We study how climate policy risk is priced across the maturity structure of equity cash flows. Using textual analysis of European news articles, we construct indices of transition and physical climate risk and, drawing on recent advances in measuring the temporal dimension of text, classify climate news by the horizon it references. We combine these indices with prices of dividend futures and dividend swaps, which allow us to decompose stock price reactions to climate news into short- and long-term cash-flow components. Heightened transition-risk news lowers stock prices, and the decline is concentrated in long-maturity dividend claims. The evidence suggests that investors expect most firms to defer adaptation, leaving near-term earnings and payouts largely unchanged while bearing greater long-run exposure. Finally, firm-level sensitivities identify which companies the market perceives as adapting early — accepting short-term losses to invest in the transition — versus those most exposed to stranded-asset risk.

We study how first-time green bond (GB) issuances impact the environmental and social performance (ESP) of issuers. If GB issuances signal the issuer's commitment to sustainable development, rating agencies should positively adjust ESG scores, assuming no opportunistic behavior or rating inefficiencies. Using a global GB issuance dataset, we employ a difference-in-differences approach to compare ESP scores of GB issuers (treatment group) with those of non-GB issuers (control group). Compared to non-GB issuers, GB issuers experience enhanced ESP after their first GB issuance, with stronger results for firms with lower ESG scores pre-issuance. Higher environmental performance is driven by reduced carbon emissions, while improved social performance is driven by better workforce, human rights, and community scores. GB issuances reduce firms' likelihood of ESG controversies. These findings contribute to our understanding of the factors driving the GB-ESG nexus and have implications for policymakers, investors, and issuers interested in integrating or promoting sustainability practices.

We extend the burgeoning literature on climate finance by examining the informational role of mutual fund sustainability ratings on the asset allocation decisions by investors when faced with climate risks. Utilizing data on a large sample of equity mutual funds in Australasia (Australia and New Zealand), we find that climate risk plays a significant role on the sensitivity of fund flows to past performance. We find that the sensitivity is stronger for mutual funds that enjoy high sustainability ratings, and we show that the informational value of past performance over subsequent fund flows becomes more important when investors face greater climate risks. We argue that sustainability ratings of managed funds not only complement performance but also help improve the efficiency of asset allocation decisions, more so during a heightened climate risk environment.

Under its climate regulation, the EU is expected to become the first continent with a net-zero emissions balance. We study the pricing of climate risks, physical and transition, within European markets. Using text-analysis, we construct two novel (daily) physical and transition risk indicators for the period 2005-2021 and two global climate risk vocabularies. Applying our climate risk indices to an asset pricing test framework, we document the emergence of economically significant transition and physical risk premia post-2015. From a firm-level analysis, using firms' GHG emissions, GHG emissions intensity, environmental, and ESG scores, we find that rises in transition (physical) risk are typically associated with an increase (decrease) in the return of green (brown) stocks. Firm-level information is used by investors to proxy firms' climate-risks exposure, especially for transition risk since 2015, whereas the sectoral classification appears to proxy firms' exposures to physical risk. From a country-level analysis emerges an intensified connection between European stock markets and climate risks post-2015, yet with some heterogeneity. Our results have important economic implications and show that investors demand compensation for their exposure to both climate risk types. Our novel climate risk vocabularies and indicators find several applications in identifying, measuring, and studying climate risks.

ABSTRACT In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

This study analyses the pricing of climate risk in equity markets. To this end, we first collect authoritative and scientific texts on the topic of physical and transition risk and build two novel vocabularies. Following, we apply the cosine-similarity approach suggested by Engle et al. 2020 to compare both vocabularies with a corpus of European daily news and construct two novel physical and transition climate risk indices covering the period 2005-2021. Finally, these time series are integrated into an asset pricing model to test the sensitivity of daily equity returns to climate shocks, controlling for several climate exposure metrics. Our results suggest that news on physical risk and transition risk carry relevant information which is reflected in asset prices. Firms with poor environmental and Environmental, Social, and Governance (ESG) performances, as well as firms with high Greenhouse Gas (GHG) emissions underperform when transition risk rises. Analogously, excess returns of firms with low environmental and ESG scores decline in the event of physical risk news. While investors appear to penalise high climate risk exposure, no evidence of outperformance of less exposed firms can be found, suggesting negative screening as a predominant investment strategy.

ABSTRACT This study investigates the impact of climate policy uncertainty (CPU) on energy and metal commodity futures markets by employing quantile regression, which accounts for various (bearish, normal, and bullish) markets. Our results reveal that the impact of CPU shocks is heterogeneous and market condition‐specific. Particularly, CPU exerts a significantly negative effect on all commodities, except natural gas, in a bearish market. Under a normal market, the impact of CPU on energy returns varies across commodities whereas for a bullish market, the CPU effect is mixed. The results also reveal natural gas to be a good hedge instrument for climate policy risk. We further conducted channel analysis using the theory of storage and hedging pressure hypothesis. The key finding reveals inventory level as the transmission channel of climate policy risk. Our findings have implications for the inventory management strategies of producers and suggest that regulators should consider market‐based policies in their decarbonization efforts.

