Blockchain Papers

Lei Xu, Takuji Kinkyo

No abstract is available for this record.

Nguyen Hong Yen, Lê Thanh Hà

Purpose This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations. Design/methodology/approach The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets. Findings The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020. Practical implications Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets.

Ayyüce Memiş Karataş, Emin Karataş, Ayhan Kapusuzoğlu, Nildağ Başak Ceylan

Abstract This chapter presents an overview of the Bitcoin and its impacts on the environment and economics from the viewpoint of carrying out a systematic analysis of the literature related to the environmental and economic effect of digital currency. It is aimed to summarize and critically examine the points of view regarding Bitcoin mining, considering its effects on global warming and the social environment, employing peer-reviewed data associated through literatures. As a result, this study provides the chance to analyze the set of knowledge regarding the effects of the Bitcoin mining procedure on the ecosystem in regard to energy use and CO2 emissions regarding unit root tests and causality test based on nonlinear models. The results show that there exists a nonlinear causal relationship between statistics on Bitcoin mining and the CO2 emissions. The results also imply that Bitcoin remains to be a tool utilized in the economic environment for a range of objectives despite high energy consumption and some negative environmental impact within the scope of renewable energy; hence, authorities would take Bitcoin mining impacts into account to reduce CO2 emissions.

Di Wang, Daozhi Zhao, Fang Chen

With the development of ecological economics, energy-saving green energy chain management has been a wide concern of academia and industries. However, the relatively high cost of green investment makes manufacturers face the problem of financial constraints. On this basis, because the green level information of products is proprietary to manufacturers, manufacturers will lie about the green level of products in order to improve their profits out of the principle of profit maximization. As a result, banks cannot obtain the true green level of products, reducing the benefits of the green energy-efficient supply chain system and making the market of green products volatile. In view of this, blockchain technology is introduced in this paper to improve customer’s product green level sensitivity and obtain lower green credit interest rates from banks. In this paper, a green supply chain financing model based on blockchain technology was constructed under the condition of green information misreporting, and it is compared with the benchmark without blockchain technology. Research shows that the adoption of blockchain can achieve Pareto improvement of green supply chain members. In addition, manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. We compared the profits of green manufacturers with those of retailers and the total emissions of manufacturers. The results show that: (1) When the financing intensity exceeds a certain value, there is an optimal coverage of green financing to ensure that the profit target of manufacturers, the profit target of retailers and the emission reduction target are achieved simultaneously. (2) The adoption of blockchain can achieve Pareto improvement of green energy supply chain members. The actual data of green transformation of Jinyuan New Technology Company were cited. Through calculation, it was found that green transformation can reduce the emissions of enterprises. When the financing intensity is in a certain range, the profits of manufacturers and retailers can be maximized, and the emission reduction degree is the highest. Thus, the practicability and reliability of this model were proved. (3) Manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. The research results of this paper provide solutions for enterprises with limited funds for green transformation and provide a theoretical basis for the government to formulate emission reduction incentive mechanism.

Provash Kumer Sarker, Chi Keung Marco Lau, Ashis Kumar Pradhan

This paper investigates the asymmetric effects of climate policy uncertainty (CPU) and the global price of energy index (GPEI) on Bitcoin prices. It applies the nonlinear ARDL method and the Granger causality test to examine how changes in climate policy uncertainty and energy prices influence Bitcoin prices. Using the monthly data of CPU, GPEI, and BTC from 2013M10–2021M12, the findings show that CPU's increases and GPEI's decreases positively affect BTC in the short term. Specifically, CPU and GPEI's increase and decrease show significantly higher effects on BTC in the long term. The causality result shows bidirectional causality between BTC and CPU's increases/decreases, while unidirectional causality runs from GPEI's increases/decreases to BTC. These findings suggest that Bitcoin investors should be aware of the risks associated with climate policy uncertainty and fluctuations in energy prices, as these factors can significantly asymmetrically impact Bitcoin prices.

Nguyễn Thị Thanh Huyền, Nguyen Hong Yen, Lê Thanh Hà

By identifying the connectedness of seven indicators from January 1, 2019, to June 13, 2022, we choose an extended joint connectedness approach to a vector autoregression model with time-varying parameter (TVP-VAR) to analyze interlinkages between Crypto Volatility (CV) and Energy Volatility (EV). Our findings show that the COVID-19 outbreak seems to have an impact on the dynamic connectedness of the whole system, which peaks at about 60% toward the end of 2019. According to net total directional connectedness over a quantile, throughout the 2020–2022 timeframe, natural gas and crude oil are net shock transmitters, while the CV, clean energy, solar energy, and green bonds consistently receive all other indicators. Specifically, pairwise connectedness indicates that the CV appears to be a net transmitter of shocks to all energy indicators before the COVID-19 outbreak but acts as a net receiver of shocks from clean energy, wind energy, and green bonds in late 2020. The CV mostly has spillover effects on green bonds. The primary net transmitter of shocks to the Crypto market is crude oil. Our findings are critical in helping investors and authorities design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty.

