Is climate policy uncertainty positively or negatively priced in the stock market, and why?

The impacts of climate policy uncertainty on stock markets: Comparison between China and the US

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.

Does climate policy uncertainty shape the response of stock markets to oil price changes? Evidence from GCC stock markets.

Climate related risks are increasingly affecting financial markets, most importantly, policy risk regarding climate regulation. Not only do such risks impact market dynamics, but they can also have an impact on investor behaviour as cognitive and emotional reactions to risk. Understanding the interplay between climate policy and market volatility is essential for both economic forecasting and behavioural finance. This study aims to examine the dynamic relationship between climate policy uncertainty and the volatility of major stock market indices viz. Nifty 50 and Sensex in India, and Nasdaq and Dow Jones in the USA and exploring potential neurobehavioural responses of investors to such uncertainty. This research aims to determine the dynamic relationship between climate policy uncertainty, Indian benchmark indices Nifty 50 and Sensex, and USA stock market indices Nasdaq and Dow Jones for the monthly data from 1st April 2010 to 31st March 2024. The article has adopted Diebold and Yilmaz's connectedness framework and WC approach for data analysis. The analysis is interpreted through the lens of neuroeconomics, considering how climate policy uncertainty may influence cognitive risk processing in financial decision-making. Findings show that indices such as Sensex, Nasdaq and Dow Jones are more responsive to climate policy uncertainty compared with others. These trends suggest that the reactions of global investors are not only strategic but also subject to psychological tension and risk perception mechanisms. Uncertainty in climate policy exerts a notable influence on stock market volatility with far-reaching implications extending beyond the classical economic indicators to encompass investor cognition and neurobehavioural reactions. The outcome of the current research underscores incorporating neuroscience-informed methods into financial decision-making, providing significant feedback for investors and policymakers regarding risk management, portfolio maximisation and interpreting behavioural responses under environmental uncertainty.

This study aims to understand how climate policy uncertainty affects investor behavior and whether it moves with stock markets in advanced economies. Accordingly, we examine data for January 2000-2023 for the stock market indices of Sweden, the United Kingdom, Germany, Norway, the Netherlands, and Finland, which have a ‘good’ CCP rating according to the MSCI classification and the climate policy uncertainty index. Furthermore, we apply two main methodologies: Wavelet Coherence Analysis and the Breitung and Candelon Frequency Causality Test. WCA shows the time-based co-movements between CPU and stock market indices and their effects on each other. We also consider the causality test to examine causality at various frequencies. The WCA results reveal a relationship between the CPU index and all markets except the Norwegian market. As a result of the causality, we conclude that there is a strong causality between the CPU index and the Finnish and Swedish stock markets in the short run, a strong causality between the CPU index and the Dutch market in the long run, and a weak causality between the CPU index and the German stock market in the short, medium and long run. Investors can develop strategies to mitigate risks and hedge volatility by monitoring exogenous factors such as CPU. Strategies such as quick-action stop-loss orders are recommended, especially for short-term CPU-affected markets such as the Swedish and Finnish stock markets.

Purpose- It can be stated that global uncertainty indices, which were developed to measure the effects of global uncertainties on markets and the economy, may have the potential to affect risk perception and investment strategies in the markets. Determining the direction and intensity of the impact of uncertainty and risks on stock markets has become very important for stock market investors under these conditions. This paper aims to comparatively examine how the Climate Policy Uncertainty Index (CPUI) and Energy Uncertainty Index (EUI), which are relatively newer than global uncertainty indices and have been the subject of fewer studies, affect stock prices in Borsa Istanbul 100 (BIST100) and Standard&Poors 500 (S&P500) stock exchanges, in a developing and developed country stock exchange. Methodology- The short and long-term relationships between global uncertainty indices and stock prices were investigated using the ARDL (Distributed Autoregressive Lag) Bounds Test. ARDL is an approach that has several advantages over classical cointegration methods. Findings- It was determined that CPUI and EUI significantly affected the S&P500 index both in the short and long term, positively and negatively, respectively. For BIST100, this effect was negative but statistically insignificant for both indices in the long-term. Conclusion- This paper has highlighted the impact of climate policy and energy uncertainty indices on stock prices, especially in developed countries. In this context, the study emphasizes that investors and policymakers in these countries, especially those considering investing in developed countries, should consider these uncertainty indices and closely monitor them to reduce risks in their risk assessments and optimize their investment strategies. The paper contributes to the existing literature by improving the understanding of how climate policy uncertainty affects financial markets in developed and developing economies. The findings suggest that investors and policymakers should consider different effects when assessing the financial impacts of climate policy and energy uncertainty. Future research could investigate how firms respond to such uncertainties and the financial impacts of corporate strategies at the sectoral level. Keywords: Uncertainty, climate policy uncertainty, energy uncertainty, stock exchange JEL Codes: C32, G01,G11

