Blockchain Papers

Dan Gabriel Anghel

No abstract is available for this record.

Esra Alp, Chi Keung Marco Lau, Hakan Kahyaoğlu

No abstract is available for this record.

Pankaj Pandey, Sokratis Katsikas

No abstract is available for this record.

Alessandra Amendola, Luca Sensini

The analysis of cryptocurrencies market behaviour is receiving significant attention from researchers and practitioners in the last decades. This paper aims at contributes to volatility estimations of the cryptocurrencies helping to highlight the main stylized facts and characteristics. The performance of different specifications of volatility modelling, within the GARCH class, have been compared through the Model Confidence Set (MCS) over four of the most capitalised cryptocurrencies, namely Bitcoin, Ethereum, Stellar and Ripple. Our empirical findings give evidence of strong asymmetric effects in cryptocurrencies volatility leading to a better performance of asymmetric GARCH specifications..

Yaman Ö. Erzurumlu, Tunc Oygur, Alper Kirik

Purpose Considering the different motivation for the creation of each of these cryptocurrencies, the purpose of this paper is to examine whether there is a dominant external factor in the cryptocurrency world. Using a novel two-step time and frequency independent methodology, the authors examine a large scope of cryptocurrencies and external factors within the same period, and analytical framework. Design/methodology/approach The examined cryptocurrencies are Bitcoin, Ethereum, Ripple, Litecoin, Monero and Dash. In total, 18 external factors from 5 factor families are selected based on the mining motivation of these cryptocurrencies. The study first examines discrete wavelet transform-based (WTB) correlations, reduce the dimension and focuson relevant pairs. Selected pairs are further examined by wavelet coherence to capture the intermittent nature of the relationships allowing the most needed “Flexibility of frequency and time domains”. Findings Each coin appears to operate as a unique character with the exception of Bitcoin and Litecoin. There is no prominent external driver. The cryptocurrency market is not a clear substitute for a specific factor or market. Two-step WTB filtered wavelet coherence analysis help us to analyze a large number of factor without the loss of focus. The co-movements within the cryptocurrencies spillover from Ethereum to altcoins and later to Bitcoin. Originality/value The study presents one of the first examples of two-step WTB filtered wavelet coherence analysis. The methodology suggests an approach for simultaneous examination of large number of variables. The scope of the study provides a rather holistic view of the co-movements of external factors and major cryptocurrencies.

Emna Mnif, Anis Jarboui, Khaireddine Mouakhar

No abstract is available for this record.

Xingzhi Qiao, Huiming Zhu, Liya Hau

No abstract is available for this record.

Pierre Venter, Eben Maré

In this paper, the pricing performance of the generalised autoregressive conditional heteroskedasticity (GARCH) option pricing model is tested when applied to Bitcoin (BTCUSD). In addition, implied volatility indices (30, 60-and 90-days) of BTCUSD and the Cyptocurrency Index (CRIX) are generated by making use of the symmetric GARCH option pricing model. The results indicate that the GARCH option pricing model produces accurate European option prices when compared to market prices and that the BTCUSD and CRIX implied volatility indices are similar when compared, this is consistent with expectations because BTCUSD is highly weighted when calculating the CRIX. Furthermore, the term structure of volatility indices indicate that short-term volatility (30 days) is generally lower when compared to longer maturities. Furthermore, short-term volatility tends to increase to higher levels when compared to 60 and 90 day volatility when large jumps occur in the underlying asset.

Liang Wu, Shujuan Chen

The long memory is usually defined via auto-covariances which further connect with Hurst exponent. The heavy tails in Bitcoin returns can cause infinite auto-covariances which make the analysis of long memory and market efficiency in Bitcoin based on estimation of Hurst exponent inappropriate. Few literatures focus on this problem. We provide two approaches based on shuffling method and rank-ordered technique to this problem, and further combine them to analyse the time-varying efficiency and long memory in Bitcoin using sliding window. Results show that the inefficiency and long memory exist in Bitcoin before 2014 and after mid-2017. Especially, the latest data reveal a recent new change that the Bitcoin market has become inefficient and exhibited long memory behaviour since mid-2017, but is turning back to efficiency recently. This change may be due to the frequent key events of Bitcoin in 2017 and 2018, which can break the weak efficiency of Bitcoin. The heavy negative tails with α<2 before September 2016 validate the necessity of our analysis under heavy tails. Besides, the change trend and exact sub-periods of efficiency and long memory are first obtained via empirical mode decomposition of Hurst exponent estimates.

