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2,964 results · page 76 of 124
Bao Doan, Huy Pham, Binh Nguyen Thanh
No abstract is available for this record.
Vaiva VasiliauskaitÄ, Fabrizio Lillo, Nino Antulov-Fantulin
We study the information dynamics between the largest Bitcoin exchange markets during the bubble in 2017-2018. By analysing high-frequency market-microstructure observables with different information theoretic measures for dynamical systems, we find temporal changes in information sharing across markets. In particular, we study the time-varying components of predictability, memory, and synchronous coupling, measured by transfer entropy, active information storage, and multi-information. By comparing these empirical findings with several models we argue that some results could relate to intra-market and inter-market regime shifts, and changes in direction of information flow between different market observables.
Ata Assaf, Husni Charif, Ender Demir
No abstract is available for this record.
Alessandra Cretarola, Gianna FigĂ âTalamanca, Cyril Grunspan
No abstract is available for this record.
Yianni Doumenis, Javad Izadi, Pradeep Dhamdhere, Epameinondas Katsikas · 5 authors
The purpose of this paper is to investigate the viability as compared with other financial assets of cryptocurrencies as a currency or as an asset investment. This paper also aims to see which macro variable relates more to the price of cryptocurrencies, especially Bitcoin. Since the whole concept of cryptocurrencies is quite novel, an attempt has been made to briefly explain the underlying blockchain technology that forms the bedrock of cryptocurrencies. In this study, we use secondary data, i.e., the price history of Bitcoin from September 2014 to September 2021 for the last seven years, captured from trading exchanges. We predicted monthly returns of Bitcoin with that of Standard & Poorâs 500 Index (S&P 500), gold, and Treasury Bonds. Our findings show that Bitcoin has very high volatility compared to S&P 500, Gold and Treasury Bonds. Also, our findings show that there is a positive correlation between Bitcoinâs price volatility and the other three financial assets before and during COVID-19. Hence, Bitcoin is acting more as a speculative asset rather than a steady store of value. This can be drawn from the comparison with the debt market i.e., a Treasury Bond that invests in long-dated (30 years) US treasuries with which Bitcoin shows no relationship. The findings of this study could help with understanding the future of Bitcoin. This has important implications for Bitcoin investors. The current study contributes to the extant literature by providing empirical evidence on long-term social sustainability vis-Ă -vis supply chain traceability.
Zvonko MerkaĆĄ, Vlasta RoĆĄka
The results of empirical analyses confirm that analysed unsystematic factors, the Stock-to-Flow index (S2F), and information on the Bitcoin (BTC) are directly correlated with BTC values. These results are expected and in line with the economic theory; however, this research paper aimed to investigate the impact of unsystematic factors on the value of decentralised virtual cryptocurrency BTC. Its aim was also to analyse the reasons for significant oscillations of market values in relation to the S2F and S2FX model and thus confirm the reliability of these models in the estimation of BTC value. The research further confirms the strong influence of non-technical information directly linked with the BTC. The limitations of this paper are the lack of possibilities for examining the impact of non-technical information affecting the Bitcoin price deviation regarding the S2F model. In addition to all mentioned limitations, the research results indicate the relevance of the S2F and S2FX models and show a strong impact of (half) the information on the value of cryptocurrencies.
Ulrich Gallersdörfer, Lena KlaaĂen, Christian Stoll
The energy consumption and related carbon emissions of cryptocurrencies such\nas Bitcoin are subject to extensive discussion in public, academia, and\nindustry. As cryptocurrencies continue their journey into mainstream finance,\nincentives to participate in the networks and consume energy to do so remain\nsignificant. First guidance on how to allocate the carbon footprint of the\nBitcoin network to single investors exist, however a holistic framework\ncapturing a wider range of cryptocurrencies and tokens remains absent. This\nwhite paper explores different approaches of how to allocate emissions caused\nby cryptocurrencies and tokens. Based on our analysis of the strengths and\nlimitations of potential approaches, we propose a framework that combines key\ndrivers of emissions in Proof of Work and Proof of Stake networks.\n
Noriyuki Kunimoto, Kazuhiko Kakamu
Using the asymmetric stochastic volatility model, this study investigates the day-of-the-week and holiday effects on the returns and volatility of Bitcoin from January 1, 2013 to August 31, 2019; in this context, we also discuss the characteristics of Bitcoin as a financial asset. The results of the estimation are threefold. First, the finding shows a small day-of-the week effect in volatility on Saturday and Sunday than in the rest of the week. Second, although the holiday effects are examined in active trading countries, namely Japan, China, Germany, and the United States, the positive post-holiday effect on the returns and weak positive pre-holiday effect on the volatility are only observed in the United States. Finally, the asymmetry effect is not observed. A comparison of Bitcoin to several assets such as stock, currency, and gold shows Bitcoin's positioning between stock, currency, and gold in relation to the week and holiday effects, its reaction to federal funds and medium of exchange characteristics, and the lack of asymmetry effect.
