Carbon Price Uncertainty and Stock Market Volatility Transmission: A GJR-GARCH-X and DCC Approach with Evidence from China's ETS

Abstract

This paper examines whether carbon price uncertainty transmits to stock market volatility in China's high-emission sectors following the launch of the national Emissions Trading Scheme (ETS) in July 2021. Using 1,072 daily observations on China Carbon Allowance (CEA) prices and Shenwan sector indices for electricity, steel, and cement over the period July 2021–December 2025, we document three findings. First, full-sample GJR-GARCH-X estimates yield statistically insignificant delta coefficients across all three sectors (|delta| ≤ 0.0085, p > 0.30), an informative null consistent with thin ETS trading and Phase 1 restriction to the power sector only. Second, event-window analysis around annual compliance deadlines reveals time-varying transmission: carbon uncertainty significantly amplifies electricity volatility in the 60-day window preceding the 2023 deadline (delta = 0.0448, p = 0.033) and the 60-day window following the 2024 deadline (delta = 0.0981, p = 0.008). Third, Asymmetric Slope CAViaR-X models demonstrate that carbon price uncertainty significantly shifts the extreme left tail of electricity returns (delta = 0.0473, p < 0.001 at the 1% quantile) even in the full sample where conditional mean-variance effects are absent. Our results distinguish between a dormant average variance channel and an active tail-risk channel, with implications for climate stress testing and carbon-aware portfolio risk management. —1—

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