Stock markets in the Middle East and North Africa face recurrent global shocks that can alter risk pricing and expected returns. This study assesses whether economic policy uncertainty, geopolitical risk, and climate policy uncertainty transmit to MENA equity returns. The objective is to estimate and compare the dynamic effects of global economic policy uncertainty (GEPU), geopolitical risk (GPR), and climate policy uncertainty (CPU) on stock market returns in the region and to identify the dominant uncertainty channel. Monthly data for ten MENA countries from January 2003 to August 2023 are analysed. Returns and uncertainty indices are expressed as log differences and checked for stationarity using ADF and PP tests. A structural vector autoregressive (SVAR) framework is estimated for each market, with lag length chosen by the Akaike criterion, and impulse responses and variance decompositions evaluate shock transmission. GEPU shocks exert statistically significant negative effects on returns for roughly four months in most markets, whereas Lebanon, Morocco, and Tunisia show weaker or insignificant responses. In contrast, GPR and CPU shocks do not produce statistically meaningful return effects. Variance decomposition indicates that GEPU contributes more to return variation than GPR or CPU, and its share generally increases with the forecast horizon, although own return shocks remain predominant. Findings support integrated risk monitoring for regulators and hedging strategies for investors. Future research should test nonlinear or regime switching dynamics, include volatility and capital flow channels, refine climate exposure measures, and assess transition period effects.

Purpose. The most recent conflicts have demonstrated that geopolitical risk has evolved into a significant issue that has an impact on the global food markets. Through the use of bi-wavelet coherence analysis, the study aimed to establish the ways in which geopolitical risk and climate policy uncertainties influences the food commodity market using Geopolitical Risk Index (GPR index), Climate Policy Uncertainty Index (CPU index) and the five components that make up the FAO Food Price Index (FPI). Methodology / approach. The study used monthly data spanning from January 1990 to March 2024. Geopolitical risk was measured using the GPR index developed through textual analysis of news articles. CPU index, developed using similar textual analysis, is used to represent the uncertainties related to climate change risk. The FAO’s FPI constituents were used to represent global food commodity market. The research applied advanced econometric methods including Johansen cointegration tests, Toda-Yamamoto causality analysis, Brock-Dechert-Scheinkman (BDS) nonlinearity tests, and bi-wavelet coherence analysis. Wavelet coherence analysis was particularly focused due to its capability to capture dynamic, time-frequency relationships among non-stationary data series. Results. The study found two significant long-run cointegrating relationships among GPR, CPU and FPI constituents. Causality tests indicated that geopolitical risk significantly influenced climate policy uncertainty but not vice versa. Wavelet analysis revealed that GPR and vegetable oil has more strong co-movement, and it is also the same in the case of CPU. CPU has a leading influence on GPR, which means that policy uncertainties lead to increased geopolitical tensions. Uncertainties in climate policies have an effect on food commodity market in the short run. Whereas, GPR affects cereals during geopolitical tension periods. In the case of dairy products, time varying co-movements in the short run could be witnessed whereas in the long run medium co-movement could be seen. Volatilities occur in the prices of vegetable oils during periods of crisis which can exacerbate prices of other food commodities, which can lead to food security issues. Originality / scientific novelty. The originality of the study lies in the fact that the main focus is on GPR, CPU and five constituents of FAO’s FPI. Moreover, the study uniquely incorporates CPU index as a proxy to climate change risk and its impact on food commodity market. Most of the studies focus on the spillover effect of geopolitical risk on different classes of asset. Significant number of literatures focus on the spillover effect on oil market, stock market and commodities market. However, there are only limited studies that focus on food commodity market. In addition, analysing these factors provides a deeper understanding of how they affect food security and market dynamics. This innovative approach offers valuable insights to policymakers, investors and stakeholders of food commodity market. Practical value / implications. Creating a more economically sustainable environment is the goal of every country, which requires joint efforts by various sectors of the financial market, government officials and economic regulators. These findings are of great importance to policymakers and stakeholders in global food systems, highlighting the need to create adapted policy frameworks, focus on the vulnerability of individual commodities, and carefully implement climate policies to mitigate potential negative impacts on food security.

