC methodologies to examine the influence mechanisms of the US S&P 500 Biodiversity Index (SPBIO) on the stock prices of the US Magnificent 7 technology enterprises (AAPL, MSFT, GOOGL, AMZN, META, NVDA, and TSLA). The research reveals four key findings. First, SPBIO demonstrates significant forecasting capability for all technology stocks, with an information transmission cycle of approximately 6 days. Second, the association between biodiversity and technology stocks exhibits frequency stratification characteristics, displaying weak correlations in short‐term frequency domains (2–16 days) whilst demonstrating strong positive correlations in medium to long‐term frequency domains (64–256 days), with correlation coefficients exceeding 0.6. Third, correlations prove strongest under normal market conditions (0.5–0.7), whilst weakening during extreme market states. Fourth, the connections between technology stocks and SPBIO exhibit significant heterogeneity: Apple and Microsoft maintain stable positive correlations, NVIDIA experiences a sharp increase in correlation after 2023, and Tesla demonstrates the greatest frequency differential between short‐ and long‐term periods. This research provides important reference points for investors constructing ESG portfolios and for policymakers refining biodiversity information disclosure systems.

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