Blockchain Papers

Erdoğan Teyyare, Kadir Ayyıldırım

No abstract is available for this record.

Awadhesh Pratap Singh, Vikrant Kulkarni

The purpose of this study is to perform a systematic literature review on Bitcoin and unveil its upsides, downside and divergent views from previous studies. The paper presents a systematic literature review of key studies published on Bitcoin between 2008 and 2019. The focus is given to three topics: benefits of Bitcoin; its shortcomings; and divergent views presented by previous cryptocurrency scholars in details. The results indicate that Bitcoin offers four key benefits—its acceptance as a digital currency, effective portfolio diversifier, hedging capabilities and higher security. Literature review revealed five major shortcomings of Bitcoin—weak substitute for traditional currency, higher volatility, idiosyncratic risks, uncertain regulatory impact and its exogenous supply. Finally, the review reveals three major areas wherein cryptocurrency scholars found to have divergent view—acceptance of its hedging capabilities across regions and portfolios, consensus on Bitcoin as highly secured and safe asset and, general acceptance of Bitcoin as a substitute of traditional currencies.

Bernd Süßmuth

No abstract is available for this record.

Walid Mensi, Shawkat Hammoudeh, Aviral Kumar Tiwari, Khamis Hamed Al‐Yahyaee

This paper examines the left and right tail dependence-switching structure between twelve MENA stock markets, and oil and other major global factors. We compare the MENA–oil tail dependence with that of Bitcoin, gold, and VIX. Using a recent combined wavelet and dependence-switching copula approach, we show evidence of significant tail dependence between MENA stock markets and oil and the other global factors. The dependence structure varies across the associated different regimes and under both the short- and long-term horizons. Moreover, the safe haven role of gold is more apparent in the long term than in the short term for all MENA markets, and this result is similar for Bitcoin but is less evident for VIX. We conclude by providing policy implications.

Andy Cheng

One of the important tasks of every multi-asset portfolio managers is to assess how different asset classes interact with each other. Historical findings indicate that tradition risk asset classes exhibited various degrees of correlation, be they positive or negative, among each other. With the raise of crypto assets, such as bitcoin, it appears that crypto assets have gradually been considering as new investment class, at least from institutional aspect. This study reveals that the correlation of the digital currency with the longest price history, bitcoin, with other traditional assets is close to zero. Thus, from diversification point of view, this makes cryptocurrencies or bitcoin a perfectly uncorrelated asset which would benefit almost any portfolio. Further study is performed to investigate the cointegration relations among bitcoin and other asset classes. It is found that the spreads between bitcoin and some major tradition risk asset classes exist a mean reversion phenomenon. This enables asset managers to develop quantitative approaches for active management strategies. Models of cointegrated time series are common place in the literature and application in financial series. Correlation and cointegration are time series modelling techniques that have applied to financial markets. They are related but with different concepts. Correlation indicates co-movements in returns which is a short run measure requires frequent rebalancing to minimize losses, while cointegration measures long run tandem movements in prices to ensure long term performance for achieving returns. Two pairs of asset prices are found to have a common stochastic trend with stationary cointegrating vector, they are in theory considered for cointegration. This stochastic process displays a mean reversion in long run. If there exists a divergence in spread due to temporary shocks, one can expects to profit from performing pairs trading strategy by creating a short position on the outperforming one, at the same time with a long position on the underperforming one. In this study, trading signal would be generated for our pairs trading with bitcoin. Largely, our results empirically support over various asset classes during the period of estimation.

Dirk G. Baur, Kislay Kumar Jha

No abstract is available for this record.

Jacopo De Stefani, Olivier Caelen, Dalila Hattab, Yann‐Aël Le Borgne · 5 authors

No abstract is available for this record.

Cem Kartal, Mehmet Bayramoğlu

No abstract is available for this record.

Mawuli Segnon, Stelios Bekiros

In this paper, we revisit the stylized facts of cryptocurrency markets and propose various approaches for modeling the dynamics governing the mean and variance processes. We first provide the statistical properties of our proposed models and study in detail their forecasting performance and adequacy by means of point and density forecasts. We adopt two loss functions and the model confidence set (MSC) test to evaluate the predictive ability of the models and the likelihood ratio test to assess their adequacy. Our results confirm that cryptocurrency markets are characterized by regime shifting, long memory and multifractality. We find that the Markov switching multifractal (MSM) and FIGARCH models outperform other GARCH-type models in forecasting bitcoin returns volatility. Furthermore, combined forecasts improve upon forecasts from individual models.

Yang Hu, Yang Hou, Les Oxley

No abstract is available for this record.

Jackie Johnson

An analyse of bolivar/bitcoin trading activity indicates that Bitcoin trading in Venezuela is more a reflection of a survival technique rather than an investment strategy with the median transactions price significantly smaller than the medians in the Argentine peso, the Brazilian real and the UK pound. A large number of very small trades point to the practice of exchanging only as many bitcoins as is necessary for immediate use, with inflation as high as 3-4%/day. An analysis of the size of transactions in bitcoins also points to much smaller bitcoin transactions in the bolivar compared to the peso, real and pound. While Bitcoin transactions in the real and the pound indicate a range of trading opportunities from small to large transactions, peso/bitcoin transactions indicate a currency that may be at the start of a journey not dissimilar to the bolivar as transactions start to get smaller in 2018. This analysis supports the anecdotal evidence that bolivar/bitcoin trading is used as a survival technique in a country with a failing economy and worthless fiat currency

Marc Gronwald

This paper deals with cryptocurrency bubbles. First, it points out that a number of recent papers on cryptocurrency bubbles are awed due to an insufficient consideration of the fundamental value of cryptocurrencies. As even fiat money is said to exhibit features of bubbles, the same applies to cryptocurrencies. Thus, any empirical investigation into either the presence of cryptocurrency bubbles or the fundamental value of cryptocurrencies is needless. Second, the paper conducts a short empirical analysis into the relationship of the prices of Etherum and Bitcoin. Evidence of explosive periods is found in the price of Etherum even if this price is expressed in terms of Bitcoin rather than US Dollars. These periods, however, are found to be in the first half of 2016 and 2017, respectively, but not during the price peak period of Bitcoin witnessed end of 2017 and beginning of 2018.

