Blockchain Papers

Dun Li, Dezhi Han, Zibin Zheng, Tien‐Hsiung Weng · 7 authors

No abstract is available for this record.

Eray Gemi̇ci̇, Müslüm Polat, Remzi Gök, Muhammad Asif Khan · 6 authors

In this paper, we examine the effect of explosive behaviors in the Bitcoin market on the top 10 largest stock markets of developed and emerging countries. The daily dataset, including the Dow Jones Industrial Index (DJIA), Nasdaq (NSQ), Shanghai Composite Index (SSE), Nikkei 225 (N225), Hang Seng Index (HSI), Shenzhen Composite Index (SZSE), Euronext Amsterdam Index (AEX), London Stock Exchange (LSE), Toronto Stock Exchange (TSX), and Bombay Stock Exchange (BSE), spans July 21, 2010, to December 9, 2022. We first investigate the existence of explosive price behaviors using the bubble detection test of Phillips and Shi and the results provide evidence of multiple bubble episodes, coinciding with the monetary policy actions of the FED and ECB. Then, we address the question of whether the explosive behaviors detected affect the variance of equity returns by employing a GARCH model. The impact is negative, albeit its magnitude and significance vary among stock indices.

Ziyang Yuan

In the past few decades, there has been an increasing demand for assets trading with help of machine learning. Contemporarily, the cryptocurrency and gold market has become prosperous with extremely dramatical fluctuations. This paper aims to study the trading price laws based on machine learning scenarios of Bitcoin and Gold to predict the price of the two currencies. To be specific, this study gives an inside view of the application of a method combined three algorithms (i.e., KNN, XGBoost and LightGBM) to predict the future Gold and Bitcoin price browser based on past data from 2017 to 2022. According to the analysis, the study shows the difference of three models, the accuracy of the combined algorithms and proves the related metrics to predict the price of the Gold and Bitcoin. Overall, these results give a guideline for the investor to make sensible decisions about Bitcoin and Gold price and shed light on guiding further exploration of price forecasting in terms of machine learning approaches.

Muhammad Umar, Fakhar Shahzad, Irfan Ullah, Tong Fanghua

No abstract is available for this record.

Zaghum Umar, Muhammad Usman, Sun‐Yong Choi, John Rice

No abstract is available for this record.

Feng Liu, Linlin Wang, Deli Kong, Shi Chen · 8 authors

Critics decry cryptocurrency mining as a huge waste of energy, while proponents insist on claiming that it is a green industry. Is Bitcoin mining really worth the energy it consumes? The high power consumption of cryptocurrency mining has become the latest global flashpoint. In this paper, we define the Mining Domestic Production (MDP) as a method to account for the final outcome of the Bitcoin mining industry's production activities in a certain period time, calculate the carbon emission per unit output value of the Bitcoin mining industry in China, and compare it with three other traditional industries. The results show that Bitcoin mining does not always have the highest when compared with others. The contribution of this paper is that we give a new perspective on thinking whether Bitcoin mining is more efficient to make more profit, in terms of the same amount of carbon emissions per unit compared to other industries. Moreover, it could even be argued that Bitcoin may present an opportunity for some developing countries to build out their electrical capacity and generate revenue.

Mohamad Husam Helmi, Abdurrahman Nazif Çatık, Coşkun Akdeni̇z

This study employs a non-linear framework to investigate the impacts of central bank digital currency (CBDC) news on the financial and cryptocurrency markets. The time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005) is estimated based on weekly data from the first week of January 2015 to the last week of December 2021. The vector of endogenous variables in the VAR estimation contains the Central Bank Digital Currency uncertainty index (CBDCU), cryptocurrency policy uncertainty index, S&P 500 index, VIX, and Bitcoin price. The TVP-VAR model’s time-varying responses demonstrated that the reactions of the cryptocurrency market to central bank digital currency announcements vary remarkably over time. The impacts of the CBDC shocks on the financial market have been increasingly visible during the COVID-19 pandemic. According to the time-varying forecast error decompositions, CBDCU and VIX shocks have accounted for most of the variance in cryptocurrency uncertainty and Bitcoin return shocks, notably during the COVID-19 period.

Nicholas Apergis

No abstract is available for this record.

