大数据与金融分析框架的完善

传统金融分析框架受制于古典经济学的理论缺陷,难以对现代金融体系的运行规律及其风险特征进行准确的描述与分析。大数据理念和技术的发展为金融分析框架的完善提供了重要契机,其应用可以从以下三方面提高金融风险分析的前瞻性和有效性:在方法论方面,从海量数据中“归纳”出整个金融网络的动态全貌,以更好地理解金融风险的形成和传播路径;在金融风险识别方面,前瞻性地捕捉微观主体的行为特征、资金异动、特殊关联结构与金融风险之间的关系;在系统性风险防范方面,精准刻画金融网络中的重要节点、“涌现”特征以及演进态势,以助力对重大风险源的及时识别、监测与处置。

The effectiveness of traditional financial analysis is limited by flaws in the theoretic framework of Classical Economics.It fails to accurately describe and analyze the principal characteristics of the modern financial system.The development of Big Data has created an opportunity for the improvement of the financial analysis framework,enhancing the effectiveness of risk analysis.In terms of methodology,rather than following the rigid and unrealistic assumptions of the Classical Framework,Big Data analysis seeks to understand the financial network based on its own characteristics,so that the formation and transmission of financial risks could be accurately understood.In terms of financial risk identification,Big Data analysis focuses on the behavioral characteristics of market participants,abnormal cash flow patterns and special structural relationships.In terms of identifying and monitoring systemic risk,Big Data analysis focuses on risk characteristics of important nodes in the financial framework,patterns of“network emergence”,and structural characteristics of the financial system.