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Azhar Mohamad, Stavros Stavroyiannis
No abstract is available for this record.
Saeed Sazzad Jeris, A.S.M. Nayeem Ur Rahman Chowdhury, Mst. Taskia Akter, Shahriar Frances ¡ 5 authors
This study conducted a systematic review regarding the association between cryptocurrency and the stock market. This study used bibliometric and content analysis covering 151 articles from 2008 to November 2021. Using VOSviewer software, we explored the influential aspects of the literature, such as the prominent institutions, authors, countries, and journals. Additionally, we performed co-authorship, bibliographic coupling, and co-occurrence of keywords to understand the network. Furthermore, in the content analysis, we discussed key findings of four major research streams that we identified. Finally, we present seven research questions that can be explored in the future. The findings have a number of implications for the present state of the literature on cryptocurrency and the stock market, including study gaps and potential future research initiatives.
Manisha Shankarrao Ashtekar
<strong>Abstract</strong> The purpose of this article is to provide an outline of cryptocurrency's function in the global financial system. Another important goal of this essay is to understand the basic notion of digital money and to assess the potential of cryptocurrencies in the global financial system. This will be a descriptive study in which an attempt will be made to investigate the many benefits and applications of cryptocurrencies. Digital financial assets are cryptocurrencies for which ownership and transfers of ownership are guaranteed by a cryptographically decentralised system. The rise in the market value of cryptocurrencies, as well as their growing popularity around the world, has created a slew of commercial and industrial economic issues and worries. Acceptance as a kind of alternative currency, as well as the prohibition of any fraudulent use, should be vigorously encouraged.
Miklesh Prasad Yadav, Satish Kumar, Deepraj Mukherjee, Rao Ps
The present study is a novel attempt to unravel the connectedness of the green bond with energy, crypto, and carbon markets using the S&P green bond index (RSPGB). We consider MAC global solar energy index (RMGS) and ISE global wind energy index (RIGW) as proxies of the energy market and use bitcoin and the European energy exchange carbon index (REEX) for the cryptocurrency and carbon market. Employing the Diebold and Yilmaz (2012), BarunĂk and KrehlĂk (2018), and wavelet coherence econometric techniques, we find that the energy market (RMGS) has the highest connectedness derived from other asset classes, and bitcoin (RBTC) has the least connectedness. Concurrently, we find that the risk transmission is heterogeneous in different scales as the short period has less connectedness than the medium and long run. We conclude that the overall diversification opportunity among green bonds, energy stock, bitcoin, and the carbon market is more in the short-run than in the medium and long-run. In summary, our findings on the green bond market will provide investors, portfolio managers, and policymakers with critical insight into ensuring a sustainable financial market.
Imran Yousaf, Larisa Yarovaya
We examine the static and time-varying herding behavior in three cryptocurrency classes: âconventionalâ cryptocurrencies, non-fungible tokens, and DeFi assets during the most recent cryptocurrency bubble of 2021. While static herding analysis failed to demonstrate any evidence of herding, the time-varying herding has been identified in conventional cryptocurrencies and DeFi assets for the short investment horizons. The herding asymmetry analysis reveals that herding is not evident in conventional cryptocurrencies and NFT during up/down market, high/low volatility days, and high/low trading days. We only find herding in DeFi assets during the low volatility days.
