Blockchain Papers

Olaf Schlotmann, Stefan Ulreich, Inka Zippe

No abstract is available for this record.

Daniel Chappell

In response to Molnár and Thies (2018) demonstrating that the price data of Bitcoin contained structural breaks, we identify the optimal number of states for a Markov regime-switching (MRS) model to capture the regime heteroskedasticity of Bitcoin. We determined that the restricted 5-state MRS model provided the best goodness-of-fit scores (-AIC, -BIC, -HQIC) for the fitted sample. In addition, we found evidence of stylised characteristics in the price data of Bitcoin, namely: volatility clustering; volatility jumps; asymmetric volatility transitions; and the persistence of shocks.

Jasmina Smgic Miladinovic, Miladinovic, Jasmina Smgic

The appearance of cryptocurrency marks the arrival of a new unlimited global system with no intermediaries and costly intercontinental transactions. Digital money would make it possible for us to have significantly quicker and cheaper transactions, which, along with present technology, is considered inevitable in the future. This paper includes three topics and deals with the bitcoin phenomenon and its influence on economic growth. The paper presents the bitcoin technology, its advantages and some risks to which the system’s users are exposed. Bitcoin represents an exceptional technical achievement, and specific features of bitcoin present a particular challenge for its users.

Aleksandar Đorđević, Dordevic, Aleksandar

During the history there have been different examples of incorporating technology into economics. Some of them include SWIFT, e-banking, mobile payments, and many more. Technology had to be commercialized and put into service of facilitating economic processes. International finances underwent the process of development too. With the globalization process national economies became more interconnected and dependent from each other. Individuals demanded a faster and more convenient way to make international payments. Internet trade is on the rise, social media rule the contemporary world, and then appears the inception of so-called crypto currencies. The most famous is Bitcoin. Where lays its place in the economic science? It looks like that Bitcoin is going towards decentralization of the monetary system known by now. The goal of this paper is to raise the awareness of the changes happening in economy and in economic science.

Nico Abbatemarco, Leonardo Maria De Rossi, Gianluca Salviotti

A blockchain is, in its essence, an unchangeable, inviolable and transparent database distributed among a network’s participants. Far from simply representing the latest innovation in ICT, blockchain could serve as a foundation for the development of new business models. Indeed, its distributed nature opens the door to the creation of a new economy characterized by greater decentralization, transparency, security and privacy. The most well-known example of blockchain is the digital currency (or cryptocurrency) Bitcoin, which aims to revolutionize the world of payments as we know it today. The remarkable appreciation of Bitcoin's value over the years has been examined by numerous studies, most of which trying to determine what are the drivers influencing its price. This study is intended to provide some economic prospects for the future of blockchain technology, with specific reference to Bitcoin. In particular, this paper is focused on identifying the costs and revenues that the Bitcoin network supports in order to ensure its operativity. On the basis of the results emerging from this analysis, the paper addresses further considerations about the nature of cryptocurrencies and the future trend of their prices.

Ying Chen, Simon Trimborn, Jiejie Zhang

No abstract is available for this record.

Elizaveta Lebedeva

No abstract is available for this record.

Andreas Hanl

Cryptocurrencies such as Bitcoin might revolutionize the economy through enabling peer-to-peer based transactions by abolishing the need for a trusted intermediary. As for now, Bitcoin remains to be the best recognized cryptocurrency, in particular in terms of market capitalization. However, as this paper shows, there are plenty of alternatives. This paper outlines the historical roots which have led to the creation of privately emitted, cryptography based digital currencies. Additionally, this paper discusses future possible hurdles of the development of cryptocurrencies and outlines features which might influence the success of a cryptocurrency. Insights into the beginning of cryptocurrency development are gained by analysis of the publicly available DOACC dataset. The paper does so by providing an overview of the techniques and mechanisms used by cryptocurrencies. It shows that newly created cryptocurrencies tend to be very similar in some properties in the early stages but new features and more diversity developed in more recent years. Additionally, newly created cryptocurrencies tend more and more to create a fixed number of coins before the initial announcement in order to sell these in Initial Coin Offerings. Even when the amount of premining increases over years, it remains at lower levels on the aggregate.

Sofia Anyfantaki, Stelios Arvanitis, Nikolas Topaloglou

No abstract is available for this record.

Dominique Guégan, Marius Frunza

The aim of this research is to explore the econometric features of Bitcoin-USD rates. Various non-Gaussian models are fitted to daily returns in order to underline the unique characteristics of Bitcoin when compared to other more traditional currencies. Market efficiency hypothesis is tested further, and the main reasons for breaches in efficiency are discussed. The main goal of the paper is to assess the presence of bubble effects in this market with customized tests able to detect the timing of various bubbles. The results show that the Bitcoin prices had two episodes of rapid inflation in 2013 and 2017.

Efe Akinci, Jing Li

This paper studies Granger Causality relations between Bitcoin and 5 stock market indexes which are Japan, Russia, South Korea, Sweden and the United States. The time-period examined is from 2013 to 2017 and all the tests are conducted based on daily data. We analyze this in three different periods, last 5 years (2013-2017), in 2017 and last 3 months of 2017. To estimate the relationship, we use unit root test and Augmented Dickey-Fuller, Lagrange Multiplier, Johansen Cointegration Test and finally Granger Causality Test. After the tests, countries have a same integrated order that exhibits a long-run relationship. In causality, except for Russia, each country has affected the Bitcoin prices and being affected in a different period, especially in the last 3 months of 2017, the impact and popularity of Bitcoin affect too much the stock market in the short-run. As a result, the causation between Bitcoin and stock market indexes shows impact statistically significant in the 2017 year. The importance of cryptocurrency and popularity not as much as hype like late 2017 in 2018, but we think that cryptocurrencies are one of the major currencies that affect economical world very deeply.

