基于BP神经网络的我国海外矿业投资金融风险预警分析

WARNING OF FINANCIAL RISKS OF CHINA'S OVERSEAS MINING INVESTMENT BASED ON BP NEURAL NETWORK

首先对海外矿业投资的金融风险因素进行了识别,并结合Delphi法建立了相应的评价指标体系,然后应用BP神经网络模型对海外矿业投资的主要投资目的国进行预警分析。结果表明,在未来几年中加拿大、俄罗斯、澳大利亚的风险预警程度中等,巴西、印度与南非的风险预警程度较差,其中南非的经济发展状况较差,印度的国际收支状况、通胀率与财政收支状况较差,巴西的实际贷款利率过高。我国企业可以考虑在风险预警程度较轻的国家进行海外矿业投资。

In order to warn the financial risks of China＇s overseas mining investment, this paper identifies the financial risks, and combines with Delphi to establish an index system to warn the financial risks in China＇s major overseas mining investing countries by means of BP neural network. The resuh implies a moderate warning in Canada, Russia and Australia, and a higher warning in Brazil, India and South Africa. South Africa has a bad economy; India is poor in global income-expenditure, inflation rate and fiscal income; and Brazil is higher in its loan rate. Chinese investors may consider entrance into the countries with a less warning.