Sina Fakharchian
Abstract Nowadays, the issue of fluctuations in the price of digital Bitcoin currency has a striking impact on the profit or loss of people, international relations, and trade. Accordingly, designing a model that can take into account the various significant factors for predicting the Bitcoin price with the highest accuracy is essential. Hence, the current paper presents several Bitcoin price prediction models based on Convolutional Neural Network (CNN) and Long-Short-Term Memory (LSTM) using market sentiment and multiple feature extraction. In the proposed models, several parameters, including Twitter data, news headlines, news content, Google Trends, Bitcoin-based stock, and finance, are employed based on deep learning to make a more accurate prediction. Besides, the proposed model analyzes the Valence Aware Dictionary and Sentiment Reasoner (VADER) sentiments to examine the latest news of the market and cryptocurrencies. According to the various inputs and analyses of this study, several effective feature selection methods, including mutual information regression, Linear Regression, correlation-based, and a combination of the feature selection models, are exploited to predict the price of Bitcoin. Finally, a careful comparison is made between the proposed models in terms of some performance criteria like Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Median Absolute Error (MedAE), and coefficient of determination (R 2 ). The obtained results indicate that the proposed hybrid model based on sentiments analysis and combined feature selection with MSE value of 0.001 and R 2 value of 0.98 provides better estimations with more minor errors regarding Bitcoin price. This proposed model can also be employed as an individual assistant for more informed trading decisions associated with Bitcoin.
Syed Aun R. Rizvi, Mohsin Ali
This study examines whether Islamic gold-backed cryptocurrencies (Onegram and X8X) provide any diversification benefits to the Islamic investors of Indonesia. We study the co-movements between return and volatility of cryptocurrencies and Indonesian Islamic equity indices during the pre-COVID-19 and COVID-19 periods. We employ Multivariate Generalized Autoregressive Conditional Heteroscedastic-Dynamic Conditional Correlation (M-GARCH-DCC) and Continuous Wavelet Transforms (CWT) for this study. We find that the COVID-19 crisis enhanced the spillover effect among the Islamic gold-backed cryptocurrencies and Islamic equities. We also provide evidence that Indonesian investors may invest in cryptocurrencies to minimize the equity sector risks during the pandemic. Our results bear significant implications for portfolio diversification strategies for Indonesian investors.
Michael Di, Ke Xu
No abstract is available for this record.
Bernice Nkrumah-Boadu, Peterson Owusu, AnokyeM Adam, Emmanuel AsafoâAdjei
The specific properties of assets such as cryptocurrencies, gold, and stocks have welcomed more empirical studies in assessing their nexus. As a result, market conditions, whether good or bad, become imperative to assess the benefits of safe have, hedges or diversification. Also, the presence of uncertainties in markets may have asymmetrical effects which make it necessary to assess their impact over time. The emergence of COVID-19 pandemic as a global uncertainty has altered the dynamics of most financial markets. Consequently, this may influence the lead/lag relationships in most financial time series at various frequencies to contribute to the heterogeneous nature of market participants. Hence, the study examines the interdependencies between cryptocurrencies, selected stocks markets of Africa, and Gold returns in a time-frequency domain before and during the COVID-19 pandemic. Using a day-to-day observations, from August 8th, 2015 to May 5th, 2020, we assess the benefits of portfolio diversification, hedges, and safe haven with the bi-wavelet technique. The findings reveal that gold and cryptocurrencies provide a safe haven, diversification and, hedge for investors of African stock especially in the Ghanaian stock market (short-term) and also during this COVID-19 period. These findings contribute to the literature on financial market interdependencies, asymmetries to demonstrate financial market participantsâ diverse investment horizons. Again, policymakers and governments of these stock markets should institute a sound system of controls in regulating stock markets. This will enable the benefits of safe haven, hedges or diversification to be efficiently realized for Gold and Cryptocurrencies during different market conditions.
Pradipta Kumar Sahoo, Badri Narayan Rath
This study explores the causal relationship between COVID-19 pandemic and Bitcoin returns by applying the time and frequency domain Granger causality framework. We find that COVID-19 has a causal effect on Bitcoin returns across time. We further find that the causal effect of COVID-19 on Bitcoin returns, varies across different frequencies from short to medium and long term. From a policy perspective, investors need to be alert while investing in Bitcoin.
