With the rapid development of economy, enterprises, as the micro-foundation and economic cell of urban economic vitality, have made great contributions to the expansion of investment, expansion of productivity development scale and improvement of productivity development level. Therefore, the steady and high-quality development of enterprises can better promote the development of the overall economy. Financial performance management is an important part of enterprise management, is the core of enterprise management, and directly affects the operation and development of enterprises. With the development of market economy, enterprises have more strict requirements on financial management. Therefore, it is very necessary to explore the financial performance management of enterprises to help them develop better.

Financial performance is the contribution that corporate strategy and its implementation and execution are making to the ultimate operating performance. Financial performance can fully express the effect of cost control, the effect of asset utilization and management, the effect of capital source allocation and the composition of the rate of return on shareholders’ equity. Therefore, financial performance evaluation plays an increasingly important role in enterprise management. Through the exploration and analysis of the enterprise’s financial performance, the factors affecting the enterprise’s financial performance are sorted out, and then specific suggestions are provided for improving the operation level of enterprise’s financial performance. It is helpful for enterprises to find their own positioning, make up for the shortcomings of the financial system, give play to their advantages, and manage their financial performance more accurately. Reasonable and effective financial performance management can provide good development conditions for enterprises, and help them to achieve stable and high-quality economic development.

As enterprises make more and more outstanding contributions in the process of economic development, many scholars have also studied the impact of financial performance management on enterprise development.

Cheng Lamei et al. (2020) took the back-door listing of SF Express as a case study, calculated the EVA value of SF Express group, and used the obtained EVA value to evaluate and analyze the financial performance of SF Express group before and after its listing. Cui Mengyuan, & Huang Qian (2019) established the financial risk early warning model through principal component analysis, and divided the financial risks of 76 enterprises, realized the early warning analysis of the financial risk of enterprises, and established the financial risk early warning index system that can reflect the investment, financing, operation, debt repayment, profit and development ability. Li Hongrui, & Wang Honghai (2020) to extract the 18 port as the research target of financial performance evaluation of listed companies, and global principal component analysis (PCA) is adopted to calculate and comprehensive scores and sorting, based on the analysis of the results of the study and interpretation, and proposes the corresponding improvement strategies, the study for the master port operating conditions which have certain reference significance for the future business decisions. Liu Jinfang, & Duan Ruyue (2020) the text analyzes the new period under the enterprise financial performance evaluation index system on the implementation of the status quo, this paper expounds the new period, the enterprise financial performance indicators evaluation system to carry out the necessity of Liu Xuanting et al. (2020) on the basis of traditional enterprise financial evaluation system, the introduction of low carbon environmental protection related indicators, from two aspects of quantitative and qualitative build financial evaluation index system. Lu Yang, Wang Jingjing, Gao Kaili, & Liu Xiaohui (2019) selected the data of listed companies in Jiangsu Province in 2017, used principal component analysis to quantify the growth of enterprises from four dimensions of profitability, cash flow capacity, operation capacity and development capacity, and analyzed the impact of R&D investment on growth through multiple linear regression. The empirical conclusion shows that the higher the R&D investment intensity, the better the growth of enterprises. Xie Hong, Xue Qianyu, & Zhu Jia-ming (2019) in view of the small and medium-sized enterprise financing problems, to small and medium-sized enterprises in Jiangxi Province as the research object, made a comprehensive assessment of its financing ability and influence factors of quantitative analysis. First of all, from seven aspects to construct the financing capacity of containing 18 indexes evaluation index system, and by using the principal component analysis (PCA) in Jiangxi Province small and medium-sized enterprise financing ability of comprehensive evaluation. Yang Zihui, Wang Rao, Li Han, Zhang Litong, & Wang Jiawei (2016) focused on the construction and influence of principal component analysis on the performance evaluation system of three types of state-owned enterprises. Based on the construction of different evaluation models and the inclusion of macro-economic indicators of the three types of enterprises by principal component analysis, it is found that the comprehensive ranking of economic competitive enterprises and the ranking of the same industry are slightly higher than the other two types of enterprises. Zhao Jinjin (2019) took Tsingtao Beer as an example, analyzed the strategic map of the company and evaluated its financial performance.

Based on the researches of several scholars on enterprise financial performance management evaluation, it is found that there are researches on the influencing factors of enterprise financial performance evaluation and related researches on enterprises in Anhui Province. However, there are relatively few studies on the combination of the two, and few studies on the application of this research idea to listed companies in Anhui Province. Therefore, this paper takes the listed companies in Anhui Province, whose development is not particularly prominent, as the research scope, comprehensively explores the impact of various indicators on the financial performance of listed companies in Anhui Province, and gives relevant suggestions.

In this paper, listed companies in Anhui Province in 2019 were selected as research samples, and appropriate screening was carried out. Enterprises with incomplete data were excluded from the screening conditions, and ST enterprises were deleted. After screening, relevant data of 56 listed companies were finally obtained for research, all of which were from flush software.

The basis of profitability assessment is the growth rate of economic value added (EVA) and sales (profit). EVA is used to replace the previous return on equity, return on total assets, earnings per share and other indicators. The evaluation of enterprise profitability can better reflect the status of net capital income and capital appreciation, which is the development trend of the improvement of enterprise performance evaluation indicators. Use the sales revenue (profit) growth rate index to measure the enterprise growth, namely the ability to develop. Operating capacity can promote enterprises to strengthen asset management, improve the efficiency of asset use, and enhance profitability. The main evaluation indexes include inventory turnover, accounts receivable turnover and fixed assets turnover. The strength of debt paying ability is the main embodiment of the economic strength and financial condition of an enterprise, and it is also an important measure to measure whether an enterprise is operating steadily. The main indicators include asset-liability ratio, current ratio and quick ratio. This article from the profitability, development ability, operation ability and solvency four aspects included 56 the return on net assets, the net interest rate of the total assets of listed companies, sales, gross margin, sales net interest rate, basic earnings per share (year-on-year growth rate), operating income (year-on-year growth rate), operating profit (year-on-year growth rate), accounts receivable turnover, inventory turnover, total assets turnover ratio, current asset turnover and current ratio, quick ratio, cash ratio, asset-liability ratio for the 15 elements such as index, as Table 1.

Excel was used to sort out the collected data, and SPSS was used to process the variable data. The descriptive statistics after the variable processing are shown in Table 2.

The 12 indexes selected in this paper are both relatively independent and correlated to some extent. Table 3 is the correlation coefficient matrix after the normalization of each index.

1) Calculate the correlation coefficient of each index.

2) Calculate the characteristic value and the contribution rate of each main factor.

The eigenvalue λ i is obtained by the vector inner product of the correlation coefficient matrix (R), and the corresponding eigenvector I i j is obtained by the inverse compact transformation. Then the number of principal factors is determined according to the cumulative percentage of eigenvalues and the contribution rate of each principal factor is calculated.

From the flush software.