Di Lan, George Xianzhi Yuan, Tu Zeng

The equity and currency tokens are typically two kinds of initial coin offerings (ICOs) like Bitcoin or Ethereum based on the platform of Blockchains to provide a particular product or service, it is very important to study the mechanism of Blockchain Ecosystems. The goal of this paper is to explain the stable in the sense for the existence of consensus equilibria for mining gap games by using one new concept called ‘consensus games (CG)’ under the framework of Blockchain Ecosystems which mainly mean the economic activities by taking into the account of three types of different factors which are expenses, reward mechanism and mining power for the work on blockschain by applying consensuses including the ‘Proof of Work’ due to Nakamoto in 2008 as a special case.

Toan Luu Duc Huynh, Muhammad Shahbaz, Muhammad Ali Nasir, Subhan Ullah

Abstract This paper empirically investigates whether cryptocurrencies might have a useful role in financial modelling and risk management in the energy markets. To do so, the causal relationship between movements on the energy markets (specifically the price of crude oil) and the value of cryptocurrencies is analysed by drawing on daily data from April 2013 to April 2019. We find that shocks to the US and European crude oil indices are strongly connected to the movements of most cryptocurrencies. Applying a non-parametric statistic, Transferring Entropy (an econophysics technique measuring information flow), we find that some cryptocurrencies (XEM, DOGE, VTC, XLM, USDT, XRP) can be used for hedging and portfolio diversification. Furthermore, the results reveal that the European crude oil index is a source of shocks on the cryptocurrency market while the US oil index appears to be a receiver of shocks.

Marc Gronwald

No abstract is available for this record.

Paolo Giudici, Iman Abu Hashish

Abstract The objective of this work is to understand the dynamics of cryptocurrency prices. Specifically, how prices switch between different regimes, going from “bull” to “stable” and “bear” times. For this purpose, we propose a hidden Markov model that aims at explaining the evolution of Bitcoin prices through different, unobserved states. The implementation of the proposed model includes a likelihood ratio test that allows to compare models with different states and with different covariance structures. Our empirical findings show that the time movements of Bitcoin prices across different exchange markets are well‐described by the proposed model. In particular, a parsimonious model with a diagonal covariance matrix leads to better predictions, compared with a model with a full covariance matrix.

Hà Thanh Nguyễn, Bin Liu, Nirav Y. Parikh

No abstract is available for this record.

Mawuli Segnon, Stelios Bekiros

No abstract is available for this record.

Seyed Alireza Manavi, Gholamreza Jafari, S. Rouhani, Marcel Ausloos

No abstract is available for this record.

Марина Малкина, V.N. Ovchinnikov

We studied the specific properties of the cryptocurrency market. Guided by the concept of implied volatility, we investigated the asymmetric reaction of the market to news. Based on the concept of realized volatility, we verified the hypothesis of herding behavior in the market. To test the properties of the market, we used a combination of methods, starting from the analysis of statistics of search queries, interpreted as proxies of information demand from professional market participants and the “wide crowd”, and ending with advanced Markov-Switching GARCH models and heterogeneous autoregressive models of realized volatility (HAR-RV-J-models). As a result, we found various types of asymmetric reactions of the cryptocurrency market to news related to both the general direction of its dynamics (growth or decrease) and the amplitude of return fluctuations (high or low volatility). During the upward price rally and overheating of the market, investors deliberately avoided the bad news; thereby the asymmetry in the cryptocurrency market was inverse (to the adopted leverage effect). On the contrary, during the downward price rally, market participants exhibited an overreaction to bad news. In addition, the asymmetric reaction to the news observed during the period of low market volatility actually disappeared when the amplitude of cryptocurrency return volatility increased. The behavior of short-term investors was also varied in the study period. While during the growth of the market, small speculators were more likely to follow their own trading strategies, during the hype they borrowed the trading practices of the largest players. We also revealed the effect of training among small investors: over time, they became less prone to provocations from large players, which did not allow the 2019 rally to surpass its counterpart in 2017 in terms of both return oscillations and duration.

