Blockchain Papers

Linh Pham, Toan Luu Duc Huynh, Waqas Hanif

No abstract is available for this record.

Subhasree Mukherjee, Nilofer Hussaini

The study investigates the relationship between the returns of Non-Fungible Tokens (NFT) and its categories; and fear indices during times of crisis. The fear indices considered are Global Fear Index (GFI), Global Economic Policy Uncertainty Index (GEPU), Twitter based Economic Uncertainty Index (TEU), Global Consumer Confidence Index (CCI), Infectious Diseases Equity Market Volatility Index (IDEMV) and Crypto Volatility Index (CVI). Employing Granger Causality Test, Autoregressive Distributed Lag technique and ARDL Bounds test on data for the period starting 1st February 2020 and ending 28th February 2022, it is found that short run association exists between TEU, CVI and NFT returns. Further, GFI leads NFT Art returns while TEU leads NFT Metaverse returns by lag 5 and lag 2 respectively. No association between fear metrics and NFT Collectible, NFT Game and NFT utility is observed. No long run association in found between NFT returns and fear indices except TEU which influences NFT returns. It is concluded that NFT, NFT Art and NFT Metaverse returns have positive association to at least one fear index during times of turmoil, especially for the short run.

John W. Goodell, John W. Goodell, Miklesh Prasad Yadav, Junhu Ruan · 7 authors

This paper analyses the connectedness among traditional assets, digital assets and renewable energy for extending the data from December 31, 2019 to January 2, 2023. For an empirical analysis, time varying parameter (TVP-VAR) is employed. We find that Chainlink (DeFi) is the highest receiver, while bitcoin is the highest transmitter of shocks to the network. Additionally, we also find that Non-Fungible Tokens (NFT) acts as the most suitable asset to be included in portfolio since it is least connected with rest of the examined assets classes. Results are important for investors and portfolio managers.

İbrahim Yağlı, Özkan HAYKIR

The study aims to investigate the causality relationship between investor happiness and cryptocurrency returns. The study is focused on the five largest cryptocurrencies, specifically Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Ripple (XRP), and Cardano (ADA). Twitter-based Happiness Index is used to measure investor happiness. The sample period covers the period between January 1, 2019, and October 2, 2021. The Zivot-Andrews test is employed to detect stationary of covariates. After ensuring that all variables are stationary at levels, the Granger causality test is adopted to understand the relationship between the happiness index and cryptocurrency returns. The impulse-response functions are illustrated. The results indicate that there is a uni-directional relationship from BTC to Happiness Index, and Happiness Index to ETH. Considering that the causal relationship between cryptocurrency returns and investor happiness differs between cryptocurrencies, it is thought that investors should closely monitor the happiness index and make adjustments in their portfolios in response to changes in investor happiness.

Imran Yousaf, Mariya Gubareva, Тамара Теплова

Employing the vector auto-regression based on generalized forecast error variance decomposition, this paper investigates the connectedness of non-fungible tokens (NFTs) with precious and industrial metals and compares the results with those for conventional cryptocurrencies (CCCs). Our study scrutinizes separately the total static and the net dynamic spillovers of returns and volatilities from March 2018 to August 2021. We evidence that both, the total return and total volatility connectedness indices for the NFTs-metals framework are below the respective indices for the CCCs-metals framework, indicating new avenues for hedging and harvesting diversification benefits of NFT exposures. We provide empirical evidence that the NFTs are distinct from the CCCs not only in terms of the volatility spillovers, but in terms of the return spillovers too. In addition, we observe the decoupling in the net volatility spillovers between the precious and non-precious metals due to the COVID-19 meltdown. COVID-19 makes precious metals transmit volatility while industrial metals continue acting as net receivers of volatility shocks. Optimal weight and hedge ratios are presented for NFT-metal and crypto-metal pairs. These findings provide potential implications for investors and policy makers.

Lingling Xu, Tingting Tian

No abstract is available for this record.

Maxat Kassen

Abstract The article elaborates on the potential of blockchain technology to transform governance in different sectors of economy. The research primarily relies on rich empirical data that have been collected from semistructured interviews and focus group studies with professional blockchain developers. In this regard, the article aims to answer the following questions: How could blockchain governance conceptually work? How could one illustrate schematically key principles of its implementation? What are the key features of blockchain governance? Why are they important? What benefits could the concept bring to different sectors of economy if its potential is realized? What are the typical barriers and limitations of blockchain governance? What could be recommended to overcome them?

Miaomiao Wang, Jun Wu, Xinyu Chen, Xiaoxi Zhu

No abstract is available for this record.

