CRIPTOMOEDAS E SISTEMA FINANCEIRO: REVISÃO SISTEMÁTICA DE LITERATURA

Senna, Viviane de; Souza, Adriano Mendonça

doi:10.1590/S0034-759020230403

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ARTIGOS • Rev. adm. empres. 63 (4) • 2023 • https://doi.org/10.1590/S0034-759020230403 copiar

CRIPTOMOEDAS E SISTEMA FINANCEIRO: REVISÃO SISTEMÁTICA DE LITERATURA

Criptomonedas y sistema financiero: revisión sistemática de la literatura

Autoria SCIMAGO INSTITUTIONS RANKINGS

RESUMO

As criptomoedas são ativos com transações gerenciadas por novos métodos se comparados a transações tradicionais mediadas pelas bolsas de valores. A inserção desses ativos pode modificar o sistema econômico. O objetivo do estudo é analisar um conjunto de artigos publicados em bases de dados internacionais de conteúdo científico sobre criptomoedas e as relações com as bolsas de valores para compreender a evolução da temática ao longo do tempo. A consulta foi realizada nas bases Scopus e Web of Science. Foram analisados 196 artigos que indicaram como evolução temática algoritmos de aprendizagem, negociação eletrônica, mercado financeiro e digital. Os principais estudos focaram a investigação do comportamento das criptomoedas diante de variáveis mercadológicas, criptomoedas como porto seguro ou diversificação, análise dos preços e do impacto do valor emocional nas criptomoedas. Os artigos mais relevantes, a rede de citações e cocitações possibilitaram o conhecimento dos autores Baur et al., 2018; Ji et al., 2020; Peng et al., 2018; Symitsi & Chalvatzis, 2019; Urquhart, 2017.

Palavras-chaves:
revisão de literatura; criptomoeda; bolsas de valores; sistema financeiro; moeda virtual

Objetivos dos artigos	Quantidade de artigos	Total de citações	Autores
Comportamento/propriedades das criptomoedas	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... )
Criptomoeda como porto seguro ou diversificação	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.... )
Preço da criptomoeda	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... )
Valor emocional (tweets) e criptomoedas	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... )
Total geral	25	1569

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