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One size does not fit all: external driver of the cryptocurrency world

Author

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  • Yaman Omer Erzurumlu
  • Tunc Oygur
  • Alper Kirik

Abstract

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.

Suggested Citation

  • Yaman Omer Erzurumlu & Tunc Oygur & Alper Kirik, 2020. "One size does not fit all: external driver of the cryptocurrency world," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(3), pages 545-560, June.
    • Handle: RePEc:eme:sefpps:sef-01-2020-0018
    DOI: 10.1108/SEF-01-2020-0018
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    References listed on IDEAS

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    1. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2019. "On long memory effects in the volatility measure of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 28(C), pages 95-100.
    2. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2018. "On the determinants of bitcoin returns: A LASSO approach," Finance Research Letters, Elsevier, vol. 27(C), pages 235-240.
    3. Matkovskyy, Roman & Jalan, Akanksha, 2019. "From financial markets to Bitcoin markets: A fresh look at the contagion effect," Finance Research Letters, Elsevier, vol. 31(C), pages 93-97.
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    Cited by:

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    2. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • F65 - International Economics - - Economic Impacts of Globalization - - - Finance
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services

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