Kokulo K. Lawuobahsumo, Bernardina Algieri, Leonardo Iania, Arturo Leccadito
We use a robust measure of non-linear dependence, the Gerber cross-correlation statistic, to study the cross-dependence between the returns on Bitcoin and a set of commodities, namely wheat, gold, platinum and crude oil WTI. The Gerber statistic enables us to obtain a more robust co-movement measure since it is neither affected by extremely large nor small movements that characterise financial time series; thus, it strips out noise from the data and allows us to capture effective co-movements between series when the movements are âsubstantialâ. Focusing on the period 2014â2022, we construct the bootstrapped confidence intervals for the Gerber statistic and test the null that all the Gerber cross-correlations up to lag kmax are zero. Our results indicate a low degree of dependence between Bitcoin and commodities prices, both when we consider contemporaneous correlation and when we employ correlations between current Bitcoin and lagged (one day, one week, or one month) commodities returns. Further, the cross-correlation between Bitcoin and commoditiesâ returns, although scanty, shows an increasing trend during periods of economic, health and financial turbulence. This increased cross-correlation of returns during hectic market periods could be due to the contagion effect of some markets by others, which could also explain the strong dependence across volatilities we detected. Based on our results, Bitcoin cannot be considered the ânew digital goldâ.
Hongjun Zeng, Abdullahi D. Ahmed
Purpose This paper aims to provide new perspectives on the integration of East Asian stock markets and the dynamic volatility transmission to the Bitcoin market utilising daily data from 2014 to 2020. Design/methodology/approach The authors undertake comprehensive analyses of the dependency dynamics, systemic risk and volatility spillover between major East Asian stock and Bitcoin markets. The authors employ a vine-copula-CoVaR framework and a VAR-BEKK-GARCH method with a Wald test. Findings (a) With exception of KS11 and N225; HSI and SSE; HSI and KS11, which have moderate dependence, dependencies among other markets are low. In terms of tail risk, the upper tail risk is more significant in capturing strong common variation. (b) Two-way and asymmetric risk spillover effects exist in all markets. The Hong Kong and Japanese stock markets have significant risk spillovers to other markets, and quite notably, the Chinese stock market is the largest recipient of systemic risk. However, the authors observe a more significant risk spillover from the Chinese stock market to the Bitcoin market. (c) The VAR-BEKK-GARCH results confirm that the Korean market is a significant emitter of volatility spillovers. The Bitcoin market does provide diversification benefits. Interestingly, the Chinese stock market has an intriguing relationship with Bitcoin. (d) An increase in spillovers in East Asia boosts spillovers to Bitcoin, but there is no intuitive effect of Bitcoin spillovers on East Asian spillovers. Originality/value For the first time, the authors examine the dynamic linkage between Bitcoin and the major East Asian stock markets.
ShuâHan Hsu
This paper examines and confirms the varying volatility of the relationship between cryptocurrency and currency markets at different time periods, such as when the market encountered multiple risk events including the USâChina trade war, COVID-19, and the RussianâUkraine war. We employ the Diagonal BEKK model and find that the co-volatility spillover effects between the returns of cryptocurrencies and currencies, with the exception of Tether and the U.S. dollar index, evolved significantly. Furthermore, the co-volatility spillover effects between cryptocurrencies and EUR have the largest effects and fluctuations. Large-cap cryptocurrencies (Bitcoin and Ethereum) have greater co-volatility spillover effects between them and currencies. Regarding the ability of cryptocurrencies to act as safe-haven for currencies, we observe that Bitcoin, Ethereum, and Tether served as safe-havens during the USâChina trade war, and Bitcoin was a safe-haven during COVID-19. During the 2022 RussianâUkraine war, Bitcoin and Tether were safe-havens. Interestingly, our findings point out that Bitcoin provides a more consistent safe-haven function for currency markets. Overall, by including multiple global risk events and a comprehensive dataset, the results support our conjecture (and earlier studies) indicating that the capabilities of cryptocurrency are time-varying and related to market status and risk events with different natures.