David Minarsch, Seyed Ali Hosseini, Marco Favorito, Jonathan S. Ward

The user experience of interacting with distributed ledger technologies (DLT) is fraught with excessive complexity, high risk and unintuitive processes. Moreover, smart contracts deployed in these systems are restricted to being reactive. These limitations have negative implications on user adoption and prevent DLTs from being general purpose. We introduce a framework for the development of Autonomous Economic Agents (AEAs), software agents that act autonomously and pursue an economic goal, and demonstrate how AEAs complement existing decentralised ledgers as a second layer technology. In particular, the framework enables a simplified user experience through automation, supports modularisation and reuse of complex decision making and machine learning capabilities, and allows for proactive behaviour facilitating autonomy. We demonstrate these gains in the context of a specific use-case, a multi-agent trading system modelling a Walrasian Exchange Economy populated by a number of agents trading a basket of tokens.

Kartik Gautam, Nitin Sharma, Praveen Kumar

This research paper examines different types of cryptocurrencies, their properties and answers various questions around their history or value in market. We begin by explaining what is cryptocurrency? We have discussed What are different properties while differentiating the cryptocurrencies. These properties include Short form, current value in market, currency's market capitalization, programming language of implementation, its year of release, founder of cryptocurrency, block time, all time high, all time low, market rank of the currency, its type of proof and algorithm used in currency. These properties are really helpful in determining whether to use the cryptocurrency or invest in it for future. We currently have hundreds of cryptocurrencies in market, which makes it really hard for one to choose a currency. In this research we have chosen some cryptocurrencies which have a very high success probability in future. We have also defined each term used in comparison, to make a clear picture in the mind of reader about what he/she is reading about.

Francisco Colon, Chaehyun Kim, Hana Kim, Wonjoon Kim

No abstract is available for this record.

Wei Zhang, Yi Li

No abstract is available for this record.

Pınar Kaya Soylu, Mustafa Okur, Özgür Çatıkkaş, Ayca Altintig

This paper examines the volatility of cryptocurrencies, with particular attention to their potential long memory properties. Using daily data for the three major cryptocurrencies, namely Ripple, Ethereum, and Bitcoin, we test for the long memory property using, Rescaled Range Statistics (R/S), Gaussian Semi Parametric (GSP) and the Geweke and Porter-Hudak (GPH) Model Method. Our findings show that squared returns of three cryptocurrencies have a significant long memory, supporting the use of fractional Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) extensions as suitable modelling technique. Our findings indicate that the Hyperbolic GARCH (HYGARCH) model appears to be the best fitted model for Bitcoin. On the other hand, the Fractional Integrated GARCH (FIGARCH) model with skewed student distribution produces better estimations for Ethereum. Finally, FIGARCH model with student distribution appears to give a good fit for Ripple return. Based on Kupieck’s tests for Value at Risk (VaR) back-testing and expected shortfalls we can conclude that our models perform correctly in most of the cases for both the negative and positive returns.

Ricardo de Souza Tavares, João F. Caldeira, Gerson de Souza Raimundo Júnior

This paper examines the formation prices in the cryptocurrency market using the CAPM model based on OLS and Regime-Switching approaches. Following Baek & Elbeck’s argument that internal factors drove cryptocurrency returns, CAPM was built, taking the CRIX index as the market and ten cryptocurrencies as assets. The results suggest that the market risk factor can partially explain cryptocurrency returns. Moreover, the regime change estimation positively impacts the market risk determination power for cryptocurrencies.

Salim Lahmiri, Stelios Bekiros

No abstract is available for this record.