Does climate policy uncertainty affect Asian financial markets? Evidence from a wavelet-quantile-based approach

Purpose The varying impacts of climate policy uncertainty on stock market performance have emerged as a critical research area, driven by the challenges that climate change poses to financial markets. This study seeks to emphasize the crucial role of climate policy uncertainty (CPU) in predicting financial market fluctuation [Dow Jones Asia (ASIA), Dow Jones Islamic (ISLAMIC) and NASDAQ OMX Clean Energy Asia (CLEAN)] for the period from 2018 to 2024. Design/methodology/approach This paper uses three innovative techniques, including wavelet quantile regression, wavelet nonparametric causality and quantile on quantile regression. Findings The results reveal that climate policy uncertainty exerts a positive influence on the selected stock markets across various quantiles and time scales. However, the relationship between CPU and ISLAMIC stock returns shows both negative and positive associations. More importantly, CPU exhibits predictive power over stock markets, indicating causality across all quantiles and frequencies. Practical implications These findings highlight the importance for investors to pay more attention to climate policies during the current climate crisis. Originality/value To the best of the authors’ knowledge, this study is among the first to investigate the time-frequency nexus and predictability between CPU and stock markets in the Asia region. Specifically, the authors use an innovative three-stage methodology to analyze the influence of CPU on Asian stock markets. These methods include wavelet-based quantile regression, wavelet-based nonparametric quantile causality and quantile-on-quantile regression (QQR). The nonparametric quantile causality technique identifies causal relationships and their respective timeframes, while the wavelet-based quantile regression evaluates the strength and direction of these interactions. Additionally, they explore how CPU impacts various quantiles across different distributions of Asian stock market returns and visualize these effects using QQR 2D-plane graphics. This robust methodology provides valuable insights, making this research particularly relevant for academic scholars, market regulators, investors and policymakers.