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PurposeThe purpose of the research is to assess the risk of the financial market in the digital economy through the quantitative analysis model in the big data era. It is a big challenge for the government to carry out financial market risk management in the big data era.Design/methodology/approachIn this study, a generalized autoregressive conditional heteroskedasticity-vector autoregression (GARCH-VaR) model is constructed to analyze the big data financial market in the digital economy. Additionally, the correlation test and stationarity test are carried out to construct the best fit model and get the corresponding VaR value.FindingsOwing to the conditional heteroscedasticity, the index return series shows the leptokurtic and fat tail phenomenon. According to the AIC (Akaike information criterion), the fitting degree of the GARCH model is measured. The AIC value difference of the models under the three distributions is not obvious, and the differences between them can be ignored.Originality/valueUsing the GARCH-VaR model can better measure and predict the risk of the big data finance market and provide a reliable and quantitative basis for the current technology-driven regulation in the digital economy.

This paper takes 968 listed companies in A-shares of Shanghai Stock Exchange as an example. Through the construction of financial competitiveness system and the use of factor analysis method, this paper systematically studies the basic situation of the overall financial competitiveness of Shanghai A-share listed companies. And from the supply side point of view, by reducing the financial costs and operating costs, it can improve the Shanghai A-share listed companies in the financial competitiveness of the relevant recommendations.

Abstract-At present, China is a country with a large population and a big agriculture. Therefore, agriculture occupies an important position in the national economy. Therefore, this paper chooses to study the listed agricultural companies under the supply-side reform, which establishes the financial competitiveness evaluation system of the listed agricultural companies from the perspective of financial competitiveness, and conducts an evaluation on the financial competitiveness of the listed companies using the factor analysis method, and it also points out some countermeasures to improve the financial competitiveness of listed companies.