Using machine learning to forecast clean energy, commodities, green bonds and ESG index prices: How important is financial stress? DOI
Hayet Soltani,

Jamila Taleb,

Fatma Ben Hamadou

и другие.

EuroMed Journal of Business, Год журнала: 2024, Номер unknown

Опубликована: Сен. 25, 2024

Purpose This study investigates clean energy, commodities, green bonds and environmental, social governance (ESG) index prices forecasting assesses the predictive performance of various factors on these asset prices, used for development a robust support decision model using machine learning (ML) techniques. More specifically, we explore impact financial stress price. Design/methodology/approach We utilize feature selection techniques to evaluate efficacy prices. Moreover, have developed by assessing accuracy two ML models: deep long short-term memory (LSTM) neural networks extreme gradient boosting (XGBoost) model. To check robustness results, authors referred bootstrap linear regression as an alternative traditional method Findings The results highlight significance in enhancing price forecast accuracy, with (FSI) panic (PI) emerging primary determinants. In terms model's our analysis reveals that LSTM outperformed XGBoost model, establishing itself most efficient algorithm among tested. Practical implications research enhances comprehension, which is valuable both investors policymakers seeking improved through utilization Originality/value authors' best knowledge, this marks inaugural attempt construct multivariate Indeed, utilizing provides practical value tool shaping investment strategies.

Язык: Английский

Navigating the winds of change: Assessing the impact of wind energy innovations and fossil energy efficiency on carbon emissions in China DOI
Oktay Özkan, Mustafa Necati ÇOBAN, Mehmet Akif Destek

и другие.

Renewable Energy, Год журнала: 2024, Номер 228, С. 120623 - 120623

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

14
Evaluating the nexus between energy transition and load capacity factor in Germany: evidence from novel quantile-based approaches DOI
Oktay Özkan, Mehmet Akif Destek, Sercan Aydın

и другие.

International Journal of Sustainable Development & World Ecology, Год журнала: 2024, Номер 31(6), С. 707 - 725

Опубликована: Март 12, 2024

This study attempts to investigate how Germany's energy transition has affected environmental quality by considering natural resources, economic growth, financial development, and globalization for the period from 1980 2021. It is also aimed discover that interactions alter with different levels of load capacity factor explanatory variables using novel quantile-based approaches. Thanks unique approaches utilized, efficacy process can be determined quantiles time periods. The results reveal although development enhance quality, growth increasing resource rents harms environment. In addition, increase in all a positive effect on capacity. impact weak high low but it becomes more pronounced middle Our offers various policy recommendations short- long-term low-level effectiveness Germany.

Язык: Английский

Процитировано

6
The growth–environment nexus amid geopolitical risks: cointegration and machine learning algorithm approaches DOI Creative Commons
Md. Idris Ali, Md. Atikur Rahaman, Mohammed Julfikar Ali

и другие.

Discover Sustainability, Год журнала: 2025, Номер 6(1)

Опубликована: Фев. 7, 2025

Geopolitical tensions, including the Russia-Ukraine conflict, ongoing Middle-Eastern wars, and post-Cold War dynamics between USA Russia, have contributed to significant global political instability. These risks disrupt economic growth, destabilize energy supply chains, foster uncertainty, often prioritizing security over environmental sustainability. Existing literature inadequately addresses how geopolitical interact with sustainability, particularly within developed economies like Canada. To bridge this gap, study examines role of per capita income on outcomes under Environmental Kuznets Curve (EKC) framework, explicitly incorporating as a critical determinant. Using Canadian time series data spanning from 1980 2022, research employs autoregressive distributed lag (ARDL) estimation technique explore short- long-term cointegrating relationships among key variables, consumption, trade openness, foreign direct investment (FDI), ICT development, financial development. The findings confirm inverted U-shaped EKC hypothesis for Canada, indicating that growth initially exacerbates carbon emissions (CO2) before leading improvements at higher levels. are found positively contribute CO2 emissions, emphasizing their barrier achieving validate robustness, Kernel Regularized Least Squares (KRLS) machine learning approach is employed, confirming consistency results. Additionally, Toda-Yamamoto causality test identifies directional causal variables. Policy recommendations emphasize need Canada implement targeted strategies mitigate impact outcomes. Specifically, advocates for: (1) diversifying sources reduce reliance geopolitically sensitive regions, (2) investing in renewable technologies ensure sustainable (3) enhancing policies prioritize low-carbon technologies.

Язык: Английский

Процитировано

0
Risk Spillover Effects of International Risk Factors on China's Energy Market - Based on Geopolitical Threats and Shipping Markets DOI Creative Commons

Zheng Yu Ren,

Yu Jie Chen, Cody Yu‐Ling Hsiao

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Апрель 11, 2024

Abstract Risks caused by geo-risk cases, such as regional conflicts, propagate around the world, and this study provides insights into dynamic complex interactions of risks between international geopolitical risks, shipping markets, China's carbon market, energy sector. The findings show that risk markets are net transmitters with positive spillover values, indicating they tend to export volatility other markets. In contrast, Chinese market traditional high-emission sectors exhibit amplified in face extreme events COVID-19 pandemic, Russian-Ukrainian conflict Israeli-Palestinian conflict. This highlights time-varying nature spillovers these Notably, peaks from Geopolitical Risk Index Baltic Dry Shanghai crude oil futures suggest a direct correlation tensions affecting industries, conflicts oil-rich regions or maritime disputes lanes. These highlight mediating role transmission paper concludes policy recommendations for predicting mitigating impact uncertainty on

Язык: Английский

Процитировано

2
Using machine learning to forecast clean energy, commodities, green bonds and ESG index prices: How important is financial stress? DOI
Hayet Soltani,

Jamila Taleb,

Fatma Ben Hamadou

и другие.

EuroMed Journal of Business, Год журнала: 2024, Номер unknown

Опубликована: Сен. 25, 2024

Purpose This study investigates clean energy, commodities, green bonds and environmental, social governance (ESG) index prices forecasting assesses the predictive performance of various factors on these asset prices, used for development a robust support decision model using machine learning (ML) techniques. More specifically, we explore impact financial stress price. Design/methodology/approach We utilize feature selection techniques to evaluate efficacy prices. Moreover, have developed by assessing accuracy two ML models: deep long short-term memory (LSTM) neural networks extreme gradient boosting (XGBoost) model. To check robustness results, authors referred bootstrap linear regression as an alternative traditional method Findings The results highlight significance in enhancing price forecast accuracy, with (FSI) panic (PI) emerging primary determinants. In terms model's our analysis reveals that LSTM outperformed XGBoost model, establishing itself most efficient algorithm among tested. Practical implications research enhances comprehension, which is valuable both investors policymakers seeking improved through utilization Originality/value authors' best knowledge, this marks inaugural attempt construct multivariate Indeed, utilizing provides practical value tool shaping investment strategies.

Язык: Английский

Процитировано

2