Kingstone Nyakurukwa, Yudhvir Seetharam
Abstract This study revisits stock market integration in Africa using an informationâtheoretic framework that quantifies the flow of information between exchanges. We use daily return data for seven MSCIâclassified African stock exchanges between 2011 and 2021. As Bitcoin has become an important asset class on the African continent, we also explore whether this cryptocurrency confers any diversification benefits. Our method holds that stock markets are integrated if there is a significant flow of information between exchanges. The results reveal a statistically insignificant flow of information among African stock exchanges, and for the few cases in which information flow is statistically significant, the magnitudes are low. South Africa is the most influential stock market, as it transmits most of the total transfer entropy (informational value) in the system. We also observe that African stock exchanges are weakly integrated with Bitcoin.
Hideaki Aoyama, Yoshi Fujiwara, Yoshimasa Hidaka, Yuichi Ikeda
Cryptoassets flow among players as recorded in the ledger of blockchain for all the transactions, comprising a network of players as nodes and flows as edges. The last decade, on the other hand, has witnessed repeating bubbles and crashes of the price of cryptoassets in exchange markets with fiat currencies and other cryptos. We study the relationship between these two important aspects of dynamics, one in the bubble/crash of price and the other in the daily network of crypto, by investigating Bitcoin and XRP. We focus on "regular players" who frequently appear on a weekly basis during a period of time including bubble/crash, and quantify each player's role with respect to outgoing and incoming flows by defining flow-weighted frequency. During the most significant period of one-year starting from the winter of 2017, we discovered the structure of three groups of players in the diagram of flow-weighted frequency, which is common to Bitcoin and XRP in spite of the different nature of the two cryptos. By examining the identity and business activity of some regular players in the case of Bitcoin, we can observe different roles of them, namely the players balancing surplus and deficit of cryptoassets (Bal-branch), those accumulating the cryptoassets (In-branch), and those reducing it (Out-branch). Using this information, we found that the regime switching among Bal-, In-, Out-branches was presumably brought about by the regular players who are not necessarily dominant and stable in the case of Bitcoin, while such players are simply absent in the case of XRP. We further discuss how one can understand the temporal transitions among the three branches.
Dimitrios Koutmos
No abstract is available for this record.
Cemal Zehir, Melike Zehir, Alex Borodin, Z. F. Mamedov ¡ 5 authors
Blockchain technology has emerging areas of deployment in diverse sectors and use cases. In this study, several potential application areas of blockchain with promising benefits have been identified in the natural gas industry. There is no single solution that can address different challenges and meet disparate requirements. Therefore, it is important to understand the needs of the natural gas industry and propose appropriate blockchain solutions. Moreover, in the literature, there is a lack of detailed case studies involving industrial experts from the natural gas sector. Expert opinion can be useful for prioritizing the most needed or expected blockchain application areas among several options. By considering privacy, authentication, speed, security, energy consumption, and costs, suitable blockchain types and consensus mechanisms can be determined. This study presents one of the first detailed case studies for tailored applications of blockchain in the natural gas industry. Through a two-staged semi-structured interview with executives from SOCAR Azerbaijan, the most important blockchain application areas and operational requirements were identified. Furthermore, the most suitable blockchain solutions that can address application-specific conditions and needs were determined. This study both, develops a replicable and reliable methodology to conduct detailed blockchain implementation case studies in the natural gas industry and various other sectors, and provides detailed insights into the primary application areas, operational expectationsârequirements, and implementation challenges specific to each application.
MĂźge SAÄLAM BEZGÄ°N, Selim GĂNGĂR
In this study, it was aimed to examine that the relationship between Bitcoin price, Bitcoin volume and bitcoin energy consumption, and to research leading indicators of Bitcoin and whether the stock markets of the 5 countries that produce the most Bitcoin act together. In this context, 2011-2022 monthly data of Bitcoin energy, Bitcoin price, Bitcoin volume, USA, China, Kazakhstan, Russia, and Canada indexes was regarded in the study. Diebold and Yilmaz (2012) spillover index and time varying parameter VAR (TVPVAR) methodologies were used in the study. In the result of Diebold and Yilmaz (2012) spillover methodology was observed that the spillover effect of the Bitcoin energy variable on the Bitcoin price is 3.5%. While was observed from leading indicators of Bitcoin to all series examined be spillover, the most spillover was observed that be from Bitcoin price to SP500 index. Net spillover index of Diebold and Yilmaz (2012) was calculated that is 4.54%. In addition to this, in the TVPVAR established model was examined the action and the reaction functions in 4, 8 and 12 months periods. In the action-reaction functions of the TVPVAR model, it was observed that the shocks at the 4, 8 and 12-month periods in Bitcoin energy prices spread with a similar intensity to the Bitcoin price. In the result of the study was observed that Bitcoin energy shocks spread to SP500, Shanghai, Kase and RTSI indexes in all periods, the shocks of the price and the volume shocks spread to these indexes in short periods.
