The effect of global price movements on the energy sector commodity on bitcoin price movement during the COVID-19 pandemic

Evaluating the environmental effects of bitcoin mining on energy and water use in the context of energy transition

This study investigates the impact of Bitcoin's energy and water consumption on environmental sustainability, focusing on the load capacity factor (LCF) and the roles of energy transition green technology in major cryptocurrency-producing nations. Utilizing the method of moments quantile regression (MMQR) approach, the findings reveal a negative impact of mining energy consumption on environmental sustainability, particularly in the lower quantiles, with a stronger negative effect in the higher quantiles. Energy transition plays a critical role in moderating this impact, though the shift towards cleaner energy sources has not been sufficient to mitigate the adverse environmental effects. The water footprint has limited influence on LCF across upper and lower quantiles. Moreover, the results do not support the LCF hypothesis. An increase in mining activity leads to a rise in LCF, while this effect turns negative in the 90th quantile. These findings underscore the importance of energy transition in reducing Bitcoin's environmental footprint and emphasize the need for policymakers to swiftly enact regulations and foster innovative technologies to promote environmentally sustainable digital currencies while providing valuable insights into water resource management.

Renewable energy and cryptocurrency: A dual approach to economic viability and environmental sustainability

One of the foremost challenges facing Bitcoin, as the most valuable cryptocurrency operating on a proof-of-work mechanism, is its substantial energy consumption and environmental impact. With the expansion of the Bitcoin market, mining has surged in popularity, particularly in countries where energy and monetary costs are comparatively low. This study aims to assess the impact of utilizing renewable energy from a photovoltaic system for Bitcoin mining, simulating a solar power plant with a 50.91-MW capacity alongside a corresponding Bitcoin mining operation in the United Arab Emirates. Economic evaluations were conducted using comprehensive, historically archived data to ensure results that closely mirror real-world scenarios. Additionally, for a more nuanced comparison, an economic assessment of selling the power plant's electricity to the grid was also performed, with the findings juxtaposed. The outcomes indicate that initiating such a system at the start of 2020 with an investment of approximately $42 million could recoup its costs in about 3.5 years. In contrast, selling electricity to the grid would extend the power plant's return on investment period to 8.1 years. Furthermore, the environmental evaluation revealed that adopting renewable solar energy for mining could avert the emission of around 50,000 tons of CO2 annually.

The impact of index futures crash risk on bitcoin futures returns and volatility

This study examines the relationship between E-mini S&P 500 futures' crash risk and Bitcoin futures' returns and volatility using data from 2017 to 2021. While E-mini S&P 500's crash risk doesn't significantly influence Bitcoin returns, it correlates with its volatility, especially during events like the COVID-19 pandemic and U.S. elections. Furthermore, as global and emerging market indices rise, Bitcoin futures volatility decreases, suggesting its role as a hedging tool. These findings are pivotal for investors aiming to construct informed trading strategies, leverage Bitcoin futures as a hedging asset during economic instability, and keep tabs on traditional market indicators like E-mini S&P 500 crash risk for anticipating fluctuations in Bitcoin futures.

The effect of voluntary disclosure on financial performance: Empirical study on manufacturing industry in Indonesia

The manufacturing sector's adherence to managing natural resources from the environment still needs to be improved. This study's objective is to determine how Corporate Social Responsibility (CSR) influences the financial performance of manufacturing firms featured in the LQ45 Index, as measured by Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM). All manufacturing companies that are included in the LQ45 Index's population for this study were sampled using the purposive sampling method. This study uses secondary data from the CSRI based on the Global Reporting Initiative (GRI) G4 standard for 2018-2020 and the annual reports of companies in the manufacturing industry sector listed on the LQ45 Index. Moreover, applying a quantitative methodology, descriptive statistical methods, conventional assumption tests, and simple linear regression analysis were applied in this study's data analysis. The results of the study proved that CSR has a significant effect on ROA but does not affect the ROE and NPM of LQ45 manufacturing companies. In accordance with the signaling theory, CSR disclosure sends a favourable message to outsiders, which stakeholders and shareholders will respond to through changes in business earnings. CSR implementation can establish a positive image for the company, but it can also improve the company's image in both the commodity and capital markets. Investors will be more attracted to a company with a positive corporate image since a positive corporate image increases consumer loyalty. As consumer loyalty rises, the company's sales will likewise rise, and its profitability will increase as a result. This paper opens a new research path in corporate social responsibility and financial performance for possible links among variables; a matter that has not been previously explored in Indonesia Manufacturing Public Companies.