We study the predictive value of climate risks for subsequent financial stress in a sample of daily data running from October 2006 to December 2022 of thirteen countries, which include China, ten European Union (EU) countries, the United Kingdom (UK), and the United States (US). The climate risk indicators are the result of a text-based approach which combines the term frequency-inverse document frequency and the cosine-similarity techniques. Given the persistence of financial stress as well as the importance of spillover effects of financial stress from other countries, we use random forests, a machine-learning technique tailored to handle many predictors, to estimate our forecasting models. Our findings show that climate risks tend to have a moderate impact, albeit in several cases statistically significant, on predictive accuracy, which tends to be stronger, in our cross-section of countries, on a daily than at a weekly or monthly forecast horizon of financial stress. Furthermore, the predictive value of climate risks for financial stress is heterogeneous across the countries in our sample, implying that a univariate forecasting model appears to be better suited than a corresponding multivariate one. Finally, the predictive value of climate risks for financial stress appears to be stronger in several countries at the lower conditional quantiles of financial stress.

Climate change affects price fluctuations in the carbon, energy and metals markets through physical and transition risks. Climate physical risk is mainly caused by extreme weather, natural disasters and other events caused by climate change, whereas climate transition risk mainly results from the gradual switchover to a low-carbon economy. Given that the connectedness between financial markets may be affected by various factors such as extreme events and economic transformation, understanding the different roles of climate physical risk and transition risk on the higher-moment connectedness across markets has important implications for investors to construct portfolios and regulators to establish regulation system. Here, using the GJRSK model, time-frequency connectedness framework and quantile-on-quantile method, we show asymmetric effects of climate risk on connectedness among carbon, energy and metals markets, with higher impacts of climate physical risk on upward risk spillovers, and greater effects of climate transition risk on the downside risk of kurtosis connectedness.

As global biodiversity declines, market participants are increasingly attentive to the financial implications of biodiversity risks. We study the effects of biodiversity risks on commodities futures returns using a novel biodiversity risk index over 2005-2022. Biodiversity risks can’t predict commodities returns, suggesting risk underestimation. Using dynamic conditional correlations (DCCs), we further show that precious metals offer diversification against biodiversity risks, while energy commodities can serve as a hedge or safe haven. However, agricultural commodities don’t provide protection against biodiversity risks, potentially increasing investors exposure to these risks. Our findings are significant for investors and regulators interested in addressing biodiversity risks.

This paper presents a novel take on the effect of uncertainty on investor learning about managerial skills by examining the fund flow-performance relationship in ESG rated funds in the context of climate uncertainty. Utilizing a large sample of mutual funds domiciled in Australia and New Zealand and recently developed transition and physical climate risk indexes for the Australia-Oceania region, we show that investor learning regarding manager skills is affected by not only the nature of climate uncertainty faced by decision makers, but also the sustainability ratings of the funds under consideration. While the response of fund flows to past performance is found to be stronger for funds with higher sustainability scores, we show that high climate risk dampens investors' ability to process information when it comes to funds with lower sustainability scores, thus hindering their ability to differentiate fund manager skill from luck. Our findings suggest that investor learning could be enhanced by the ESG performance of funds even under high uncertainty. We underscore the informational value captured by ESG ratings from a novel angle, particularly during periods of higher climate uncertainty. Our findings have implications for the managed fund industry and the information asymmetries that may arise between fund managers and investors.

We investigate whether text-based physical or transition climate risks forecast the daily volume of gold trade contracts. Given the count-valued nature of gold volume data, we employ a log-linear Poisson integer-valued generalized autoregressive conditional heteroskedasticity (IN-GARCH) model with a climate-related covariate. We detect that physical risks have a significant predictive power for gold volume at 5- and 22-day-ahead horizons. Additionally, from a full-sample analysis, it emerges that physical risks positively relate with gold volume. Combining these findings, we conclude that gold hedges physical risks at 1-week and 1-month horizons. Similar results hold for platinum and palladium, but not for silver.

We examine the impact of climate risks on the nexus of clean energy and technology stocks using a time-varying correlation model. We find that physical and transition climate risks are positively associated with the long-term correlation between clean energy and technology stock indices, whereas the effect of transition risk is more robust to different sample periods and alternative stock indices. On the contrary, the short-term correlation tends to decrease after shocks to physical risk, since clean energy stocks react more strongly to physical risk shocks than technology stocks.

