CRYPTOCURRENCY AND FINANCIAL SYSTEM: SYSTEMATIC LITERATURE REVIEW

Senna, Viviane de; Souza, Adriano Mendonça

doi:10.1590/S0034-759020230403x

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ARTICLES • Rev. adm. empres. 63 (4) • 2023 • https://doi.org/10.1590/S0034-759020230403x copy

CRYPTOCURRENCY AND FINANCIAL SYSTEM: SYSTEMATIC LITERATURE REVIEW

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Cryptocurrencies are assets with transactions managed by new methods compared to traditional transactions mediated by Stock Exchanges. The insertion of these assets can change the economic system. The objective of the study is to analyze a set of articles published in international databases of scientific content on cryptocurrencies and the relations with the Stock Exchanges to understand the evolution of the theme over time. The consultation was carried out in the Scopus and Web of Science databases, where 196 articles were analyzed, these indicated learning algorithms, electronic trading, financial and digital markets thematic evolution. The main studies focused on investigating the behavior of cryptocurrencies in the face of market variables, cryptocurrencies as a safe haven or diversification, analysis of prices and the impact of emotional value on cryptocurrencies. The most relevant articles, the citations and co-citations network of these, provided insights into not yet known literature, such authors are Baur et al., 2018; Ji et al., 2020; Peng et al., 2018; Symitsi & Chalvatzis, 2019; Urquhart, 2017.

Keywords:
literature review; cryptocurrency; stock exchanges; financial system; virtual currency