Franklin Allen, Antonio FatĂĄs, Beatrice Weder di Mauro
We investigate whether the market for ICOs in 2017â2018 and 2021 showed signs of contagion from prices of Bitcoin and Ether. During phases of optimism, ICO daily returns display low correlations with those of Bitcoin or Ether. But when the bubble bursts, correlations jump to very high levels, signaling that the ICO market becomes a sideshow of the cryptocurrency dynamics. We demonstrate that this high correlation was not present during the Nasdaq bubble in the 1990s, signaling that the price dynamics of digital tokens seems to be driven by a common factor, much more than in previous bubbles.
Turhan Korkmaz, TuÄba Nur
Purpose: This paper aims to test the volatility models for Bitcoin (BTC) and the financial stress index (FSI) and examine the volatility spillover among them. This aim was reached by obtaining weekly data from the 7th of January 2011 and the 24th of December 2021. Methodology: First, volatility modelling for the series is provided, and GARCH (1,1) for the BTC series and IGARC (1,2) for the FSI series are determined as the most appropriate volatility models. Then, residual volatility series are created for each variable over the IGARCH (1,2) and GARCH (1,1) models for the volatility spread between the series. The volatility spread between the series is examined with the diagonal VECH GARCH method. It is concluded that there is a positive volatility spillover effect from the FSI variable to the BTC variable. Then, impulse-response analysis is performed on the volatility residual series created for each variable. The empirical findings from impulse response analysis support a risk transfer between BTC and FSI series. Results and Findings: Changes in the BTC return series and FSI series are caused mainly by themselves, and the series are most affected by their shocks. By comparing the variance decomposition of the volatility series with the analysis results, it can be said that the changes in the volatility series are caused mainly by each other.
Yu Yan, Yiming Lei, Yiming Wang
A monetary model is established to introduce that bitcoin does have the characteristics of a price rise when the economic situation is terrible under high risk aversion. At this time, Bitcoin has the property of a safe-haven asset, and when economic conditions are good and risk aversion is low, Bitcoin has a pro-cyclical nature. At this time, Bitcoin has a stronger property as a medium of exchange. To show the movement law of the bitcoin price, we make a logarithmic linearization of the model and simulation, and the result is consistent with the theoretical analysis. To better understand the role of bitcoin in the real economy, several standard portfolio models are used to measure the similarities and differences between gold and bitcoin in an investment portfolio. After the outbreak of COVID-19, bitcoin has shown stronger safe-haven asset properties.
Mahdi Ghaemi Asl, Oluwasegun B. Adekoya, Muhammad Mahdi Rashidi
No abstract is available for this record.
Yi Li, Wei Zhang, Andrew Urquhart, Pengfei Wang
No abstract is available for this record.
Zhilin Yao, Jingdan Su, Jingwen Hu
In this paper, we build an autoregressive integrated moving average (ARIMA) model and analyze the short-term trends of the gold price (GP) and bitcoin price (BCP) based on historical data. In addition, we use MATLAB to perform statistics and analysis on the data, find that the probability of continuous depreciation or appreciation after day 5 decreases exponentially, and find the maximum and minimum fluctuations. Further, we build a trading strategy model that uses the Apriori algorithm to calculate the number of subsets where prices have risen or fallen for 5 consecutive days. Finally, we perform a sensitivity analysis on the established model.