Afees A. Salisu, Aviral Kumar Tiwari, Ibrahim D. Raheem

This study exploits several conditional heteroskedasticity models with various supported distributions in order to find the best distribution as well as the best GARCH-type model that may be used to model volatility of Bitcoin returns. Innovatively, the study is able to establish that pre-testing the residuals of Bitcoin returns for the best distribution can help to identify the appropriate distribution when modelling with GARCH-type models regardless of the data frequency.

Jamil Civitarese

No abstract is available for this record.

Yasar Kaya

In this paper, the price fluctuations of Bitcoin under speculative environment is studied. It has been seen that the market trend points out an existence of a speculative bubble. Over the course of the period from 2014 to 2018, the trend in price movements of bitcoin has proved to be strongly speculative. In that regard, investors might be curious about what drivers might be instrumental in these speculative price changes. After reviewing of NPV, it was seen that NPV is not applicable to the case of cryptocurrencies due to their nature and lack of free cash flows to base the asset valuation to some fundamental facts. Later, LPPL model is reviewed, however, that also proved to be insufficient since it does not reflect the investor speculations and inform much about price dynamics regarding behavioral finance principles. Then, some papers from the past price fluctuations of bitcoin (for the period from 2010 to 2013) was reviewed and three key variables were determined which might explain price movements. Public interest towards Bitcoin as interest-driven, regulatory and political news about cryptocurrencies as event-driven and VIX as overall investor approach to Bitcoin market have been taken. After running regressions, the only significant variable happened to be public interest and popularity of Bitcoin. Although, for some cases, VIX variable also explain price fluctuations for some intervals, in none of the cases event-driven variable has long- terms effect on price fluctuations under speculative environment. Lastly, a robustness test is also handled considering the “weekend effect” and it has been seen public interest variable again proved to be a significant price determinant.

Thanos Andrikopoulos, Robert Hudson, Saeed Akbar, Darius Saftoiu

No abstract is available for this record.

Christian Masiak, Joern Block, Tobias Masiak, Matthias Neuenkirch · 5 authors

We apply time series analysis to investigate the market cycles of Initial Coin Offerings (ICOs) as well as bitcoin and Ether. Our results show that shocks to ICO volumes are persistent and that shocks in bitcoin and Ether prices have a substantial and positive effect on these volumes – with the effect of bitcoin shocks being of shorter duration than that of Ether shocks. Moreover, higher ICO volumes cause lower bitcoin and Ether prices. Finally, bitcoin shocks positively influence Ether but not the other way round. Our study has implications for financial practice, in particular for cryptocurrency investors and entrepreneurial firms conducting ICOs.

Min Luo, Vasileios E. Kontosakos, Athanasios A. Pantelous, Jian Zhou

No abstract is available for this record.

Jamil Civitarese

Metcalfe's Law argues the value of a network is proportional to the square of its users. Bitcoin and other cryptocurrencies can be modeled as such: if Metcalfe's Law is true, then it is possible to forecast prices using the size of the network. I test this assertion by a cointegration test between price and an adjusted number of wallets' connections. It is stated that the series do not cointegrate, rejecting the Metcalfe's Law. A first-differences model is employed to further analyse the relation between returns and variations in the number of wallets. It is stated that Metcalfe's Law consistently predicts the trend in the value of Bitcoin; nevertheless, it is not possible to reject the reverse causation of Bitcoin returns leading to new wallets.

Manas Gupta, Parth Gupta

No abstract is available for this record.

Jesús Fernández‐Villaverde

Abstract This article reviews what cryptocurrencies are, and it frames them within the context of historical monetary experiences and contemporary monetary economics. The article argues that, as pure fiduciary private money, cryptocurrencies are a bubble without a fundamental value and they will not provide, in general, optimal amounts of money or deliver price stability. Nevertheless, cryptocurrencies can play a role in improving the current means of payments and in disciplining central banks into providing better government‐run fiduciary monies.

Alessandra Cretarola, Gianna Figà‐Talamanca, Marco Patacca

No abstract is available for this record.

Kee-Youn Kang, Seungduck Lee

No abstract is available for this record.

Kamwoo Lee, Sinan Ulkuatam, Peter A. Beling, William T. Scherer

In this paper, we present a novel method to predict Bitcoin price movement utilizing inverse reinforcement learning (IRL) and agent-based modeling (ABM). Our approach consists of predicting the price through reproducing synthetic yet realistic behaviors of rational agents in a simulated market, instead of estimating relationships between the price and price-related factors. IRL provides a systematic way to find the behavioral rules of each agent from Blockchain data by framing the trading behavior estimation as a problem of recovering motivations from observed behavior and generating rules consistent with these motivations. Once the rules are recovered, an agent-based model creates hypothetical interactions between the recovered behavioral rules, discovering equilibrium prices as emergent features through matching the supply and demand of Bitcoin. One distinct aspect of our approach with ABM is that while conventional approaches manually design individual rules, our agents' rules are channeled from IRL. Our experimental results show that the proposed method can predict short-term market price while outlining overall market trend.

Michael S. Pagano, John Sedunov

No abstract is available for this record.