Criptomonedas y sistema financiero: revisión sistemática de la literatura

Senna, Viviane de; Souza, Adriano Mendonça

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Revista de Administração de Empresas

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

Criptomonedas y sistema financiero: revisión sistemática de la literatura

Autoría SCIMAGO INSTITUTIONS RANKINGS

RESUMEN

Las criptomonedas son activos con transacciones gestionadas por nuevos métodos en comparación con las transacciones tradicionales mediadas por bolsas de valores. La inserción de estos activos puede cambiar el sistema económico. El objetivo del estudio es analizar un conjunto de artículos publicados en bases de datos internacionales de contenido científico sobre las criptomonedas y las relaciones con las bolsas de valores para comprender la evolución del tema a lo largo del tiempo. La consulta se realizó en las bases de datos Scopus y Web of Science, donde se analizaron 196 artículos que señalaron como evolución temática algoritmos de aprendizaje, comercio electrónico, mercados financieros y digitales. Los principales estudios se centraron en investigar el comportamiento de las criptomonedas ante las variables del mercado, las criptomonedas como refugio o diversificación, análisis de precios e impacto del valor emocional en las criptomonedas. Los artículos más relevantes, la red de citas y cocitaciones proporcionaron conocer literatura aún no conocida, los autores Baur et al., 2018; Ji et al., 2020; Peng et al., 2018; Symitsi & Chalvatzis, 2019; Urquhart, 2017.

Palabras clave:
revisión de la literatura; criptomoneda; bolsas de valores; sistema financiero; monedas virtuales

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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