Azza Béjaoui, Wajdi Frikha, Ahmed Jeribi, Aurelio F. Bariviera

This paper examines the dynamic connectedness between Gulf countries and BRICS stocks markets with a sample of cryptocurrencies, as well as two newly developed digital assets, namely NFT and DeFi, and Gold. The period under examination spans from January 2019 until September 2022. Our analysis is based on wavelet coherence, which is a suitable methodology considering the nonlinear dynamics present in data. Our empirical results clearly identify nontrivial time-varying connectedness between different assets and the stock markets. Asymmetric patterns in the interconnections of newly developed digital assets, cryptocurrencies, Gold and emerging market indices are well-documented, especially during the advent of the health and political events. Our empirical findings have relevant implications for portfolio managers, investors and researchers about portfolio allocation, investment strategies and potential diversification benefits of NFT and DeFi digital assets.

Bikramaditya Ghosh, Elie Bouri, Jung Bum Wee, Noshaba Zulfiqar

No abstract is available for this record.

Shijie Lin

This research document demonstrates the understanding of two key elements: Proof of Work (PoW) and Proof of Stake (PoS) within cryptocurrency. Cryptocurrency is often misunderstood as just volatile and risky but many investors do not understand what it even is. What is proof of work (BTC)? What is proof of stake (ETH)? How are they similar and how are they different? Cryptocurrency is actually more relatable that originally imagined once a person understands digital currency, money, it’s origins, and how they hold similar monetary value within their own wallets. Cryptocurrency in PoW involves complicated mathematical equation solving via mining from a large growing pool of miners. These miners receive rewards such as bitcoin/tokens/etc. from their mined hash blocks verified, and blocks added to the blockchain. Challenges are that there are many miners and there may be a computational limit per core of each PC to be able to mine since Bitcoin has increased its difficulty 70 billion times since it started. BTC or Bitcoin is still widely trusted due to its increasing difficulty to race to the finish line to finish the advanced math computations. Whereas within PoS this is not a race between the masses and advanced math computations, but a validator that generally has more put in their stake vs. gained by receiving the processing fees associated. ETH or Ethereum has shifted from PoW to PoS for its better energy efficiency in resources. It has employed many other additional checks from Casper to Gasper which is the combination of Casper (fork-choice algorithm), LMD-GHOST (heavest observed subtree), and finality which requires 2/3rd agreement as well as once a block is justified it is upgraded to a finalized block. the similarities between the two PoW and PoS are that they are consensus-driven algorithms. They are designed to reach an agreement between the systems in place before each block is placed in the blockchain. Additionally, they also have a shared public ledger that operates on a global if not international scale. With blockchains, there is always only one true version and this is relying on a network rather than a governing authority like a bank/government entity to provide security and to prevent fraudulent transactions. It is still widely contested which is better than these two well-known consensus algorithms and it is still widely contested. The best answer is suited on a per investor per business basis in terms of the willingness of taking a risk just like any investment. This document serves to help provide guidance in the understanding of cryptocurrency of two main consensus algorithms, its similarities, differences, and help identify see what a potential investor the reader may be.

Tarek Bouazizi

This article explores the complexities of cryptocurrency price volatility during times of crisis. We analyze time series data with long-term memory or long-range dependence to understand the impacts of crises on cryptocurrency prices. Specifically, we examine the effects of the Covid-19 pandemic and the Russo-Ukrainian war on cryptocurrency markets, as well as the role of investor sentiment in price fluctuations during periods of uncertainty. To do so, we use fractionally integrated models to analyze the short- and long-term effects of these external factors on cryptocurrency prices. Our study mainly focuses on Bitcoin returns volatility using specific fractionally integrated models during four sub-period of historical crises from 2014. It assesses and compares the fractionally integrated models of the GARCH, the FIGARCH-BBM, the FIGARCH-CHUNG, FIEGARCH, and the FIAPARCH-BBM during the sub-periods of the pre-Covid-19, of the Covid-19 situation, between the Covid-19 and the Russo-Ukrainian War, and of the Russo-Ukrainian War. Conditional volatility models' parameters are first estimated from the four sub-sample data series BTC/USD exchange rate returns and it is calculated. Estimated conditional volatilities are then compared to specific volatilities relying on information criteria, after which the models are ranked. Finally, we test the specifics fractionally integrated volatility models with the normality test, the Q-Statistics on Standardized Residuals Test, the ARCH Test, and the graphic analysis. The specific volatility model of the first sub-period pre-Covid-19 is FIAPARCH-BBM (2,1). BTC/USD returns evolution during the Covid-19 crisis indicates that the FIEGARCH (2,2) is the appropriate volatility model. In addition, our results find that the FIEGARCH (2,1) is the appropriate model of volatility over the third sub-period and during the Russo-Ukrainian War period. By extrapolating the results of the four events, the study showed that the series of BTC/USD returns sampled over the four sub-periods were not immune to risk leading to historical crisis situations. The fluctuations of Bitcoin data during a political or economic event influence the choice of volatility models and their coefficients. More specifically, the parameters of the determined models of conditional volatility show that a war will make cryptocurrency more important on the exchange market even than an epidemic in the example of Covid-19. Our results suggest that the pandemic and geopolitical tensions have had a significant impact on cryptocurrency prices, but investor sentiment has played a crucial role in exacerbating price volatility. Additionally, we demonstrate the effectiveness of fractionally integrated models in predicting cryptocurrency prices during times of crisis. In summary, this study provides important insights into the dynamics of cryptocurrency markets during global crises, highlighting the need for sophisticated modeling techniques to effectively capture the complexities of these markets.

