基于BP神经网络的互联网沪深上市公司财务预警研究

发布时间：2018-05-31 14:35

本文选题：互联网行业 + 财务风险　；参考：《中国地质大学(北京)》2017年硕士论文

【摘要】：随着市场经济的迅猛发展,企业之间的竞争越加激烈,时刻面临着被市场淘汰的威胁。为了在经济市场中谋的一席之地,避免被市场淘汰,企业必须时刻警惕,加强经营财务管理,防止财务风险发生。自从“互联网+”计划在政府报告中提及成为互联网行业快速发展的助力,主要表现为移动互联网、云计算、物联网等与现代工商业、制造业、农业、教育、医疗等的结合,进而推动了电子商务、工业互联网和互联网金融的发展,互联网行业已经成为我国经济发展中不容忽视的一股力量。而互联网企业财务风险的存在极其影响企业的健康、稳定和持续的发展。正是由于互联网行业发展对国民经济的重要性和行业自身的特殊性,构建互联网上市公司财务预警模型便具有其研究价值。本文首先对财务风险和财务预警理论进行阐述,结合我国目前互联网行业的发展状况,分析对互联网行业进行财务预警的必要性;其次,结合互联网经营中“流量”为先、轻资产、低资产负债率、量大额小、轻成本重费用等特点及财务风险的形成原因,构建了互联网沪深上市公司财务预警指标体系;接着,结合BP神经网络相关理论与步骤以及互联网行业特点,构建BP神经网络;然后,选取了我国沪深上市的43家互联网企业作为研究样本,利用SPSS 22统计学软件对指标进行优化,确定预警区间,再通过因子分析法得到得分因子作为预警模型的输入变量,进行样本训练和仿真测试;最后,对预警结果进行分析。
[Abstract]:With the rapid development of market economy, the competition between enterprises is becoming more and more fierce, and they are always facing the threat of being eliminated by the market. In order to seek a place in the economic market and avoid being eliminated by the market, enterprises must always be vigilant, strengthen the management of financial management and prevent the occurrence of financial risks. Since the "Internet" program mentioned in its government report that it has become a driving force for the rapid growth of the Internet industry, mainly in the form of mobile Internet, cloud computing, the Internet of things, and the combination of modern industry and commerce, manufacturing, agriculture, education, health care, etc. Then it promotes the development of electronic commerce, industrial Internet and Internet finance. Internet industry has become a force that can not be ignored in the economic development of our country. And the existence of financial risk of Internet enterprises greatly affects the health, stability and sustainable development of enterprises. It is precisely because of the importance of the development of the Internet industry to the national economy and the particularity of the industry itself that it has its research value to construct the financial early-warning model of the Internet listed companies. In this paper, firstly, the financial risk and financial early warning theory are expounded, and the necessity of financial early warning for the Internet industry is analyzed according to the current situation of the Internet industry in our country; secondly, the "flow" in the Internet operation is the first. Light assets, low asset-liability ratio, large amount and small amount, light cost and heavy expense, and the reasons for the formation of financial risk, the financial early-warning index system of Shanghai and Shenzhen listed companies on the Internet is constructed. Combining with the related theory and steps of BP neural network and the characteristics of Internet industry, the paper constructs BP neural network, then selects 43 Internet enterprises listed in Shanghai and Shenzhen as the research sample, and optimizes the index by using SPSS 22 statistical software. Determine the early warning interval, and then get the score factor as the input variables of the early warning model by factor analysis, and carry on the sample training and simulation test. Finally, the early warning results are analyzed.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F275;F49;F832.51

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