 Sustainable Development Goals (SDGs) Research ImpactÂ
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Ali, S., Badshah, I., Demirer, R., Hegde, P., & Rognone, L. (2024). Climate risk, ESG ratings, and the flow-performance relationship in mutual funds. Global Finance Journal, 101041.
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
Dogah, K. E., Wu, Y., & Rognone, L. (2024) Commodity futures market conditions and Climate policy risk: Evidence from energy and metals markets. Journal of Futures Markets, 44: 1694-1709. [Open Access]
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
Bua, G., Kapp, D., Ramella, F., & Rognone, L. (2024). Transition versus physical climate risk pricing in European financial markets: a text-based approach. The European Journal of Finance, 1–35. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
Fava, S. del, Gupta, R., Pierdzioch, C., & Rognone, L. (2024). Forecasting international financial stress: The role of climate risks. Journal of International Financial Markets, Institutions and Money, 92, 101975. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action; 17 Partnership for the Goals
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action; 17 Partnership for the Goals
Zhou. Y., Wu, S., Liu. Z. & Rognone, L. (2023) The asymmetric effects of climate risk on higher-moment connectedness among carbon, energy and metals markets. Nature Communications, 4, 7157. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 8 Decent Work and Economic Growth; 11 Sustainable Cities and Communities; 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 8 Decent Work and Economic Growth; 11 Sustainable Cities and Communities; 13 Climate Action
Bouri, E., Dudda, T. L., Rognone, L., & Walther, T. (2023). Climate risk and the nexus of clean energy and technology stocks. Annals of Operations Research. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 7 Affordable and Clean Energy; 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 7 Affordable and Clean Energy; 13 Climate Action
Bouri, E., Rognone, L., Sokhanvar, A. & Wang, Z. (2023). From climate risk to the returns and volatility of energy assets and green bonds: A predictability analysis under various conditions. Technological Forecasting and Social Change. 194, p. 1-22 22 p., 122682. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 7 Affordable and Clean Energy; 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 7 Affordable and Clean Energy; 13 Climate Action
Karmakar, S., Gupta, R., Cepni, O., & Rognone, L. (2023). Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model. Resources Policy, 82, 103438.
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
Cepni, O., Demirer, R., Pham, L., & Rognone, L. (2023). Climate uncertainty and information transmissions across the conventional and ESG assets. Journal of International Financial Markets, Institutions & Money, 101730. [Open Access]
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
Cepni, O., Demirer, R., & Rognone, L. (2022). Hedging climate risks with green assets. Economics Letters, 212, 110312.
ABSTRACT
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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.
UN SDGsThis output contributes to the following UN Sustainable Development Goals (SDGs): 13 Climate Action
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