Tanzeela Yaqoob, Hooria Akbar

This paper evaluated Bitcoin financial and economic behaviour by using the econometric model on Bitcoin rate of returns compared to the alternatives assets like precious metals, stock market, and exchange rate risk. The study employed the various Quantile Regression models to observe the hedging ability of Bitcoin under bearish and bullish scenarios. The daily data of China and the USA have been collected, from July 18, 2010, to August 31, 2021. The result indicates that under different market phenomena, Bitcoin holds hedge and safe-haven asset properties against precious metals such as gold, silver, and platinum. Bitcoin can be used as an alternative to money during the currency devaluation against the US Dollar since it holds a hedge and safe- haven properties against S&P 500 Index and SSEC Index. The study elaborates the several implications for investors portfolios. Finally, the study draws the attention of policymakers towards the legalisation of Bitcoin as a currency alternative considering its efficient performance under different economic conditions, supported by detailed theoretical and empirical analyses.

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.

Jiřı́ Málek, Duc Khuong Nguyen, Ahmet Şensoy, Quang Van Tran

No abstract is available for this record.

Hongjun Zeng, Ran Lu, Abdullahi D. Ahmed

Research background: In order to examine market uncertainty, the paper depicts broad patterns of risk and systematic exposure to global equity market shocks for the major South Asian and Chinese equity markets, as well as for specific assets (gold and Bitcoin). Purpose of the article: The purpose of this paper is to investigate the dynamic correlation among the major South Asian equity markets (India and Pakistan), the Chinese equity markets, the MSCI developed markets, Bitcoin, and gold markets. Methods: While applying the GARCH-Vine-Copula model and the TVP-VAR Connectedness approach, major patterns of dependency and interconnectedness between these markets are investigated. Findings & value added: We find that risk shocks from developed equity markets are critical in these dynamic links. A net return spillover from Bitcoin to the Chinese and Pakistani stock markets throughout the sample period is reported. Interestingly, gold can be applied to hedge and diversify positions in China and major South Asian markets, particularly following the COVID-19 outbreak. Our paper presents three main original add valued: (1) This paper adds global factors to the targeted study of risk transmission among South Asian and Chinese stock markets for the first time. (2)The assets of Bitcoin and gold were added to the study of risk transmission among South Asian and Chinese stock markets for the first time, enabling the research in this paper to observe the non-linear link among the South Asian and Chinese stock markets with them. (3) Our research adds to these lines of inquiry by giving empirical evidence on how COVID-19 altered the dependent structure and return spillover dynamics of Bitcoin, gold and South Asian and Chinese stock markets for the first time. Our results have critical implications for investors and policymakers to effectively understand the nature of market forces and develop risk-averse strategies.

M. Jabłczyńska, Krzysztof Kość, P Rys, Paweł Sakowski · 6 authors

The main aim of the study is to analyze BTC mining's efficiency under current market conditions (December 2021), including soaring energy prices produced from many different sources in different geographical locations. After a thorough analysis of initial assumptions concerning the (1) price of mining machine with associated components and its effective amortization period, (2) difficulty and the hash rate of the BTC network, (3) BTC transaction fees, and (4) energy costs from various sources, we have found that currently, BTC mining is not profitable, except for some rare cases. The main reason for this phenomenon is the fast and unpredictable increase of difficulty of the BTC network over time which results in decreasing participation of already purchased mining machines in the BTC network hash rate. The research is augmented with a detailed sensitivity analysis of mining efficiency to initial parameters assumptions, which allows observing that the conditions for BTC mining to be efficient and profitable are very challenging.

Onur Polat

This study examines the time-varying connectedness among the realized volatilities of seven major cryptocurrencies between January 2020 and May 2022. To this end, we implement the time and frequency connectedness time-varying parameter vector autoregression (TVP-VAR) approaches. Our findings propose that (i) the COVID-19 pandemic significantly affected the dynamic connectedness; (ii) the total connectedness index hits its apex around the official announcement of the pandemic; (iii) in line with previous studies Ethereum, Bitcoin, and Link are the largest propagators/recipients of shocks; (iv) the tightest volatility interdependencies are related to the short-run.

