Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?

Abstract The growing cryptocurrency market has attracted the attention from many investors worldwide, mainly due to the ease of entering the market and its extremely volatile character. The main aim of this paper is to examine interdependencies between log-returns of cryptocurrencies, with the special focus on Bitcoin. Based on implications from the literature, we use methods dedicated for studying the stock market and apply the two-step analysis, comparing results between two subsequent periods. Results obtained using Minimum Spanning Tree (MST) method show that cryptocurrencies form hierarchical clusters, consistently over two separate periods, indicating potential topological properties of the cryptocurrency market. Then, using Vector Autoregression (VAR) model, we study the transmission of demand shocks within clusters. Results show that changes in Bitcoin price do not affect and are not affected by changes in prices of other cryptocurrencies. However, results indicate that findings obtained for Bitcoin shall not be generalized to the entire cryptocurrency market.

[1]  Elie Bouri,et al.  Herding behaviour in cryptocurrencies , 2019, Finance Research Letters.

[2]  Kai Zimmermann,et al.  Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions , 2014, ECIS.

[3]  Leonidas Sandoval Junior Pruning a Minimum Spanning Tree , 2011, 1109.0642.

[4]  Adam Hayes,et al.  Cryptocurrency Value Formation: An Empirical Analysis Leading to a Cost of Production Model for Valuing Bitcoin , 2016, MCIS.

[5]  S. Corbet,et al.  Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets , 2017 .

[6]  Robert J. Barro,et al.  Money and the Price Level under the Gold Standard , 1979 .

[7]  Ladislav Kristoufek,et al.  What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis , 2014, PloS one.

[8]  Teresa B. Ludermir,et al.  Collective behavior of cryptocurrency price changes , 2018, Physica A: Statistical Mechanics and its Applications.

[9]  J. Poterba,et al.  What moves stock prices? , 1988 .

[10]  Claudia Czado,et al.  Selecting and estimating regular vine copulae and application to financial returns , 2012, Comput. Stat. Data Anal..

[11]  D. Wijk,et al.  What can be expected from the Bitcoin , 2013 .

[12]  Dimitrios Koutmos Return and volatility spillovers among cryptocurrencies , 2018, Economics Letters.

[13]  Julian Lorenz,et al.  Bitcoin and Cryptocurrencies - Not for the Faint-Hearted , 2016 .

[14]  Ladislav Kristoufek,et al.  BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era , 2013, Scientific Reports.

[15]  Tālis J. Putniņš,et al.  Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed Through Cryptocurrencies? , 2018, The Review of Financial Studies.

[16]  D. Roubaud,et al.  Co-explosivity in the cryptocurrency market , 2019, Finance Research Letters.

[17]  Adam S. Hayes,et al.  Cryptocurrency Value Formation: An Empirical Analysis Leading to a Cost of Production Model for Valuing Bitcoin , 2016, MCIS.

[18]  R. Mantegna Hierarchical structure in financial markets , 1998, cond-mat/9802256.

[19]  Shelton Peiris,et al.  A new look at Cryptocurrencies , 2018 .

[20]  Gangjin Wang,et al.  Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency? , 2018, International Review of Financial Analysis.

[21]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[22]  Grau-Carles Pilar,et al.  The cryptocurrency market: A network analysis , 2018 .

[23]  D. Zięba,et al.  Are demand shocks in Bitcoin contagious , 2018 .

[24]  A. H. Dyhrberg Bitcoin, gold and the dollar – A GARCH volatility analysis , 2016 .

[25]  Juan Gabriel Brida,et al.  Hierarchical Structure of the German Stock Market , 2007, Expert Syst. Appl..

[26]  Qiang Ji,et al.  Dynamic connectedness and integration in cryptocurrency markets , 2019, International Review of Financial Analysis.

[27]  P. Ciaian,et al.  The economics of BitCoin price formation , 2014, 1405.4498.

[28]  Helmut Ltkepohl,et al.  New Introduction to Multiple Time Series Analysis , 2007 .