International political uncertainty and climate risk in the stock market

Gong, Xu; Fu, Chengbo; Huang, Qiping; Lin, Meimei

doi:10.1016/j.intfin.2022.101683

Cited by 54 publications

(10 citation statements)

References 61 publications

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“…RFE is a feature selection algorithm based on a base predictive model (e.g., random forest) to sort the input data according to relevance order, during which less significant features would be discarded. It can identify the optimal combination of components to produce superb performance (Genuer et al, 2010). Given its superiority, we employ it to carry out feature selection on all elements, including the lag features.…”

Section: Forecasting Methodsmentioning

confidence: 99%

“…With the increase in natural disasters caused by climate change and attention to climate issues, more and more studies are investigating the impact of climate risk on financial markets. Several studies have shown that climate change has significant implications for economic activity, energy markets, and financial markets, such as (Gong, Fu, et al, 2022; Moore & Diaz, 2015; Rubtsov et al, 2021; Yalew et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The Kullback-Leibler (KL) divergence approach was used to determine the topic number T. For further details, see Lin et al (2010). Therefore, this study selects the number of topics based on KL divergence to achieve topic variance and manual adjustment.…”

Section: Media Climate Attention Indexmentioning

confidence: 99%

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Climate change attention and carbon futures return prediction

Gong

Guan

et al. 2023

Journal of Futures Markets

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This study explores the predictive effect of climate change attention on carbon futures returns. Using climate‐related Google Trends and news, we construct five dimensions of the public climate attention index and media climate attention index. After feature selection, we incorporate the optimized combination with lagged order into the machine learning model to predict EU Emission Allowance futures returns. Our empirical results show that the forecasting models with climate attention outperform the corresponding benchmark models, indicating that climate attention does provide predictive information for carbon futures returns. In addition, we carry out trading simulations to investigate the economic performance of the forecast results. It turns out that the market strategies based on the prediction models with climate attention can deliver more benefits than the counterpart market strategies. More specifically, the cumulative returns reach 140% during the out‐of‐sample period, much higher than 79% of the cumulative returns of the buy‐and‐hold strategy.

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Section: Forecasting Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Climate change attention and carbon futures return prediction

Gong

Guan

et al. 2023

Journal of Futures Markets

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“…Another literature has emerged on the question of investors' "climate sentiments," showing strong correlations between surges in investor awareness and market volatility (Tran, 2021;Gong et al, 2022), and between climate sentiments and overvaluations of low-carbon assets (Santi, 2020). Anginer et al (2021) show that banks toughen their lending terms to firms involved in negative climate news and attribute it to reputational risk management.…”

Section: Time-heterogeneity and Investors' Climate Sentiments In The ...mentioning

confidence: 99%

“…Another literature has emerged on the question of investors’ “climate sentiments,” showing strong correlations between surges in investor awareness and market volatility (Tran, 2021; Gong et al., 2022), and between climate sentiments and overvaluations of low‐carbon assets (Santi, 2020). Anginer et al.…”

Section: Financiers and Transition Risksmentioning

confidence: 99%

Financial stability, stranded assets and the low‐carbon transition – A critical review of the theoretical and applied literatures

Daumas

2023

Journal of Economic Surveys

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Transitioning to a low‐carbon economy will entail sweeping transformations of energy and economic systems. A growing research body has raised concerns about the effect of such strain on financial stability. This literature on “financial transition risk” has highlighted that the conjunction of climate policy, technological change and shifts in consumption patterns may propagate to financial markets. In extreme cases, these dynamics may result in a “Climate‐Minsky” moment with systemic implications. The field has developed quickly, covering many methods and research questions. While this expansion in literature is advantageous when studying a complex issue like the low‐carbon transition, it also comes with downsides. The large number of methods hampers result comparison, and the integration of research designs. It also makes it difficult to provide a synthetic view of results in the literature as well as identify remaining uncertainties. To bridge these gaps, I propose a critical review of the literature. I examine three sub‐fields: the asset stranding literature, the direct assessment of transition risks through prospective models and the financial empirics of the low‐carbon transition. I expound their main results, critically assess underlying methodologies and propose a framework to compare results. The review ends by suggesting some avenues for future research.

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Impact of Global Risk Factors on the Islamic Stock Market: New Evidence from Wavelet Analysis

Kazak,

Saiti,

Kılıç

et al. 2024

Comput Econ

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The emergence of Islamic finance as an alternative financial investment area and the increasing political and economic uncertainty around the world necessitated an examination of the relationship between these two factors. This study examines the impact of four important global uncertainty and risk indicators “Global Economic Policy Uncertainty-GEPU, Geopolitical Risk Index-GPR, World Uncertainty Index-WUI, and CBOE Volatility Index-VIX” on two important Islamic stock market indices (Dow Jones Islamic Market Index and Bist Participation 100) using wavelet coherence (WTC) and asymmetric Fourier TY analyzes Quarterly data for the period March 2011–June 2023 were used in the study. The results of the analysis show that economic instability indicators impact Islamic equity market indices (both in Turkey and the world). This effect is determined as VIX, GEPU, GPR, and WUI. In addition, the fact that the GPR and WUI indices, which have an impact on conventional markets, have truly little and only a partial impact on Islamic equity markets is an important finding. The results of this study make important contributions to the literature and provide important findings for investors and policy makers.

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International political uncertainty and climate risk in the stock market

Cited by 54 publications

References 61 publications

Climate change attention and carbon futures return prediction

Climate change attention and carbon futures return prediction

Financial stability, stranded assets and the low‐carbon transition – A critical review of the theoretical and applied literatures

Impact of Global Risk Factors on the Islamic Stock Market: New Evidence from Wavelet Analysis

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