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Cryptocurrencies and Exchange Rates: A Relationship and Causality Analysis

Author

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  • Angelo Corelli

    (Center of Excellence for Research in Finance and Accounting (CERFA), American University in Dubai, Dubai 28282, UAE)

Abstract

The paper analyzes the relationship between the most popular cryptocurrencies and a range of selected fiat currencies, in order to identify any pattern and/or causality between the series. Cryptocurrencies are a hot topic in Finance due to their strict relationship with the Blockchain system they originate from and therefore are normally considered as part of the ongoing, world-wide financial revolution. This innovative study investigates this relationship for the first time by thoroughly investigating the data, their features, and the way they are interconnected. Results show very interesting results in terms of how concentrated the causality effect on some specific cryptocurrencies and fiat currencies is. The outcome is a clear and possibly explainable relationship between cryptocurrencies and Asian markets, while envisioning some kind of Asian effect.

Suggested Citation

  • Angelo Corelli, 2018. "Cryptocurrencies and Exchange Rates: A Relationship and Causality Analysis," Risks, MDPI, vol. 6(4), pages 1-11, October.
    • Handle: RePEc:gam:jrisks:v:6:y:2018:i:4:p:111-:d:174110
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    References listed on IDEAS

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    Cited by:

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    3. Castle, Jennifer L. & Kurita, Takamitsu, 2024. "Stability between cryptocurrency prices and the term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
    4. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    5. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Pawe{l} O'swik{e}cimka & Tomasz Stanisz & Marcin Wk{a}torek, 2020. "Complexity in economic and social systems: cryptocurrency market at around COVID-19," Papers 2009.10030, arXiv.org.
    6. Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 238-252.
    7. Pourpourides, Panayiotis, 2023. "Long-Term Nexus of Macroeconomic and Financial Fundamentals with Cryptocurrencies," Cardiff Economics Working Papers E2023/23, Cardiff University, Cardiff Business School, Economics Section.
    8. Raza, Syed Ali & Ahmed, Maiyra & Aloui, Chaker, 2022. "On the asymmetrical connectedness between cryptocurrencies and foreign exchange markets: Evidence from the nonparametric quantile on quantile approach," Research in International Business and Finance, Elsevier, vol. 61(C).
    9. Griffin Msefula & Tony Chieh-Tse Hou & Tina Lemesi, 2024. "Financial and market risks of bitcoin adoption as legal tender: evidence from El Salvador," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    10. Huang, Linxian, 2024. "The relationship between cryptocurrencies and convention financial market: Dynamic causality test and time-varying influence," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 811-826.
    11. Sifat, Imtiaz Mohammad & Mohamad, Azhar & Mohamed Shariff, Mohammad Syazwan Bin, 2019. "Lead-Lag relationship between Bitcoin and Ethereum: Evidence from hourly and daily data," Research in International Business and Finance, Elsevier, vol. 50(C), pages 306-321.
    12. Theodore Pelagidis & Eleftheria Kostika, 2022. "Investigating the role of central banks in the interconnection between financial markets and cryptoassets," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 481-507, September.
    13. Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
    14. Sanjib Kumar Nayak & Sarat Chandra Nayak & Subhranginee Das, 2021. "Modeling and Forecasting Cryptocurrency Closing Prices with Rao Algorithm-Based Artificial Neural Networks: A Machine Learning Approach," FinTech, MDPI, vol. 1(1), pages 1-16, December.
    15. Seyram P. Kumah, 2024. "Cryptocurrency and African fiat currencies: A peaceful coexistence?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 53(1), February.
    16. Anastasiadis Panagiotis & Katsaros Efthymios & Koutsioukis Anastasios-Taxiarchis & Pandazis Athanasios, 2020. "GARCH Modelling of High-Capitalization Cryptocurrencies' Impacts During Bearish Markets," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(3), pages 87-106.
    17. Jennifer Castle & Takamitsu Kurita, 2022. "Structural relationships between cryptocurrency prices and monetary policy indicators," Economics Series Working Papers 972, University of Oxford, Department of Economics.
    18. Cem Cagri Donmez & Doruk Sen & Ahmet Fatih Dereli & M. Bilal Horasan & Cagri Yildiz & Nergis Feride Kaplan Donmez, 2021. "An Investigation of Fiat Characterization and Evolutionary Dynamics of the Cryptocurrency Market," SAGE Open, , vol. 11(1), pages 21582440219, February.

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