Zhongmiao Sun, Qi Xu, Jinrong Liu

Blockchain technology is very useful. This paper considers the application of blockchain technology to smart contracts, green certification, and market information disclosure, and introduces the carbon trading market price as a parameter to solve the dynamic incentive problem of the government for port enterprises to reduce emissions under the carbon trading policy. Based on the state change of port carbon emission reduction, this paper uses principal–agent theory to construct the dynamic incentive contract model of government without blockchain, with blockchain, and when carbon trading is considered under blockchain, respectively, and uses the optimal control method to solve and analyze the model. This paper finds that only when the opportunity cost of port enterprises is greater than a certain critical point and the fixed cost of blockchain is less than a certain critical point, the implementation of blockchain will help improve government efficiency. However, only when the critical value of carbon emission reduction of port enterprises and the unit operating cost of blockchain are small, the government should start the carbon trading market under blockchain technology. Through numerical simulation, this paper also finds that it is usually beneficial for the government to regulate and appropriately increase the carbon trading market price.

Meng Qin, Tong Wu, Xuecheng Ma, Lucian-Liviu Albu · 5 authors

No abstract is available for this record.

Hua Cheng, Farhad Taghizadeh–Hesary

No abstract is available for this record.

Zaghum Umar, Sun‐Yong Choi, Тамара Теплова, Tatiana V. Sokolova

Are green investments decoupled from the dirty investment such as the fossil fuel markets? We address this issue by extending the literature on environmental, social, and governance (ESG) assets by examining the dynamic relationship between fossil fuels and digital ESG assets proxied by green cryptocurrencies using the TVP-VAR(Time-varying parameter vector auto regression) spillover framework. Furthermore, we analyze the hedging attributes of green cryptocurrencies and fossil fuels in a minimum connectedness framework. The main findings are as follows: First, green cryptocurrencies are the main shock transmitters in all asset systems. Second, the dynamic connectedness between green cryptocurrencies and fossil fuels increased during the COVID-19 and Russia-Ukraine conflicts. Third, green cryptocurrencies have shown considerable hedging effectiveness against the fossil fuels. Our study has important implications for investors, regulators, and policy makers, such as shifting to green cryptocurrencies, regulation of carbon footprint, and promoting eco-friendly assets.

Sumaira Ashraf, António Almeida, Iram Naz, Rashid Latief

This study investigates the interconnectedness of the Islamic stock market, Bullion, and Bitcoin as diversifiers for portfolios, exploring their role as hedges and safe havens. The analysis covers the period from January 2015 to December 2022, with a particular focus on the influence of the COVID-19 pandemic and the Russia-Ukraine War on the MSCI World Islamic Index, bullions (Gold, Silver, Platinum, Nickel, Palladium, and Aluminium), and Bitcoin, employing a time-varying parameter vector autoregression (TVP-VAR) model. During crisis periods, our findings reveal that the transmission and reception of shocks among these assets varied, with a heightened level of co-movement observed during the pandemic and war periods. These results emphasise the importance of considering the dynamic nature of financial assets' connectedness in asset investment decisions, particularly in times of crisis. Furthermore, the findings suggest that Bullion can serve as a hedge for both Bitcoin and the Islamic stock market. The study also explores the optimal diversification of investment portfolios and highlights the importance of adhering to Islamic principles in portfolio diversification. By integrating Islamic rules into the diversification process, investors can enhance the effectiveness and relevance of their investment strategies.

Ardian Prasetianto, Iwan Kustiwan

Purpose — The main objective of this study is to analyze the influence of socioeconomic development and fiscal decentralization on environmental quality in Indonesia, as well as to identify causal relationships between them.Method — The data utilized in this study are secondary data collected over the period from 2010 to 2020. Data sources were obtained from the Ministry of Environment and Forestry, the Central Bureau of Statistics, the Ministry of Finance, and the World Bank. This study uses a quantitative approach in dynamic panel data analysis with a generalized method of moments (GMM) estimation analysis. The causal relationship between environmental quality and the research variables is analyzed using the Granger causality test.Result — The study's findings indicate the presence of the reverse of an Environmental Kuznet Curve (EKC) relationship between Gross Regional Domestic Product (GRDP) per capita and environmental quality. Environmental quality is influenced positively and significantly by various factors, including human development, expenditure on environmental functions, poverty, and the manufacturing industry. On the other hand, fiscal transfers and urbanization have a negative and significant effect on environmental quality.Contribution — A more comprehensive analysis of the impact of development achievements in Indonesia on environmental quality indicators is needed at the provincial government level, considering economic development, social development, and governance aspects. This study also classifies research results based on three regional classifications and includes GMM estimation analysis, which has not been widely done.

Sanjeev Kumar, Ritesh Patel, Najaf Iqbal, Mariya Gubareva

No abstract is available for this record.

