AN ANALYSIS OF EVOLUTIONARY CRYPTOCURRENCY MARKET DYNAMICS

Öz

The focus of this research is to describe and discuss future blockchain technology in relation to different forms of digital cryptocurrencies by investigating distinct characteristics and common features of cryptocurrencies on the market. This research explores significant relationships between the major cryptocurrencies on the complex cryptocurrency market ecosystem, particularly Bitcoin and the most prominent altcoins based on historical market capitalization data for the last two years. In this work cross-correlations between different cryptocurrencies are examined in terms of changes in the market capitalization value. For the comparative analysis minimum spanning tree (MST) and hierarchical structure tree (HST) methods are applied in the context
of economic behaviour of cryptocurrencies with regard to global cryptocurrency market trends. 

Anahtar Kelimeler

• Blokzinciri,Kayıtzinciri,Kripto Paralar,Korelasyon Matrisi,Asgari Yayılma Ağacı,Analitik Hiyerarşi Süreci

AN ANALYSIS OF EVOLUTIONARY CRYPTOCURRENCY MARKET DYNAMICS

Öz

The focus of this research is to describe and discuss future blockchain technology in relation to different forms of digital cryptocurrencies by investigating distinct characteristics and common features of cryptocurrencies on the market. This research explores significant relationships between the major cryptocurrencies on the complex cryptocurrency market ecosystem, particularly Bitcoin and the most prominent altcoins based on historical market capitalization data for the last two years. In this work cross-correlations between different cryptocurrencies are examined in terms of changes in the market capitalization value. For the comparative analysis minimum spanning tree (MST) and hierarchical structure tree (HST) methods are applied in the context of economic behaviour of cryptocurrencies with regard to global cryptocurrency market trends.

Anahtar Kelimeler

• Blockchain,Cryptocurrencies,Correlation matrix,Minimum Spanning Tree,Hierarchical Structure Tree

Kaynakça

1. [1] S. Nakamoto, Bitcoin: A peer-to-peer electronic cash system, 2009. https://bitcoin.org/bitcoin.pdf.
2. [2] D.G. Hileman, M. Rauchs, Global Cryptocurrency Benchmarking Study, 2017
3. [3] C. Burniske and A.White, Bitcoin: Ringing the Bell for a New Asset Class, 2016
4. [4] A.S. Bruyn, Blockchain an introduction, 2017.
5. [5] M. Casey, J. Crane, G. Gensler, S. Johnson, N. Nerula, The impact of blockchain technology and finance: a catalyst for change, Geneva Report on the World Economy, 21st, (2018).
6. [6] L. Cocco, G. Concas, M. Marchesi, Using an artificial financial market for studying a cryptocurrency market, Journal of Economic Interaction and Coordination 12 (2) (2017) 345-365.
7. [7] D. Stosic, D.Stosic, T.B. Ludermir, T. Stosic, Collective behavior of cryptocurrency price changes. Pyhsica A: Statistical Mechanics and its Applications 507 (2018) 499-509.
8. [8] R.N. Mantegna, in: Econophysics: an emergent science, Proceedings of the 1st Workshop on Econophysics, ed. I. Kertesz and I. Kondor, Available at: http://www.phy.bme.hu/~kullmann/Egyetem/konyv.html, (2002) 27-35.