Sofia Karagiannopoulou, Konstantina Ragazou, Ioannis Passas, Alexandros Garefalakis · 5 authors

This study aimed to investigate the interactions between Bitcoin to euro, gold, and STOXX50 during the period of COVID-19. First, a bibliometric analysis based on the R package was applied to highlight the research trends in the field during the period of the COVID-19 pandemic. While investigating the effects of the pandemic on Bitcoin, the number of cases of COVID-19 was used as a proxy. Using daily data for the period 1 March 2020 to 3 March 2020 and based on a vector autoregressive model, impulse response, and variance decomposition were utilized to analyze the dynamic relationships among the variables. The results revealed that the COVID-19 cases and gold hurt the exchange rate of Bitcoin to euro, while there was great volatility regarding the response of Bitcoin to a shock of STOXX50. The Granger causality test was constructed to investigate the relationships among the variables. The results show the presence of unidirectional causality running from new cases to STOXX50 and from STOXX50 to gold. This study contributes to the existing scholarly research into the dynamic relationships that appeared among Bitcoin, gold, and STOXX50 in a period of great uncertainty. Finally, the findings have significant implications for investors, who are interested in diversifying their portfolios.

Walid Mensi, Rim El Khoury, Syed Riaz Mahmood Ali, Xuan Vinh Vo · 5 authors

No abstract is available for this record.

Simran Simran, Anil Kumar Sharma

No abstract is available for this record.

Ahmad Monir Abdullah

In this article, the MGARCH-DCC model is utilised to compare the usefulness of Bitcoin, gold, and crude oil as a hedge and safe haven for the US Islamic stock index. We utilised daily data from August 2014 to April 2022, which covers the most recent COVID-19 epidemic and the Russia-Ukraine conflict. We find the dynamic correlation between Bitcoin and the US Islamic stock index to be low and often negative during major economic and political events, showing that Bitcoin is a safe haven and hedging instrument, especially during the pandemic period. However, we find that Bitcoin is very volatile, limiting its use as a safe haven and hedging instrument compared to gold. Gold is more stable and negatively correlated with the US Islamic stock index, making it more appropriate as a diversifier and hedging instrument. Adding gold to the US Islamic stock index portfolio reduces the portfolio’s risk.

Abu Hanifa Md. Noman, Muhammad Mahmudul Karim, M. Kabir Hassan, Muhammad Asif Khan · 5 authors

No abstract is available for this record.

Minghan Jiang, Yufei Xia

Non-fungible tokens (NFTs) have experienced wild market fluctuation during the past years, which leads to the high volatility of NFT’s daily price. This paper examines two potential volatility drivers of NFTs: macroeconomic fundamentals and investor attention. We employ the global and local economic policy uncertainty (EPU) indices as the economic fundamentals’ proxies. The investor attention is represented by the Google search volumes (GSV) or NFTs attention index. Based on the empirical results of a modified generalized autoregressive conditional heteroskedasticity –mixed-data sampling (G-M) model, we find that either economic fundamentals or investor attention can increase the volatility of NFTs significantly. The monthly global EPU index adjusted by the current GDP and weekly GSV contain complementary information. Macroeconomic fundamentals and investor attention can jointly model the volatility of NFTs better than considering only one explanatory variable, as suggested by the G-M model with two explanatory variables. The results remain robust to alternative Twitter-based EPU indices and the ongoing COVID-19 pandemic period.

Fang-Mei Tseng, Ching-Wen Liang, Ngoc B. Nguyen

No abstract is available for this record.

Sai Shibu N B

Abstract Carbon dioxide (CO2) emissions primarily contribute to global warming and climate change. The immediate source of CO2 emissions is burning fossil fuels like petrol, diesel, natural gas and coal, accounting for 78% of total emissions. CO2 emissions have risen since the late 1800s, reaching a record high of 33.1 billion tons in 2019. The paper proposes a Blockchain and IoT-based framework to track and trade carbon credits, aiming to reduce carbon dioxide emissions and mitigate their impact on global warming and climate change. We consider electrical energy as one use case for carbon emission and credit trading. The framework will monitor the energy usage of each entity, recording real time carbon emissions in a tamperproof blockchain ledger. Each entity will receive carbon credits based on the recorded emissions, which can then be traded on a blockchain exchange. This will enable entities with higher emissions to offset their emissions by purchasing credits from entities with lower emissions. The blockchain ledger ensures the authenticity and transparency of the carbon emissions data, promoting a secure and efficient solution for reducing carbon emissions. The paper also outlines a reward and penalty mechanism for consumers, encouraging them to reduce their carbon footprint and contribute to a more sustainable future. The paper discusses the blockchain and IoT-based carbon credit exchange architecture, including algorithms for estimating energy consumption, carbon emissions, reward, and penalty. The paper concludes with a proof of concept implementation using the Ethereum platform and a performance evaluation of the algorithms. The paper proposes a comprehensive solution for reducing carbon emissions and mitigating their environmental impact, leveraging the strengths of blockchain and IoT technologies.