Impact of policy uncertainty on stock market volatility in the China’s low-carbon economy

Does climate policy uncertainty affect Chinese stock market volatility?

This paper uses panel data from 30 Chinese provinces over the period 2003–2022 to construct a Panel Vector Autoregression (PVAR) model combined with System Generalized Method of Moments (GMM) estimation to investigate the dynamic interactions among changes in climate physical risks, adjustments in climate policy uncertainty, and the development of the low-carbon energy transition. Through Granger causality tests, impulse response analysis, and variance decomposition, the study reveals the causal relationships and shock transmission mechanisms among these variables. The results show that at the national level, there are bidirectional Granger causal relationships among exist among changes in climate physical risks, adjustments in policy uncertainty, and the development of the low-carbon energy transition. The low-carbon transition of energy structures significantly mitigates climate physical risks but increases climate policy uncertainty in the short term. An increase in climate policy uncertainty exacerbates physical risks in the short term but helps to digest risks in the long term. The response of energy transition to climate physical risks and policy uncertainty exhibits alternating positive and negative dynamic feedback. Regional analysis indicates that the interactions are strongest in the central region, while the eastern and western regions are more sensitive to policy fluctuations, and the northeastern region shows the weakest interactive effects. Based on these findings, the study recommends establishing a stable and predictable climate policy framework, enhancing investments in clean energy infrastructure, and improving climate risk early warning systems to synergistically promote China’s energy transition and climate risk governance.

Quantile connectedness between the climate policy and economic uncertainty: Evidence from the G7 countries

Building resilient clean energy transitions: Does economic, fiscal, and climate policy uncertainties contribute to renewable energy consumption in United States.

This study investigates how economic policy uncertainty affects stock market volatility in developing countries. Using monthly data on the Vietnamese stock market from March 2011 to December 2024 and employing the Vector Autoregression (VAR) model, the author identified significant connections between economic policy uncertainty and other macroeconomic factors and stock market fluctuations. The findings indicate that economic policy uncertainty in Vietnam significantly and positively influences market volatility, implying that a higher level of policy uncertainty leads to higher market fluctuations. Moreover, past market changes, inflation, and the COVID-19 pandemic have also played significant roles in affecting stock market changes in Vietnam. The results underscore the importance of eocnomic policy uncertainty in shaping the dynamics of the Vietnamese stock market, and stress the necessity for transparent and stable policy frameworks to ensure stable market operations. Based on these results, the authors suggest relevant recommendations for policymakers and investors to reduce the unfavorable impact of policy uncertainty on stock market operations and portfolio investments.

This study seeks to investigate the spillover effects between uncertainty indexes and returns on African stock markets; explore the time-varying nature of these interactions using TVP-VAR and QVAR techniques; and assess the resilience of individual stock markets to shocks, with particular attention to Energy Policy Uncertainty (EPU), Climate Policy Uncertainty (CPU), and Geopolitical Risks (GPRs) indexes. Accordingly, we employed two novel techniques, namely QVAR and TVP-VAR connectedness approaches to ascertain interdependencies under the bearish, bullish, and normal market regimes. The results for the QVAR approach revealed a total connectedness index (TCI) of 89.5%, suggesting substantial co-movement across markets during bearish market regime. Total connectedness index increased marginally to 89.7% under the bullish regime, reflecting an adaptive shift in shock propagation. Results from the TVP-VAR technique show a TCI of 71.97%, an indication of a reduced market interconnectedness amidst normal market regimes. We observe that CPU, EPU, and GPRs displayed heterogeneous spillover effects, with EPU and GPRs presenting pressing risks for majority of the markets. Additionally, the markets exhibited varying degrees of resilience under the various regimes, providing valuable insights for investors and policymakers on the nuances of the African stock market and shocks across various market regimes.