9. [9] R.N. Mantegna, H.E. Stanley, An Introduction to Econophysics: Correlations and Complexity in Finance, Cambridge University Press, 1999.
10. [10] R.N. Mantegna, H.E. Stanley, Scaling behaviour in the dynamics of an economic index, Nature 376 (1995) 46–49.
11. [11] L.A.N. Amaral, S.V. Buldyrev, S. Havlin, M.A. Salinger, H.E. Stanley, Power law scaling for a system of interacting units with complex internal structure, Physical Review Letters 80 (7) (1998) 1385–1388.
12. [12] J. Kwapień, S. Drożdż, Physical approach to complex systems, Physical Reports 515 (3-4) (2012) 115–226.
13. [13] E.J. Elton, M.J. Gruber, Modern Portfolio Theory and Investment Analysis, John Wiley & Sons, 1995.
14. [14] J.P. Bouchaud, M. Potters, Theory of Financial Risk, Cambridge University Press, 2000.
15. [15] J.Y. Campbell, A.W. Lo, A.C. MacKinlay, The Econometrics of Financial Markets, Princeton University Press, 1997.
16. [16] H. Wold, A Study in the Analysis of Stationary Time Series, Almqvist and Wiksell, 1938.
17. [17] O.A. Rosso, H.A. Larrondo, M.T. Martin, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Physical Review Letters 99 (15) (2007) 154102.
18. [18] V. Plerou, P. Gopikrishnan, B. Rosenow, L.A.N. Amaral, H.E. Stanley, Universal and nonuniversal properties of cross-correlations in financial time series, Physical Review Letters 83 (7) (1999) 1471–1474.
19. [19] A. Peterson, “Hal Finney received the first Bitcoin transaction. Here’s how he describes it.”, Available at: https://www.washingtonpost.com/news/the-switch/wp/2014/01/03/hal-finney-received-the-first-bitcoin-transaction-heres-how-he-describes-it/?noredirect=on&utm_term=.f4dcd5382876, 2014.
20. [20] R. Bigmore “A decade of cryptocurrency: from bitcoin to mining chips”, Available at: https://www.telegraph.co.uk/technology/digital-money/the-history-of-cryptocurrency/, 2018.
21. [21] Bitcoin price index, Available at: https://www.coindesk.com/price/bitcoin (Accessed on 23 October 2018)
22. [22] P. Ciaian, M. Rajcaniova, K. d'Artis, Virtual relationships: Short-and long-run evidence from Bitcoin and altcoin markets, Journal of International Financial Markets, Institutions and Money 52 (2018) 173-195.
23. [23] R. Farell, An Analysis of the Cryptocurrency Industry, Wharton Research Scholars, 2015.
24. [24] L.H. White, The market for cryptocurrencies, Cato Journal 35 (2015) 383-402.
25. [25] J. Li, W. Mann, Initial Coin Offering and Platform Building, 2018.
26. [26] C. Catalini, J.S. Gans, Initial Coin Offerings and the Value of Crypto Tokens, National Bureau of Economic Research, 2018.
27. [27] G. Wood, Ethereum: a secure decentralised generalised transaction ledger, Ethereum Project Yellow Paper 151 (2014) 1-32.
28. [28] S. Yi, Z. Xu, G. Wang, Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency? International Review of Financial Analysis 60 (2018) 98-114.
29. [29] D. Schwartz, N. Youngs, A. Britto, The Ripple protocol consensus algorithm, Ripple Labs Inc White Paper 5 (2014) 1-8.
30. [30] M. Orcutt, Cryptocurrencies are not created equal, MIT Technology Review 121 (3) (2018) 26-27.
31. [31] O. Nica, K. Piorowska, K.R. Schenk-Hoppé, Cryptocurrencies: Concept and Current Market Structure, 2017.
32. [32] Transaction speeds: Which cryptocurrency is the fastest?, https://www.abitgreedy.com/transaction-speed/ (Accessed on 20 November 2018)
33. [33] Cryptocurrencies with a fixed max supply, https://cryptoli.st/lists/fixed-supply (Accessed on 20 November 2018)
34. [34] Cryptocurrency market capitalizations, Available at: https://coinmarketcap.com/charts/ (Accessed on 23 October 2018)
35. [35] Percentage of total market capitalization of cryptocurrencies, Available at: https://coinmarketcap.com/charts/ (Accessed on 23 October 2018)
36. [36] The total cryptocurrencies by market capitalization, Available at: https://coin.dance/stats/marketcaptoday (Accessed on 23 October 2018)
37. [37] The cryptocurrency market statistics, Available at: https://www.cryptoindex.co/ (Accessed on 23 October 2018)
38. [38] Top 10 cryptocurrencies by market capitalization, Available at: https://coinmarketcap.com/ (Accessed on 23 October 2018)
39. [39] Top 10 cryptocurrencies by market capitalization, Available at: https://www.cryptocurrencychart.com/ (Accessed on 23 October 2018)
40. [40] T. Ulusoy, M. Keskin, A. Shirvani, B. Deviren, E. Kantar, C.Ç. Dönmez, Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach, Physica A: Statistical Mechanics and Its Applications 391 (21) (2012) 5121-5131.
41. [41] R.N. Mantegna, Hierarchical structures in financial markets, European Physical Journal B, 1999.
42. [42] G. Hall, Pearson’s correlation coefficient, 2015
43. [43] CoinMarketCap API, Available at: https://api.coinmarketcap.com/v1/ticker (Accessed on 18 October 2018)
44. [44] CryptoCompare API, Available at: https://min-api.cryptocompare.com (Accessed on 18 October 2018)
45. [45] C. Zahn. “Graph-theoretical methods for detecting and describing gestalt clusters”. IEEE Transactions on Computers, C-20:68-86, 1971.