Welcome to Francis Academic Press

Academic Journal of Business & Management, 2023, 5(2); doi: 10.25236/AJBM.2023.050218.

Investor-Induced Cryptocurrency Contagion Channels: An Empirical Evidence from Five Major Economies


Yatao Wang

Corresponding Author:
Yatao Wang

Economics and Management School, Xi’an University of Posts and Telecommunications, Xi’an, China


Coupled with the global pandemic and hyperinflation, the innovation risks of cryptocurrency have led to significant price volatility. There is a significant effect of cryptocurrencies on traditional financial markets and contagion channels. Therefore, regulatory authorities should understand the contagion channels to analyze the input risks and take necessary measures. This paper adopts the copula model to study the contagion channels of cryptocurrencies in five major economies. Additionally, three hypotheses are tested to determine whether investor induction serves as the main contagion channel. The empirical results indicate that cryptocurrency market contagion is significant in all five economies, with "portfolio rebalancing" as an important channel of transmission. Moreover, some countries represent time-varying contagion channels. Lastly, cryptocurrencies are not only an indirect symbol of the country’s integration into the global economy but also a risk indicator for new assets.


Cryptocurrency regulation; Contagion channels; Portfolio rebalancing; Copula model

Cite This Paper

Yatao Wang. Investor-Induced Cryptocurrency Contagion Channels: An Empirical Evidence from Five Major Economies. Academic Journal of Business & Management (2023) Vol. 5, Issue 2: 121-128. https://doi.org/10.25236/AJBM.2023.050218.


[1] Gai P, Kapadia S, Millard S, et al. Financial innovation, macroeconomic stability and systemic crises[J]. The Economic Journal, 2008, 118(527): 401-426.

[2] Jiang H, Tang S, Li L, et al. Re-examining the Contagion Channels of Global Financial Crises: Evidence from the Twelve Years since the US Subprime Crisis[J]. Research in International Business and Finance, 2022, 60: 101617.

[3] Samitas A, Kampouris E, Umar Z. Financial contagion in real economy: The key role of policy uncertainty[J]. International Journal of Finance & Economics, 2022, 27(2): 1633-1682.

[4] Boubaker S, Jouini J, Lahiani A. Financial contagion between the US and selected developed and emerging countries: The case of the subprime crisis[J]. The Quarterly Review of Economics and Finance, 2016, 61: 14-28.

[5] Ye W, Liu X, Miao B. Measuring the subprime crisis contagion: Evidence of change point analysis of copula functions[J]. European Journal of Operational Research, 2012, 222(1): 96-103.

[6] Longstaff F A. The subprime credit crisis and contagion in financial markets[J]. Journal of financial economics, 2010, 97(3): 436-450.

[7] Lipton A. Cryptocurrencies change everything[J]. Quantitative Finance, 2021, 21(8): 1257-1262.

[8] Devries P D. An analysis of cryptocurrency, bitcoin, and the future[J]. International Journal of Business Management and Commerce, 2016, 1(2): 1-9.

[9] Malhotra N, Gupta S. Volatility spillovers and correlation between cryptocurrencies and Asian equity market[J]. International Journal of Economics and Financial Issues, 2019, 9(6): 208.

[10] Aydoğan B, Vardar G, Taçoğlu C. Volatility spillovers among G7, E7 stock markets and cryptocurrencies[J]. Journal of Economic and Administrative Sciences, 2022.

[11] Yuan Y, Wang H, Jin X. Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19[J]. International Review of Financial Analysis, 2022, 83: 102315.

[12] Boyer B H, Kumagai T, Yuan K. How do crises spread? Evidence from accessible and inaccessible stock indices[J]. The journal of finance, 2006, 61(2): 957-1003.

[13] Kumar M S, Persaud A. Pure contagion and investors’ shifting risk appetite: analytical issues and empirical evidence[J]. International Finance, 2002, 5(3): 401-436.

[14] Wang H, Yuan Y, Li Y, et al. Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory[J]. Economic Modelling, 2021, 94: 401-414.

[15] Horta P, Lagoa S, Martins L. Unveiling investor-induced channels of financial contagion in the 2008 financial crisis using copulas[J]. Quantitative Finance, 2016, 16(4): 625-637.

[16] Naeem M A, Bouri E, Costa M D, et al. Energy markets and green bonds: A tail dependence analysis with time-varying optimal copulas and portfolio implications[J]. Resources Policy, 2021, 74: 102418.

[17] Pho K H, Ly S, Lu R, et al. Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China[J]. International Review of Financial Analysis, 2021, 74: 101674.

[18] Fülle M J, Herwartz H. Predicting Tail Risks by a Markov Switching MGARCH Model with Varying Copula Regimes[J]. Available at SSRN, 2022.

[19] Jayech S. The contagion channels of July–August-2011 stock market crash: A DAG-copula based approach[J]. European Journal of Operational Research, 2016, 249(2): 631-646.

[20] Forbes K J, Rigobon R. No contagion, only interdependence: measuring stock market comovements [J]. The journal of Finance, 2002, 57(5): 2223-2261.

[21] Liu H, Erdem E, Shi J. Comprehensive evaluation of ARMA–GARCH (-M) approaches for modeling the mean and volatility of wind speed[J]. Applied Energy, 2011, 88(3): 724-732.

[22] Sklar M. Fonctions de repartition an dimensions et leurs marges[J]. Publ. inst. statist. univ. Paris, 1959, 8: 229-231.

[23] Cherubini U, Luciano E, Vecchiato W. Copula methods in finance[M]. John Wiley & Sons, 2004.

[24] Joe H. Multivariate models and multivariate dependence concepts[M]. CRC press, 1997.

[25] Frahm G, Junker M, Schmidt R. Estimating the tail-dependence coefficient: properties and pitfalls[J]. Insurance: mathematics and Economics, 2005, 37(1): 80-100.