Masud Alam, Mohammad Ashraful Ferdous Chowdhury, Mohammad Abdullah, Mansur Masih

We investigate the return and volatility spillovers among NFTs, REITs, and other major financial assets from January 2019 to November 2022, using connectedness approaches. The findings indicate that total return and volatility connectedness increased during the COVID-19 and the Russia–Ukraine war. REITs partially maintained their historical independence from shocks from other assets, while NFTs emerged as the new portfolio diversifiers. Findings suggest that investors can use REITs or a combination of NFTs, OIL, GOLD, and REITs with other assets to hedge against volatile assets during periods of financial turmoil. These findings have significant implications for heterogeneous market participants aiming to identify optimal portfolio diversifiers.

Wajdi Frikha, Mariem Brahim, Ahmed Jeribi, Amine Lahiani

This paper aims to investigate the impacts of the COVID-19 pandemic and Russia-Ukraine war on the interconnectedness between the US and China stock markets, major cryptocurrency and commodity markets using the wavelet coherence approach over the period from January 1 2016 to April 18 2022. The aim is to understand how the COVID-19 pandemic and the Russia-Ukraine war have affected the hedging efficiency of volatile crypto-currencies and gold. Wavelet coherency analysis unveils perceptual differences between the short-term and longer-term market reactions. In the short-run, we find strong co-movements during the first and second waves of the pandemic. During the first wave, longer-term investors were driven by the belief of future pandemic demise. They make use of time diversification that results in positive returns. During the Russia-Ukraine war, S&P 500 leads Bitcoin, BNB, and Ripple whereas Ethereum leads S&P 500 and SSE.

Hanna Kołodziejczyk

This study investigates the diversifier, hedge and safe haven properties of stablecoins against various financial assets including cryptocurrencies such as Bitcoin, Ether, XRP and stock market indices. Using quantile coherency we show that stablecoins included in the study act as weak hedges in normal conditions and weak safe havens when considering moments of market turmoil and there is little evidence to support the existence of any contagion effects between the cryptocurrency and stablecoin markets. Aforementioned results are not significantly influenced by the choice of investment horizon. We further evaluate the implications of those results for the question of whether stablecoins are in fact stable.

Shoaib Ali, Imran Yousaf, Xuan Vinh Vo

Purpose This study examines the dynamics of the comovement and causal relationship between conventional (Bitcoin, Ethereum and Binance coin) and Islamic (OneGram, X8X token and HelloGold) cryptocurrencies. Design/methodology/approach This study uses wavelet coherence approach to examine the time-varying lead-lag relationship between conventional and Islamic cryptocurrencies. Furthermore, the authors use BEKK-GARCH model to estimate the optimal weights, hedge ratio and hedging effectiveness in pre-COVID-19 and during the COVID-19 period. Findings The authors find no significant comovement in pre-COVID-19. However, the authors find significant positive comovement in conventional and Islamic cryptocurrencies at the beginning of the pandemic, and in most cases, conventional cryptocurrencies are leading. X8X and HelloGold have no/weak correlation with conventional cryptocurrencies, implying that investors can diversify the risk by making an Islamic and conventional cryptocurrencies portfolio. The authors also calculate the optimal weights, hedge ratio and hedging effectiveness using the BEKK-GARCH model. Based on the optimal weights, for the portfolios of conventional–Islamic cryptocurrencies, investors are suggested to increase their investment in Islamic cryptocurrencies during the COVID-19 than normal period. The results of hedge ratios show that hedging costs are higher during COVID-19 than before. Practical implications The findings of the paper offer several practical policy implications for investors, portfolio manager, Shariah advisors and policymakers pertaining to asset allocation, risk management, forecasting and diversification. Specifically, investors can maximize the risk adjusted returns of their conventional cryptocurrencies portfolio by adding some portions of Islamic cryptocurrencies. Considering the comovement is time-varying, investors/manager should adjust their investment strategies frequently. For the entrepreneurs in crypto-industry, it is advised to introduce new Islamic cryptocurrencies, as it has a huge growth potential because of their distinct features and performance. Originality/value This is the first study that explores the linkages between conventional and Islamic cryptocurrencies, therefore this study extends the literature of Islamic finance, stablecoins and cryptocurrencies in pre-COVID-19 and during COVID-19 period. The study results provide insights to conventional crypto investor on how to manage their portfolio during normal and turbulent period.

Sheng Fang, Guangxi Cao, Paul Egan

No abstract is available for this record.