Criptomoedas e sistema financeiro: Revisão sistemática de literatura

Conteúdo do artigo principal

Viviane de Senna
https://orcid.org/0000-0003-2924-5813
Adriano Mendonça Souza
https://orcid.org/0000-0002-1562-2246

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.

Downloads

Não há dados estatísticos.

Métricas

Carregando Métricas ...

Detalhes do artigo

Como Citar
DE SENNA, V.; SOUZA, A. M. Criptomoedas e sistema financeiro: Revisão sistemática de literatura . RAE-Revista de Administração de Empresas, [S. l.], v. 63, n. 4, p. e2022–0019, 2023. DOI: 10.1590/S0034-759020230403. Disponível em: https://periodicos.fgv.br/rae/article/view/89819. Acesso em: 4 jul. 2024.
Seção
Artigos

Referências

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Bariviera, 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

Baumeister, R. F., & Leary, M. R. (1997). Writing Narative Literature Reviews - Bausmeister & Leary. Review of General Psychology, 1(3), 311–320.

Baur, 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

Begušić, 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

Bhandarkar, V. V, Bhandarkar, A. A., & Shiva, A. (2019). Digital Stocks using blockchain technology the possible future of stocks? International Journal of Management, 10(3), 44–49. https://doi.org/10.34218/IJM.10.3.2019/005

Bouri, 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

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5, 146–166. https://doi.org/10.1016/j.joi.2010.10.002

da Gama Silva, P. V. J., Klotzle, M. C., Pinto, A. C. F., & Gomes, L. L. (2019). Herding behavior and contagion in the cryptocurrency market. Journal of Behavioral and Experimental Finance, 22, 41–50. https://doi.org/10.1016/j.jbef.2019.01.006

da Silva Filho, A. C., Maganini, N. D., & de Almeida, E. F. (2018). Multifractal analysis of Bitcoin market. Physica A: Statistical Mechanics and Its Applications, 512, 954–967. https://doi.org/10.1016/j.physa.2018.08.076

Drożdż, 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

Eliacik, 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

Engle, R. (2002). Dynamic Conditional Correlation. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487

Eross, 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

Feng, 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

Gajardo, 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

Galvão, M. C. B., & Ricarte, I. L. M. (2019). REVISÃO SISTEMÁTICA DA LITERATURA: CONCEITUAÇÃO, PRODUÇÃO E PUBLICAÇÃO. Logeion: Filosofia Da Informação, 6(1), 57–73. https://doi.org/10.21728/logeion.2019v6n1.p57-73

Garcia, 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

Harris, L. (1991). Stock Price Clustering and Discreteness. The Review of Financial Studies, 4(3), 389–415.

Higgins, J. P., & Green, S. (2008). Cochrane Handbook for Systematic Reviews of Interventions. In J. P. Higgins & S. Green (Eds.), Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series, 1-649. Wiley.

Ikenberry, D. L., & Weston, J. P. (2007). Clustering in US Stock Prices after Decimalisation. European Financial Management, 14(1), 30–54. https://doi.org/10.1111/j.1468-036X.2007.00410.x

Ilha, P. C. da S., Piacenti, C. A., & Leismann, E. L. (2018). Uma Análise Comparativa da Competitividade Econômico-financeira das Cooperativas Agroindustriais do Oeste do Paraná. Revista de Economia e Sociologia Rural, 56(1), 91–106. https://doi.org/10.1590/1234-56781806-94790560106

Ji, 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

Kamran, M., Butt, P., Abdel-Razzaq, A., & Djajadikerta, H. G. (2022). Is Bitcoin a safe haven? Application of FinTech to safeguard Australian stock markets. Studies in Economics and Finance, 39(3), 386–402. https://doi.org/10.1108/SEF-05-2021-0201

Kliber, 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

Kristjanpoller, 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

Kurka, 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

Liang, J., Li, L., & Zeng, D. (2018). Evolutionary dynamics of cryptocurrency transaction networks: An empirical study. PLOS ONE, 13(8), e0202202. https://doi.org/10.1371/journal.pone.0202202

Mensi, 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

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. www.bitcoin.org

Panagiotidis, 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

Peng, 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

Poyser, 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

Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses. Annual Review of Psychology, 70(1), 747–770. https://doi.org/10.1146/annurev-psych-010418-102803

Stosic, 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

Symitsi, 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

The Campbell Collaboration. (2014). Campbell Collaboration Systematic Reviews: Policies and Guidelines. https://doi.org/10.4073/cpg.2016.1

Thomé, A. M. T., Scavarda, L. F., & Scavarda, A. J. (2016). Conducting systematic literature review in operations management. Production Planning & Control, 27(5), 408–420. https://doi.org/10.1080/09537287.2015.1129464

Thorne, S., Jensen, L., Kearney, M. H., Noblit, G., & Sandelowski, M. (2004). Qualitative Metasynthesis: Reflections on Methodological Orientation and Ideological Agenda. Qualitative Health Research, 14(10), 1342–1365. https://doi.org/10.1177/1049732304269888

Tiwari, 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

Tiwari, A. K., Selmi, R., & Hammoudeh, S. (2018). Efficiency or speculation? A dynamic analysis of the Bitcoin market. Economics Bulletin, 38(4), 2037–2046. https://ideas.repec.org/a/ebl/ecbull/eb-18-00395.html

Urquhart, A. (2017a). Price clustering in Bitcoin. Economics Letters, 159, 145–148. https://doi.org/10.1016/j.econlet.2017.07.035