Kai‐Hua Wang, Zu‐Shan Wang

No abstract is available for this record.

Ameena Arshad, Faisal Shahzad, Ijaz Ur Rehman, Bruno S. Sergi

No abstract is available for this record.

David Y. Aharon, Ender Demir, Oğuz Ersan

This study aims to identify the sources of spillovers affecting tourism tokens and classify the type of assets to which they correspond. Using daily data for different asset classes from June 2018 through November 2022, we employ a TVP-VAR methodology to test the connectedness between two tourism tokens, two leading travel equity indices, and the two dominant cryptocurrencies, namely, Bitcoin and Ethereum. The findings show that tourism tokens are relatively independent of fluctuations in the traditional sources affecting the travel and leisure sector, such as the U.S. dollar, the price of oil, or travel equity indices. These results hint that tourism tokens are more closely related to cryptocurrencies rather than pure travel goods. The results may help decision-makers in the travel and hospitality industries considering the use of tourism tokens identify the potential forces impacting them.

Muhammad Abubakr Naeem, Thi Thu Ha Nguyen, Sitara Karim, Brian M. Lucey

No abstract is available for this record.

Neeti Misra, Sumeet Gupta, Kawerinder Singh Sidhu, Anil Kumar · 10 authors

Green bonds have gained significant attention in supporting sustainable development goals for achieving sustainability. During the issuance of green bonds, there are a few concerns such as standardization, greenwashing, and lack of benefits that can be gained with green bonds. However, blockchain technology is a promising solution for green bond issuance because it has already shown its impact on different finance activities. This study aims to address and analyze the role and significance of green bond issuance for meeting sustainability with blockchain technology and also suggested recommendations for future research. Decentralized application based on the Algorand blockchain and high-level architecture proposed for the issuance of green bonds is at the primary level. There is no discussion regarding standardizing the environmental data, and the number of benefits gained by the green bond is not addressed in the previously published literature. From the analysis, it has been identified that a similar framework of blockchain cannot be implemented as the geographical and environmental parameters are quite different for every nation. So, every nation needs to customize the framework according to the nation's requirements. This study is the first attempt to combine information from previously published research about green bond issuance and integration of blockchain for green bond issuance, enlightening the disruption caused in the issuance of green.

Emon Kalyan Chowdhury, Mohammad Abdullah

No abstract is available for this record.

Kiryoung Lee, Juik Cho

No abstract is available for this record.

Spyros Papathanasiou, Dimitrios Vasiliou, Anastasios Magoutas, Drosos Koutsokostas

In view of the need for portfolio diversification, we investigate the interlinkages between a private equity ETF and a set of high-demand asset classes including bonds, equities, crude oil, gold, commodities, currency, Bitcoin, and shipping within a spillover framework. For this objective, we apply the enhanced modification of the Diebold and Yilmaz approach for the period 1 January 2010 to 31 January 2023. The empirical findings indicate a modest degree of connectedness among the investigated markets, whereas volatility spillovers showed acceleration during tumultuous periods. In addition, we assess the capacity of private equities for hedging, for the whole sample period and during COVID-19 infectious disease, in order to suggest investors for potential portfolio restructures. Results demonstrate that the short position in the volatility of private equity ETF can result in strong hedging effectiveness for investors holding long positions in Bitcoin, shipping, bonds, and crude oil. JEL Classification: C32, C58, G11, G15

Yunfei Yang, Jiamei Xiong, Lei Zhao, Xiaomei Wang · 6 authors

Cryptocurrency prices have the characteristic of high volatility, which has a specific resistance to cryptocurrency price prediction. Therefore, the appropriate cryptocurrency price predictive method can help reduce the investment risk of investors. In this study, we proposed a novel prediction method using a fractional grey model (FGM (1,1)) to predict the price of blockchain cryptocurrency. Specifically, this study established the FGM (1,1) through the closing price of three representative blockchain cryptocurrencies (Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC)). It adopted the PSO algorithm to optimize and obtain the optimal order of the model, thereby conducting prediction research on the price of blockchain cryptocurrency. To verify the predictive precision of the FGM (1,1), we mainly took MAPE, MAE, and RMSE as the judging criteria and compared the model’s predictive precision with the GM (1,1) through experiments. The research results indicate that within the data range studied, the predictive accuracy of the FGM (1,1) in the closing price of BTC, ETH, and LTC has reached a “highly accurate” level. Moreover, in contrast to the GM (1,1), the FGM (1,1) outperforms predictive capability in the experiments. This study provides a feasible new method for the price prediction of blockchain cryptocurrency. It has specific references and enlightenment for government departments, investors, and researchers in theory and practice.