Kelan Gao

The global current situation continues to be turbulent. International crises like the Covid-19 epidemic and the continuing Russian-Ukrainian war have thrown the global economy for a loop. As a result, global economic policy uncertainty has spiked due to the resulting spike in energy prices and economic disruptions. During the outbreak of Covid-19, prices of bitcoin (BTC) have moved higher, but its hedging effect is weakening. Also, combined with rising global inflation expectations and the constant rate hikes by central banks against inflation, bitcoin's hedging effectiveness is waning due to its strong correlation with equities. Furthermore, with the outbreak of the Russian-Ukrainian war, the price of gold continued to rise, and the relationship between gold and the global financial market decreased, confirming gold's diversification ability in a crisis. Simultaneously, the link between gold and bitcoin has weakened marginally. Ultimately, preliminary evidence suggests that gold and bitcoin can be used as complements, rather than substitutes, for diversification purposes during a crisis. This article will construct a portfolio about bitcoin and gold, and examine how individual gold and bitcoin and this portfolio performed as hedging assets throughout the Covid-19 pandemic and the Russian-Ukrainian war.

Yang Yu

Digital finance development has an important role in promoting economic transformation and has become a new engine leading the development of the real economy, while green innovation is an important goal of the current economic transformation to a green and sustainable one. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2018, this paper finds that digital finance has a significant promoting effect on the green innovation of new energy enterprises through panel data fixed effects regression model. Furthermore, through sub-sample regression, it is found that the promotion effect of digital finance on new energy enterprises is heterogeneous, and the promotion effect is more significant for state-owned enterprises and enterprises with more decentralized power. The above findings of this paper have important implications for the current economic transformation in China.

Ahmed Ayadi, Yosra Ghabri, Khaled Guesmi

No abstract is available for this record.

Reşat Ceylan, Cihat KARADEMİR, Şencan FELEK

Bu çalışmada, 2017M1-2022M1 dönemleri arasındaki veriler kullanılarak Bitcoin (BTC) ile Karbon Emisyonu (CO2) arasındaki ilişki incelenmiştir. Son zamanlarda yapılan çalışmalara istinaden kripto para ve enerji piyasalarının spekülatif ve kırılgan yapıya sahip olduğu ve bundan dolayı değişkenlerin doğrusal olmayan bir forma sahip olabileceği konusuna dikkat çekildiği gözlenmektedir. Dolayısıyla bu bilgiler çerçevesinde çalışmada öncelikle Luukkonen vd. (1988), Harvey vd. (2008) doğrusallık testi ve Kapetanios vd. (2003) doğrusal olmayan birim kök testi ile değişkenlerin doğrusallık sınaması yapılmaktadır. Akabinde değişkenlerin doğrusal olmayan forma sahip olduğu tespit edildiği için çalışmada Kapetanios vd. (2006) Doğrusal Olmayan Eşbütünleşme analizi kullanılmaktadır. Kapetanios vd. (2006) testi bulgularına göre BTC ile CO2 arasında uzun dönemde doğrusal olmayan bir eşbütünleşme ilişkisi olduğu tespit edilmektedir. Bu durum BTC ile CO2 arasındaki ilişkinin uzun dönemde dengeye doğrusal olmayan bir şekilde yakınsadığı sonucunu göstermektedir. Değişkenler arasında doğrusal olmayan eşbütünleşme ilişkisini tespit ettikten sonra bu ilişkinin yönünü belirlemek amacıyla yapılan Granger nedensellik testi sonucuna göre ise Bitcoin’den Karbon Emisyonuna doğru tek yönlü nedensellik olduğu tespit edilmektedir. Bu bulgu, BTC üretiminde kullanılan enerjinin çevre dostu kaynaklardan elde edilmesine yönelik politikaların benimsenmesi gerektiği biçiminde yorumlanabilir.

Zhenzhen Jia, Sunil Tiwari, Jianhua Zhou, Muhammad Umar Farooq · 5 authors

No abstract is available for this record.