Zachary Ludwig, Patryk Perkowski
In this paper, I examine how social media affects cryptocurrencies and more traditional stocks. I use data on Twitter posts in combination with daily stock prices to estimate the causal effect of a tweet on stock and coin prices. To do this, I use a difference-indifference regression with index funds as my control group, which allows me to capture general market trends that coins and stocks would follow if not for intervention. I find that tweets have a significant impact on cryptocurrencies that last up to three days after the post. The increase in coin prices is driven by tweets from Tyler Winklevoss and tweets about Tezos and Ethereum specifically. Meanwhile, Twitter posts have no impact on more traditional stocks. These results suggest that social media can provide the public with valuable information in real time for fast moving and volatile crypto assets, while their effects on more stable and institutionalized traditional stocks are more muted.
Irfan Haider Shakri, Jaime Yong, Erwei Xiang
This paper investigates the relationship between the COVID-19 crisis and the two leading cryptocurrencies, Bitcoin and Ethereum, from 31 December 2019 to 18 August 2020. We also use an economic news sentiment index and financial market sentiment index to explore the possible mechanisms through which COVID-19 impacts cryptocurrency. We employ a VAR Granger Causality framework and Wavelet Coherence Analysis and find the cryptocurrency market was impacted in the early phase of the sample period through economic news and financial market sentiments, but this effect diminished after June 2020.
P. Srinivasan, Bipasha Maity, K K Saji Kumar
Bitcoins are evolving as a modern class of investment assets and it is crucial for investors to manage their investment risk. This paper examines the impact of macroeconomic-financial indicators on Bitcoin price using symmetric and asymmetric version of autoregressive distributed lag (ARDL) models with structural breaks. The asymmetric long-run association ascertained between Bitcoin prices and the macroeconomic-financial indicators is evident. Our empirical results indicate that the Bitcoin cannot be used to hedge against the inflation, Federal funds rate, stock markets and commodity markets. We further find that Bitcoin can be regarded as a hedging device for the oil prices. Our findings have significant implications for market participants who consider including alternate investment assets in their portfolios.
David Y. Aharon, Ender Demir
No abstract is available for this record.
Kirill Shilov, Andrey Zubarev
The cryptocurrency market debate resumed in 2020 with renewed vigour as the price of Bitcoin surpassed late 2017 highs. This study aims to analyse possible factors of Bitcoinâs pricing at various cryptocurrency market development stages â before the 2017 price bubble, after and during the COVID-19 pandemic. The main method of analysis is a generalized autoregressive conditional heteroskedasticity model with conditional generalized error distribution (GARCHGED). Two groups of indicators are used as possible factors related to the Bitcoin dynamics. The first group consists of various quantitative indicators directly related to Bitcoin (the so-called internal factors) â the volume of exchange trade, the volume of transactions in the Bitcoin blockchain, the number of new and active wallets, hash rate, the sum of fees paid in the blockchain, as well as the dynamics of Google Trends search queries. The second group is the return on various financial assets â stock and bond indexes, commodities, and currency markets. The results of the analysis demonstrate the absence of a stable correlation between any of the factors under consideration and Bitcoin returns in all the periods that we focus on. In the period before the 2017 price bubble, the internal factors and Bitcoin returns showed generally co-directional dynamics, but the situation changed in 2018. In early 2021, the correlation between Bitcoin and traditional financial assets returns has increased significantly. We can conclude that Bitcoin is becoming a popular means of diversification as a high-risk asset, which, however, follows the pattern of a speculative bubble at the beginning of 2021. The increased demand for the need to invest in Bitcoin using various exchange-traded instruments (ETFs for cryptocurrencies) may soon lead to a further increase in the price of this cryptocurrency if such instruments are registered on the exchange.
