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Purpose The stock market is vulnerable to various exogenous factors, and its fluctuations can reflect the effects of political, economic and market factors. The purpose of this paper is therefore to choose the stock market as a representative to analyze the potential impact of the Brexit event on global financial markets and how to prevent the spread of risks across global financial markets. Design/methodology/approach This study chooses the auto-regressive moving average generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model to fit the financial series and uses it as the marginal distribution model to establish the vine copula model. The maximum spanning tree algorithm is used to select the optimal rattan structure model and pair-copula function. According to the final ARMA-GARCH-R-vine copula model, the tail correlation coefficients of the UK, France, Germany, USA and China stock markets are calculated and used to analyze their dependence structure. Findings The negative impact of the Brexit event on the British stock market is greater and is more likely to be transmitted to France and Germany. China and the USA are less likely to be impacted by the Brexit incident. The US financial market is more closely linked to France, and it may benefit from the Brexit incident due to the impact of the exchange rate. Although the Chinese stock market is directly connected to the British stock market, due to the existence of national macro-controls and other factors, it will be less affected by the Brexit incident. The main impact comes from the dual devaluation pressure on the RMB. Originality/value This paper selects the optimal combination model based on actual data, and the results obtained can accurately reflect the interdependence between relevant stock markets and can guide risk aversion in the financial investment field.