Nezir Köse, Emre Ünal

Abstract For this paper, the relationship between seventeen popular cryptocurrencies was analyzed by multivariate Granger causality tests and simple linear regression, using data spanning the period 1 September 2020 to 8 December 2021. The novelty of this work is that it studies the effects of sampling interval and sample size in cryptocurrency markets, which can yield significantly different results. Minute-by-minute, hourly and daily data were collected to examine the Granger causality relationship between cryptocurrencies. It was found that all the currencies demonstrated a significant causality relationship when high frequency (such as minute-by-minute) data was used, in contrast to hourly and daily data. The bigger the sample size, the higher the probability of rejecting the null hypothesis. Hence, the null hypothesis for the Granger causality test can be rejected for minute-by-minute time series data because of too large a sample size. Granger causality test results for hourly and daily data indicated that Bitcoin, Ethereum Classic, and Neo were leading indicators among the cryptocurrencies included in the research. In addition, according to simple linear regression analysis, the short term marginal effect of Bitcoin plays an important role by creating significant impacts on other cryptocurrencies.

Hao Zhang, Ye Duan, Jun Yang, Han Zeng-lin · 5 authors

Green finance is crucial to advancing the decrease of haze pollution in my nation as a new kind of environmental governance. This research constructs a comprehensive evaluation system of green finance to analyze the impact of green finance on haze pollution reduction and to consider the mediating role of energy efficiency in 30 provinces and regions in China. Through a series of robustness tests, the mechanism and path of green finance on haze pollution reduction are confirmed. The main conclusions are as follows: First, the development of green finance has a positive effect on haze pollution reduction. Second, the upgrading of industrial structure and the improvement of technological level are important paths for green finance to promote haze pollution reduction, and can also have an indirect impact through energy efficiency. The moderating and mediating effects of energy efficiency and green finance can effectively promote the reduction of haze pollution. In other words, the development of green finance can achieve the goal of reducing haze pollution by improving energy efficiency. Third, there is regional heterogeneity in green finance for haze pollution reduction, and regions with high levels of green finance are more effective in reducing haze pollution. Fourth, environmental Supervision, environmental decentralization and average wind speed can promote haze pollution reduction, economic development to some extent exacerbated the haze pollution. Based on the above research conclusions, this paper puts forward corresponding countermeasures and suggestions.

Inzamam Ul Haq, Paulo Ferreira, Derick Quintino, Nhan Huynh · 5 authors

The purpose of the research is to explore the dynamic multiscale linkage between economic policy uncertainty, equity market volatility, energy and sustainable cryptocurrencies during the COVID-19 period. We use a multiscale TVP-VAR model considering level (EPUs and IDEMV) and returns series (cryptocurrencies) from 1 December 2019 to 30 September 2022. The data are then decomposed into six wavelet components, based on the wavelet MODWT method. The TVP-VAR connectedness approach is used to uncover the dynamic connectedness among EPUs, energy and sustainable cryptocurrency returns. Our findings reveal that CNEPU (USEPU) is the strongest (weakest) NET volatility transmitter. IDEMV is the most consistent volatility NET transmitter among all uncertainty indices across the original returns and wavelet scales (D1~D6). Energy cryptocurrencies, i.e., GRID, POW and SNC, are more likely to receive volatility spillovers than sustainable cryptocurrencies during a turbulent period (COVID-19). XLM (XNO) is least (most) affected by volatility spillover in system-wide connectedness, and XLM (ADA and MIOTA) showed a consistent (heterogeneous) non-recipient behavior across the six wavelet (D1~D6) scales and original return series. This study uncovers the dynamic connectedness across multiscale, which will support investors considering different investment horizons (D1~D6).

Halilibrahim Gökgöz, Cantürk Kayahan

Bu çalışmada, Bitcoin ile gelişmiş ve gelişmekte olan ülkelerin hisse senedi piyasaları arasındaki volatilite yayılım ilişkisinin incelenmesi ve bulguların finansal piyasaları etkileyen küresel olaylar bağlamında değerlendirilmesi amaçlanmıştır. Bu amaçla 03.01.2017-25.03.2022 dönemi, Bitcoin, MSCI ABD, MSCI Avrupa ve MSCI gelişmekte olan piyasalar endeksi günlük verilerine zamanla değişen parametre vektör otoregresif (TVP-VAR) modeli uygulanmıştır. Uygulama sonucunda Bitcoin’in MSCI ABD ve MSC Avrupa karşsısında net volatilite alıcısı olduğu ve MSCI gelişmekte olan piyasalar karşısında net volatilite yayıcısı olduğu gözlenmiştir. MSCI ABD’nin net volatililite yayıcısı ve MSCI gelişmekte olan piyasaların ise net volatilite alıcısı olduğu tespit edilmiştir. Ayrıca Bitcoin’in gelişmiş ve gelişmekte olan piyasalarla zayıf bağlantılı olduğu gözlenmiştir. Bulgular, volatilite yayılımının aşırı artış-azalış gösterdiği dönemlerde tüm dünyayı etkileyen küresel olaylar olduğunu göstermiştir.

Arshian Sharif, Mariem Brahim, Eyup Dogan, Panayiotis Tzeremes

No abstract is available for this record.