Hanan Naser
The pandemic of coronavirus (COVID-19) creates fear and uncertainty causing extraordinary disruption to financial markets and global economy. Witnessing the fastest selloff in the American stock market in history with a plunge of more than 28% in S&P 500 has increased the volatility of global financial market to exceed the level observed during the financial crisis of 2008. On the other hand, Bitcoin value has shown considerable stability in the last couple of months peaking at $10,367.53 in the mid of February 2020. In this context, the aim of this paper is to investigate the impact of COVID-19 numbers on Bitcoin price taking into consideration number of controlling variables including WTI-oil price, S&P 500 index, financial market volatility, gold prices, and economic policy uncertainty of the US. To do so, ARDL estimation has been applied using daily data from December 31, 2019 till May 20, 2020. Key findings reveal that the daily reported cases of new infections have a marginal positive impact on Bitcoin price in the long term. However, the indirect impact associated with the fear of COVID-19 pandemic via financial market stress cannot be neglected. Bitcoin can also serve as a hedging tool against the economic policy uncertainty in the long term. In the short run, while the returns of economic policy uncertainty have no impact on Bitcoin price, the growth in the new cases of COVID-19 infection and returns of financial market volatility have more positive significant impact on Bitcoin returns.
Barbara BÄdowska-SĂłjka, Agata Kliber, Aleksandra Rutkowska
We try to establish the commonalities and leadership in the cryptocurrency markets by examining the mutual information and lead-lag relationships between Bitcoin and other cryptocurrencies from January 2019 to June 2021. We examine the transfer entropy between volatility and liquidity of seven highly capitalized cryptocurrencies in order to determine the potential direction of information flow. We find that cryptocurrencies are strongly interrelated in returns and volatility but less in liquidity. We show that smaller and younger cryptocurrencies (such as Ripple's XRP or Litecoin) have started to affect the returns of Bitcoin since the beginning of the pandemic. Regarding liquidity, the results of the dynamic time warping algorithm also suggest that the position of Monero has increased. Those outcomes suggest the gradual increase in the role of privacy-oriented cryptocurrencies.
InĂ©s JimĂ©nez, AndrĂ©s MoraâValencia, Javier Perote
This paper establishes a brand-new perspective of analyzing the risk of crypto assets through a semi-nonparametric approach, discussing its theoretical advantages and testing its performance compared to parametric approaches and in terms of backtesting techniques and different risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. Our comprehensive analysis for six cryptocurrencies shows that flexible semi-nonparametric approaches outperform risk measures of most crypto assets (particularly Bitcoin) and tend to provide the most conservative risk assessment. Furthermore, we propose the Median Shortfall as a robust-to-outliers and reliable risk measure for cryptocurrencies and discuss on the choice of the appropriate probability levels according to the assumed distribution. The evidence supports that Median Shortfall at 98.31 % and 98.51 % confidence levels as accurate alternatives to Value-at-Risk at 99 % and Expected Shortfall at 97.5 %.
Sinan ErdoÄan, Maruf Yakubu Ahmed, Samuel Asumadu Sarkodie
Abstract When Bitcoin (BTC), the first pioneering cryptocurrency was released in 2009, it was considered as an apolitical currency. Besides, the possible effect of BTC and other cryptocurrencies on either financial markets or transactions has been widely discussed. However, the environmental effects of cryptocurrency demand have been ignored. Here, this study examines the nexus between cryptocurrencies and environmental degradation by employing standard and asymmetric causality methods. The Toda-Yamamoto and bootstrap-augmented Toda-Yamamoto test results reveal Bitcoin and Ethereum (ETH) excluding Ripple (XRP) have causal effects on environmental degradation. The Fourier-augmented Toda-Yamamoto test results show causal effects running from Bitcoin and Ripple to environmental degradation, whereas no causal effect runs from Ethereum to environmental degradation. The asymmetric causality shows causal effects from the positive shock of Bitcoin demand, negative shocks of Ripple and Ethereum demands to positive shocks of environmental degradation. Further discussions and policy implications are provided in the relevant sections of this study.
Stephanie Danielle Subramoney, Knowledge Chinhamu, Retius Chifurira
Risk management and prediction of market losses of cryptocurrencies are of notable value to risk managers, portfolio managers, financial market researchers and academics. One of the most common measures of an assetâs risk is Value-at-Risk (VaR). This paper evaluates and compares the performance of generalized autoregressive score (GAS) combined with heavy-tailed distributions, in estimating the VaR of two well-known cryptocurrenciesâ returns, namely Bitcoin returns and Ethereum returns. In this paper, we proposed a VaR model for Bitcoin and Ethereum returns, namely the GAS model combined with the generalized lambda distribution (GLD), referred to as the GAS-GLD model. The relative performance of the GAS-GLD models was compared to the models proposed by Troster et al. (2018), in other words, GAS models combined with asymmetric Laplace distribution (ALD), the asymmetric Studentâs t-distribution (AST) and the skew Studentâs t-distribution (SSTD). The Kupiec likelihood ratio test was used to assess the adequacy of the proposed models. The principal findings suggest that the GAS models with heavy-tailed innovation distributions are, in fact, appropriate for modelling cryptocurrency returns, with the GAS-GLD being the most adequate for the Bitcoin returns at various VaR levels, and both GAS-SSTD, GAS-ALD and GAS-GLD models being the most appropriate for the Ethereum returns at the VaR levels used in this study.
