Examining the interconnectedness of green finance: an analysis of dynamic spillover effects among green bonds, renewable energy, and carbon markets

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(31), С. 77605 - 77621

Опубликована: Июнь 1, 2023

Язык: Английский

---

Exploring the nexus between monetary uncertainty and volatility in global crude oil: A contemporary approach of regime-switching

Resources Policy, Год журнала: 2023, Номер 85, С. 103886 - 103886

Опубликована: Июль 28, 2023

Язык: Английский

---

The protective nature of gold during times of oil price volatility: An analysis of the COVID-19 pandemic

The Extractive Industries and Society, Год журнала: 2023, Номер 15, С. 101284 - 101284

Опубликована: Июнь 6, 2023

Язык: Английский

---

Price forecasting through neural networks for crude oil, heating oil, and natural gas

Deleted Journal, Год журнала: 2024, Номер 1, С. 100001 - 100001

Опубликована: Фев. 29, 2024

Building price projections of various energy commodities has long been an important endeavor for a wide range participants in the market. We study forecast problem this paper by concentrating on four significant commodities. Using nonlinear autoregressive neural network models, we investigate daily prices WTI and Brent crude oil as well monthly Henry Hub natural gas New York Harbor No. 2 heating oil. prediction performance resulting from model configurations, including training techniques, hidden neurons, delays, data segmentation. Based investigation, relatively straightforward models are built that yield quite accurate reliable performance. Specifically, terms relative root mean square errors is 1.96%/1.81%/9.75%/21.76%, 1.96%/1.80%/8.76%/14.41%, 1.87%/1.78%/9.10%/16.97% training, validation, testing, respectively, overall error 1.95%/1.80%/9.51%/20.35% whole sample oil/Brent oil/New oil/Henry gas. The outcomes projection might be used technical analysis or integrated with other fundamental forecasts policy analysis.

Язык: Английский

---

Impact of natural resources and technology on economic development and sustainable environment – Analysis of resources-energy-growth-environment linkages in BRICS

Resources Policy, Год журнала: 2023, Номер 85, С. 103865 - 103865

Опубликована: Июль 8, 2023

Язык: Английский

---

Exploring carbon dioxide emissions forecasting in China: A policy-oriented perspective using projection pursuit regression and machine learning models

Technological Forecasting and Social Change, Год журнала: 2023, Номер 197, С. 122872 - 122872

Опубликована: Сен. 28, 2023

Язык: Английский

---

A novel deep-learning technique for forecasting oil price volatility using historical prices of five precious metals in context of green financing – A comparison of deep learning, machine learning, and statistical models

Resources Policy, Год журнала: 2023, Номер 86, С. 104216 - 104216

Опубликована: Окт. 1, 2023

Язык: Английский

---

Techno-economic and environmental analyses of hybrid renewable energy systems for a remote location employing machine learning models

Applied Energy, Год журнала: 2024, Номер 361, С. 122884 - 122884

Опубликована: Март 5, 2024

This article offers a detailed investigation into the technical, economic along with environmental performance of four configurations hybrid renewable energy systems (HRESs), aiming at supplying electricity to remote location, Henry Island in India. The study explores combinations involving photovoltaic (PV) panels, wind turbines, biogas generators, batteries, and converters, while evaluating their economic, performance. analysis yield that among all examined, PV, turbine, generator, battery, converter integrated configuration stands out highly favourable results, showcasing minimal value levelized cost (LCOE) $0.4224 per kWh lowest net present (NPC) $6.41 million. However, technical comprising PV battery yields maximum excess output 2,838,968 kWh/yr. Additionally, machine learning techniques are employed analyse data. shows Bilayered Neural Network model achieves exceptional accuracy predicting LCOE, Medium proves be most accurate These findings provide valuable perception design optimisation HRES for off-grid applications regions, taking account aspects.

Язык: Английский

---

Investigating the causal relationship between electricity pricing policy and CO2 emission: An application of machine learning-driven metalearners

Journal of Environmental Management, Год журнала: 2025, Номер 380, С. 124514 - 124514

Опубликована: Март 13, 2025

Язык: Английский

---

The role of financial markets in the energy transition: an analysis of investment trends and opportunities in renewable energy and clean technology

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(43), С. 97948 - 97964

Опубликована: Авг. 21, 2023

Язык: Английский

---