Due to the increasing severity of climate change, climate policy uncertainty has become an important factor in influencing the economic performance of various industries, particularly affecting weather-sensitive industries such as tourism (Scott et al., 2012; Rastegar and Becken, 2024; Becken and Scoot, 2024; Deku and Morris, 2025; Wang and Hu, 2025). Global warming, frequent extreme weather events, and other phenomena have become common challenges worldwide. Governments have implemented various policies to combat climate change. However, the frequent adjustments, varying intensity, and uncertainty in the timing of these policies have resulted in “climate policy uncertainty,” introducing new risks to business operations and investment decisions. In China, the importance of climate-related policies has increased, with their uncertainty having a considerable impact on market participants’ behavior.

The development of the tourism industry, which is vital for China’s economy, is constrained by weather conditions and related policies (Du et al., 2016; Song et al., 2018; Zhang et al., 2020; Wang et al., 2025). The fluctuations in weather policy uncertainty may substantially impact the stock prices of the listed tourism companies through various channels (Sofield and Li, 2013; Wong et al., 2013; Apergis et al., 2023; Hamida, 2024; Fan et al., 2025). On the one hand, the operation of the tourism industry is highly dependent on climate conditions. Environmental factors, such as temperature, precipitation, and air quality, directly affect the attractiveness and traffic of tourist destinations. On the other hand, climate change policies, such as carbon emission restrictions, environmental taxes, and energy structure adjustments, may elevate operating costs and alter profit models for tourism companies (Scott et al., 2016). Furthermore, natural disasters triggered by abnormal climate events and their response policies may disrupt or considerably alter tourism operations. Altogether, these factors form a complex mechanism by which climate policy uncertainty influences the stock market performance of the tourism industry (Zhang et al., 2024). Research specifically addressing the relationship between weather policy uncertainty and the stock market performance of the tourism industry is limited (Nguyen et al., 2020; Altaf, 2024), despite previous studies exploring the impact of policy uncertainty on the stock market.

The impact of climate change and related policies has received widespread academic attention (Abdesslem et al., 2025; Du et al., 2025; Fahmy, 2025; Yan, 2025; Yan et al., 2025). Baker et al. (2016) introduced the economic policy uncertainty index, which has since been widely used to study the impact of policy uncertainty on financial markets. Subsequently, scholars have developed more specialized policy uncertainty indicators, such as the climate policy risk index constructed by Engle et al. (2020) and the Chinese Climate Policy Uncertainty (CCPU) index proposed by Ma et al. (2023). These indices provide quantitative tools for studying the impact of climate policies on financial markets. Traditional correlation analysis, vector autoregression models, and other techniques struggle to capture complex relationships that evolve over time. Wavelet analysis, which can analyze signal characteristics in the time and frequency domains, has gained popularity in recent years for analyzing financial time series. In particular, Torrence and Compo (1998) and Grinsted et al. (2004) proposed the wavelet coherence analysis method, which has provided a powerful tool for studying the dynamic relationships between nonstationary time series.

Using time series data, the present study adopts wavelet coherence analysis to explore the dynamic relationship between the CCPU index and the stock market performance of the tourism industry wavelet coherence analysis, an advanced time–frequency analysis tool, effectively captures the correlations between nonlinear, nonstationary time series (Vacha and Barunik, 2012; Rhif et al., 2019; Singh et al., 2022; Szczygielski et al., 2024; Karatas et al., 2025), overcoming the limitations of traditional econometric methods in dealing with complex financial time series. The paper uses this method to reveal the time-varying characteristics of the weather policy uncertainty’s impact on the stock market performance of the tourism industry and its transmission mechanisms.

Theoretically, this study broadens the research on the relationship between policy uncertainty and stock market performance, specifically by incorporating the emerging issue of weather policy into the analytical framework. The practical relevance lies in providing a basis for investors to manage risks in tourism sector stocks and a reference for governments to consider the potential impacts of climate policies on the capital market while developing them. The findings may provide new insights into how policy uncertainty affects the capital market performance of specific industries within the Chinese market environment.