Yuzhi Cai, Thanaset Chevapatrakul, Danilo V. Mascia
Abstract We shed light on how the price explosivity characterising Bitcoin and other major cryptocurrencies is triggered, by employing the Quantile Self-Exciting Threshold Autoregressive (QSETAR) model. Our results for Bitcoin, Ripple, and Stellar reveal that the explosive behaviour originates from the extreme upper tails of the return distributions following a price increase in the preceding day. We do not find evidence of explositivity in the price of Litecoin.
Lee A. Smales
The cryptocurrency market has experienced stunning growth, with market value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, and stablecoins. Our results demonstrate that conditional correlations are time-varying, peaking during the COVID-19 pandemic sell-off of March 2020, and that both ARCH and GARCH effects play an important role in determining conditional volatility among cryptocurrencies. We find a bi-directional relationship for returns and long-term (GARCH) spillovers between BTC and ETH, but only a unidirectional short-term (ARCH) spillover effect from BTC to ETH. We also find spillovers from BTC and ETH to USDT, but no influence running in the other direction. Our results suggest that USDT does not currently play an important role in volatility transmission across cryptocurrency markets. We also demonstrate applications of our results to hedging and optimal portfolio construction.
Boubaker TOUIJRAT, Brahim Benaid, Hassane Bouzahir
This paper studied the mean and volatility transmission among Bitcoin as the most prominent cryptocurrency, exchange rates from developed countries/regions, and exchange rates from emerging countries/regions. Using daily returns between January 1, 2015, and December 31, 2018, and Bivariate VAR - Diagonal VECH models. The empirical results suggest there was no mean transmission between USD/EUR and USD/BTC. However, there was a unidirectional mean shock transmission link from USD/CNH, USD/MAD, and USD/IDR to USD/BTC. The results also suggested the existence of a bidirectional cross-volatility persistence link between bitcoin and all the exchange rates, except for USD/IDR and a bidirectional cross-volatility spillover link between USD/BTC and USD/CNH. A critical implication of these results is that they will be of use to investors, speculators, risk managers, and policymakers in understanding the degree of integration in terms of volatility and return among Bitcoin, currencies from developed, and currencies from emerging countries.
Walid Chkili, Aymen Ben Rejeb, Mongi Arfaoui
No abstract is available for this record.
Hatice Karahan
Cryptocurrencies are attracting considerable attention around the world because of the various advantages that they offer. On the other hand, they also carry some inherent risks. Although monetary authorities broadly agree that cryptocurrencies do not engender an immediate threat to national and global financial systems, the future is full of unknowns. In this regard, drawing a framework based on the current drivers of demand for cryptocurrencies would help visualize the prospects for these assets and create a roadmap to avoid or manage any disruptive risks. This discussion paper aims to contribute to the literature by examining the key factors that will determine the future performance of cryptocurrencies. The main conclusion derived from the discussion is that national regulations will potentially affect the direction of cryptocurrencies, as well as the need for any special efforts in the domain of monetary policy
Sunita Dasman
This study aims to explore the potential use of the cryptocurrency bitcoin as an investment instrument in Indonesia. The return obtained from bitcoin cryptocurrency is compared to other investment instruments, namely stock returns, gold and the rupiah exchange rate. The research period was carried out based on research data from 2011 to 2020. This study employee compares means test (t test) and analysis of variance (F test) on rate of return of bitcoin investment. The bitcoin return compare to the rate of return form the others investments instruments namely exchange rate, gold and stock. The study collected 120 data of each investments instruments: bitcoin, exchange rate, gold and stock from various of sources during 2011â2020. Then, we calculate the return and risk of individual investment instruments. The results showed that the bitcoin currency had the highest rate of return 18% with a standard deviation of 61% compared to exchange rate, gold and stock returns. While the rate of return for the others investment instruments showed less than 0.5% with standard deviation less than 5%. The rate of return bitcoin has significance difference compare to the rate of return of exchange rate, gold and stock. The study contribute for the investors who would like to invest on bitcoin. The investors should understand the characteristic of bitcoin in term of rate of returns and also the risk. This study also contributes to government of Indonesia on crypto currency development. The Indonesia government should adopt and regulate on crypto currency in the future to secure the investor and economic growth.