This paper examines the effect of climate uncertainty on the spillover effects across the European conventional and environmental, social, and governance (ESG) financial markets via novel measures of physical and transitional climate risk proxies obtained from textual analysis. Analyzing daily data for stocks in the MSCI Europe ESG Leaders Index and various Euro based ESG bond indexes over the period January 3, 2014–September 30, 2021, we show that the shock transmissions between the conventional and ESG assets are significantly lower during periods of high climate uncertainty, suggesting that ESG investments can offer conventional investors diversification benefits against climate-driven shocks. Further comparing a forward-looking investment strategy conditional on the level of climate risk against the passive investment strategy, we show that investors who are worried about physical climate risks could utilize ESG equity sector portfolios as a diversification tool against physical climate uncertainty. In contrast, ESG bonds are found to be particularly useful in managing transition risk exposures that are associated with policy uncertainty and/or business transitions with respect to environmental policies. The findings have important implications regarding the role of climate uncertainty as a driver of informational spillovers across the conventional and ESG assets with important insights to manage climate risk exposures.

The importance of climate risk as a source of systemic risk for financial markets and the decisions of investors, portfolio managers, and regulators is growing. We examine the directional predictability from two climate risk measures, transition risk and physical risk, to the returns and volatility of European brown and green energy stocks, European carbon emission allowances, and global green bonds. Using daily data, we apply a cross-quantilogram approach in a time-varying setting to measure potential differences in the predictability across quantiles and over various crisis periods. The return predictability results are more pronounced for transition risk than physical risk, especially for brown energy stocks and carbon emission allowances, and they generally vary across periods and markets conditions. The predictability of volatility is also significant at specific time periods and volatility states, especially from transition risk, and the sign of the predictability is positive for brown energy and carbon emission allowances whereas it is negative for green bonds. We show that a lower-than-expected level of discussion about the transition process leads to a heightened volatility of brown energy markets. These findings have important implications regarding climate risks assessment on return and volatility predictability and climate risk and portfolio decarbonization under COP26.

Utilizing two novel measures of transition and physical climate risks obtained from textual analysis, we examine the hedging benefits of various green assets and popular precious metals against climate uncertainty. We find that green bonds stand out from the rest of the assets in our sample, including gold, exhibiting a consistent positive correlation with both types of climate risks. The findings suggest that green bonds can offer reliable safe haven benefits against climate uncertainty, providing new insight into the role of these assets not only as an investment that offers benefits associated with socially responsible investing, but also as a tool to manage climate risk exposures in investment portfolios.

We investigate the ability of textual analysis-based metrics of physical or transition risks associated with climate change in forecasting the daily volume of trade contracts of gold. Given the count-valued nature of gold volume data, our econometric framework is a log-linear Poisson integer-valued generalized autoregressive conditional heteroskedasticity (INGARCH) model with a particular climate change-related covariate. We detect forecastability of gold volume at 5- and 22-day-ahead horizons, and that too from physical risks. Given the underlying positively evolving impact of such risks on the trading volume of gold, as derived from a full-sample analysis using a time-varying INGARCH model, we can say that gold acts as a hedge against physical risks at medium- and long-horizons. Such a characteristic is also detected for platinum, and to a lesser extent for palladium, but not silver. Our results have important investment implications. JEL Classification: C22; C53; Q02; Q54.

This paper analyses the implications of climate change for the conduct of monetary policy in the euro area. It first investigates macroeconomic and financial risks stemming from climate change and from policies aimed at climate mitigation and adaptation, as well as the regulatory and fiscal effects of reducing carbon emissions. In this context, it assesses the need to adapt macroeconomic models and the Eurosystem/ECB staff economic projections underlying the monetary policy decisions. It further considers the implications of climate change for the conduct of monetary policy, in particular the implications for the transmission of monetary policy, the natural rate of interest and the correct identification of shocks. Model simulations using the ECB’s New Area-Wide Model (NAWM) illustrate how the interactions of climate change, financial and fiscal fragilities could significantly restrict the ability of monetary policy to respond to standard business cycle fluctuations. The paper concludes with an analysis of a set of potential monetary policy measures to address climate risks, insofar as they are in line with the ECB’s mandate. JEL Classification: E52, E58, Q54

We use high frequency intra-day data to investigate the influence of unscheduled currency and Bitcoin news on the returns, volume and volatility of the cryptocurrency Bitcoin and traditional currencies over the period from January 2012 to November 2018. Results show that Bitcoin behaves differently to traditional currencies. Traditional currencies typically experience a decrease in returns after negative news arrivals and an increase in returns following positive news whereas Bitcoin reacts positively to both positive and negative news. This suggests investor enthusiasm for Bitcoin irrespective of the sentiment of the news. This phenomenon is exacerbated during bubble periods. Conversely, cryptocurrency cyber-attack news and fraud news dampen this effect, decreasing Bitcoin returns and volatility. Our results contribute to the discussion on the nature of Bitcoin as a currency or an asset. They further inform practitioners about the characteristics of cryptocurrencies as a financial asset and inform regulators about the influence of news on Bitcoin volatility, particularly during bubble periods.