Yuecheng Jia, Yangru Wu, Shu Yan, Chen-xi Yin

No abstract is available for this record.

Edward Lehner, John R. Ziegler, Louis Carter

This chapter builds on the body of work that has depicted cryptocurrency as a model for science and higher education funding. To that end, this work examines the degree to which one or more cryptocurrencies would need to be adopted and achieve a network effect prior to implementation of such a funding model. Empirical data from three different cryptocurrencies were examined. The current work deploys generalized autoregressive conditional heteroskedasticity (GARCH) to analyze stochastic volatility. This work contends that the examined coins are likely overdistributed and too volatile, thereby limiting the wealth generation possibilities for funding science or higher education. Additionally, based on the GARCH analysis, this work highlights that cryptocurrency pricing metrics and valuation models, to this point, may be insufficiently complex to persuade institutional investors to seriously allocate capital to this ecosphere.

M. Kamisli, S. Kamisli, Fatih Temi̇zel

No abstract is available for this record.

Don M. Autore, Nicholas Clarke, Danling Jiang

No abstract is available for this record.

Anwar Hasan Abdullah Othman, Syed Musa Alhabshi, Razali Haron

This study investigates whether symmetric and asymmetric volatility effects are persisted in the daily return series of Bitcoin currency compared to the gold and fiat money system using GARCH family models. The symmetric analysis shows that the three monetary systems exhibit time-varying volatility with high persistence and predictability behaviour whereas asymmetric analysis indicates that Bitcoin currency and gold are not significantly respond to asymmetric information effects in the financial markets however, the US dollar index is affected by the positive shocks. This suggesting Bitcoin and gold have the capability for hedging or safe-haven assets against market risk specifically during times of economic turmoil. Evidence suggests that cryptocurrency is a potential alternative to current fiat money system, offering benefit for policy makers and a good investment option for positional investors in terms of hedging, portfolio diversification strategy and risk management.

Arzu Tay Bayramoğlu, Çağatay Başarır

No abstract is available for this record.

Craig E. Landry, Dylan Turner, Jeffrey H. Dorfman

No abstract is available for this record.

Maximilian-Benedikt Koehn, Andrejs Cekuls

In 2008 a group of programmers, alias Satoshi Nakamoto, introduced bitcoin. Bitcoin is a cryptocurrency
\nor virtual money derived from mathematical cryptography and is conceived as an alternative to government authorised
\ncurrency. The founder anticipated, through bitcoin’s construction and his digital mining processes, that bitcoin prices
\nwould be relatively stable. However, the recent bitcoin price decline proves that bitcoin is extraordinarily volatile and is
\nnot that stable as hoped. Although some scientists have already shown that the fundamental value of bitcoin is zero, the
\nprice of bitcoin has reached over 19.000$ in December 2018. Since then, bitcoin prices dropped nearly 70% from their
\npeak value and showed in addition to that the typical trends of a speculative bubble.
\nHyman Minsky and Charles Kindleberger discussed three different patterns of speculative bubbles. One is when price
\nrises in an accelerating way and then crashes very sharply after reaching its peak. Another is when the price rises and is
\nfollowed by a more similar decline after reaching its peak. The third is when the price rises to a peak, which is then
\nfollowed by a period of gradual decline known as the period of financial distress, to be followed by a much sharper crash
\nat some later time. One of the key findings of this study is that all these three patterns occurred during 2017-18 for the
\nbitcoin price.
\nTherefore, the purpose of this paper is to analyse the historical bitcoin prices in context with the typical five-step
\ncharacteristics of a speculative bubble. Furthermore, each phase of a speculative bubble is explained by a behavioural
\nfinance approach and answer the price development of this cryptocurrency. The result is frightening, bitcoin can be seen
\nas a perfect textbook example of a speculative bubble.

Serdar Erdoğan, Volkan Dayan

No abstract is available for this record.

Aleš Zamuda, Vincenzo Crescimanna, Juan C. Burguillo, Joana Dias · 12 authors

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this problem-solving metric perspective, i.e., as technical analysis, forecasting, and estimation using a standardized ledger-based technology. The envisioned tools based on forecasting are then suggested, i.e., ranking Initial Coin Offering (ICO) values for incoming cryptocurrencies, trading strategies employing the new Sentiment Analysis metrics, and risk aversion in cryptocurrencies trading through a multi-objective portfolio selection. Our perspective is rationalized on the perspective on elastic demand of computational resources for cloud infrastructures.

Agata Kliber, Katarzyna Włosik

The aim of this research is to investigate interdependencies between leading cryptocurrency exchanges (American, European and Japanese ones). We examine price and volume spillovers of daily frequency, to answer the question whether these platforms are integrated one with another or whether they form different isolated clusters. The results show that the big exchanges are indeed closely linked one to another. However, the magnitude of spillovers is higher in the case of prices, compared to volume. We also find that the analysed markets react with the same intensity to the price shocks coming from the other markets as to their own shocks. They are, however, more isolated in terms of volume spillovers.

Angelika Kokkinaki, Svetlana Sapuric, Ifigenia Georgiou

No abstract is available for this record.