Objectives of the articles	Number of articles	Total of citations	Authors
Behavior/properties of cryptocurrencies.	17	982	(Begušić et al., 2018Begušić, S., Kostanjčar, Z., Eugene Stanley, H., & Podobnik, B. (2018). Scaling properties of extreme price fluctuations in Bitcoin markets. Physica A: Statistical Mechanics and Its Applications, 510, 400–406. https://doi.org/10.1016/j.physa.2018.06.131 https://doi.org/10.1016/j.physa.2018.06.... ; Drożdż et al., 2018Drożdż, S., Gȩbarowski, R., Minati, L., Oświȩcimka, P., & Wa̧torek, M. (2018). Bitcoin market route to maturity? Evidence from return fluctuations, temporal correlations and multiscaling effects. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(7), 071101. https://doi.org/10.1063/1.5036517 https://doi.org/10.1063/1.5036517... ; Eross et al., 2019Eross, A., McGroarty, F., Urquhart, A., & Wolfe, S. (2019). The intraday dynamics of bitcoin. Research in International Business and Finance, 49, 71–81. https://doi.org/10.1016/j.ribaf.2019.01.008 https://doi.org/10.1016/j.ribaf.2019.01.... ; Feng et al., 2018Feng, W., Wang, Y., & Zhang, Z. (2018). Informed trading in the Bitcoin market. Finance Research Letters, 26, 63–70. https://doi.org/10.1016/j.frl.2017.11.009 https://doi.org/10.1016/j.frl.2017.11.00... ; Gajardo et al., 2018Gajardo, G., Kristjanpoller, W. D., & Minutolo, M. (2018). Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen? Chaos, Solitons & Fractals, 109, 195–205. https://doi.org/10.1016/j.chaos.2018.02.029 https://doi.org/10.1016/j.chaos.2018.02.... ; Ji et al., 2020Ji, Q., Zhang, D., & Zhao, Y. (2020). Searching for safe-haven assets during the COVID-19 pandemic. International Review of Financial Analysis, 71, 101526. https://doi.org/10.1016/j.irfa.2020.101526 https://doi.org/10.1016/j.irfa.2020.1015... ; Kristjanpoller & Bouri, 2019Kristjanpoller, W., & Bouri, E. (2019). Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies. Physica A: Statistical Mechanics and Its Applications, 523, 1057–1071. https://doi.org/10.1016/j.physa.2019.04.115 https://doi.org/10.1016/j.physa.2019.04.... ; Kurka, 2019Kurka, J. (2019). Do cryptocurrencies and traditional asset classes influence each other? Finance Research Letters, 31, 38–46. https://doi.org/10.1016/j.frl.2019.04.018 https://doi.org/10.1016/j.frl.2019.04.01... ; Mensi et al., 2019Mensi, W., Sensoy, A., Aslan, A., & Kang, S. H. (2019). High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets. The North American Journal of Economics and Finance, 50, 101031. https://doi.org/10.1016/j.najef.2019.101031 https://doi.org/10.1016/j.najef.2019.101... ; Panagiotidis et al., 2019Panagiotidis, T., Stengos, T., & Vravosinos, O. (2019a). The effects of markets, uncertainty and search intensity on bitcoin returns. International Review of Financial Analysis, 63, 220–242. https://doi.org/10.1016/j.irfa.2018.11.002 https://doi.org/10.1016/j.irfa.2018.11.0... ; Peng et al., 2018Peng, Y., Albuquerque, P. H. M., Camboim de Sá, J. M., Padula, A. J. A., & Montenegro, M. R. (2018). The best of two worlds: Forecasting high frequency volatility for cryptocurrencies and traditional currencies with Support Vector Regression. Expert Systems with Applications, 97, 177–192. https://doi.org/10.1016/j.eswa.2017.12.004 https://doi.org/10.1016/j.eswa.2017.12.0... ; Silva et al., 2018; Silva et al., 2019; Stosic et al., 2019Stosic, D., Stosic, D., Ludermir, T. B., & Stosic, T. (2019). Multifractal behavior of price and volume changes in the cryptocurrency market. Physica A: Statistical Mechanics and Its Applications, 520, 54–61. https://doi.org/10.1016/j.physa.2018.12.038 https://doi.org/10.1016/j.physa.2018.12.... ; Symitsi & Chalvatzis, 2019Symitsi, E., & Chalvatzis, K. J. (2019). The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks. Research in International Business and Finance, 48(C), 97–110. https://doi.org/10.1016/j.ribaf.2018.12.001 https://doi.org/10.1016/j.ribaf.2018.12.... ; Tiwari et al., 2019Tiwari, A. K., Raheem, I. D., & Kang, S. H. (2019). Time-varying dynamic conditional correlation between stock and cryptocurrency markets using the copula-ADCC-EGARCH model. Physica A: Statistical Mechanics and Its Applications, 535, 122295. https://doi.org/10.1016/j.physa.2019.122295 https://doi.org/10.1016/j.physa.2019.122... )
Cryptocurrency as a safe haven or diversification	3	429	(Baur et al., 2018Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189. https://doi.org/10.1016/j.intfin.2017.12.004 https://doi.org/10.1016/j.intfin.2017.12... ; Bouri et al., 2020Bouri, E., Lucey, B., & Roubaud, D. (2020). Cryptocurrencies and the downside risk in equity investments. Finance Research Letters, 33, 101211. https://doi.org/10.1016/j.frl.2019.06.009 https://doi.org/10.1016/j.frl.2019.06.00... ; Kliber et al., 2019Kliber, A., Marszałek, P., Musiałkowska, I., & Świerczyńska, K. (2019). Bitcoin: Safe haven, hedge or diversifier? Perception of bitcoin in the context of a country’s economic situation — A stochastic volatility approach. Physica A: Statistical Mechanics and Its Applications, 524, 246–257. https://doi.org/10.1016/j.physa.2019.04.145 https://doi.org/10.1016/j.physa.2019.04.... )
Price of cryptocurrency.	3	62	(Bariviera et al., 2018Bariviera, A. F., Zunino, L., & Rosso, O. A. (2018). An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(7), 1–17. https://doi.org/10.1063/1.5027153 https://doi.org/10.1063/1.5027153... ; Poyser, 2019Poyser, O. (2019). Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach. Eurasian Economic Review, 9(1), 29–60. https://doi.org/10.1007/s40822-018-0108-2 https://doi.org/10.1007/s40822-018-0108-... ; Urquhart, 2017Urquhart, A. (2017a). Price clustering in Bitcoin. Economics Letters, 159, 145–148. https://doi.org/10.1016/j.econlet.2017.07.035 https://doi.org/10.1016/j.econlet.2017.0... )
Emotional value (tweets) and cryptocurrencies	2	96	(Eliacik & Erdogan, 2018Eliacik, A. B., & Erdogan, N. (2018). Influential user weighted sentiment analysis on topic based microblogging community. Expert Systems with Applications, 92, 403–418. https://doi.org/10.1016/j.eswa.2017.10.006 https://doi.org/10.1016/j.eswa.2017.10.0... ; Garcia & Schweitzer, 2015Garcia, D., & Schweitzer, F. (2015). Social signals and algorithmic trading of Bitcoin. Royal Society Open Science, 2(9), 150288. https://doi.org/10.1098/rsos.150288 https://doi.org/10.1098/rsos.150288... )
Overall total	25	1569

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