基于SVAR模型的大数据技术在信托业发展中的应用研究

Xiaoyuan Zhang, Jing Qin
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摘要

摘要:信托业作为中国金融体系的重要组成部分,已经发展成为金融投资行业的先锋。信托资产规模从2000年的1000亿元增长到2017年峰值的26.25万亿元,发展速度惊人。而且,信托业的业务模式早已从单一的存贷款业务向多元化发展转变,不仅弥补了传统金融机构无法覆盖的实体经济领域,而且现在已经发展出符合中国国情的新的阶段性模式,如家族信托、房地产信托和投资基金等。本文首先分析了信托业发展与中国GDP增长的关系。然后,通过设置条件约束的Cholesky分解、脉冲响应函数和方差分解,利用信任规模和宏观经济数据建立SVAR结构的向量自回归模型,论证了信任对中国经济增长的促进作用。最后得出结论,在国家控制非标资产和中美贸易战的背景下,信托机构快速转型以满足市场创新需求既是历史机遇,也是构建自身核心竞争力的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Application of Big Data Technology Based on SVAR Model in the Development of Trust Industry
Abstract: The trust industry, as an important part of China's financial system, has developed into the vanguard of the financial investment industry. Trust assets have grown from 100 billion yuan in 2000 to 26.25 trillion yuan at the peak in 2017, with an amazing development speed. Moreover, the business model of trust industry has long changed from single deposit and loan business to diversified development, which not only makes up for the real economy field that cannot be covered by traditional financial institutions, but has now developed new phased models in line with China's national conditions, such as family trust and real estate trust and investment fund. In this paper, firstly, the relationship between the development of trust industry and China's GDP growth is analyzed. Then, the promotion effect of trusts on economic growth in China was demonstrated by establishing a vector autoregressive model of SVAR structure using trust size and macroeconomic data by means of Cholesky decomposition with setting condition constraints, pulse response function and variance decomposition. Finally, the conclusion was drawn that under the background of national control of non-standard assets and Sino-US trade war, the trust institution's rapid transformation to meet the market's innovation demand is not only a historic opportunity, but also the key to build its own core competitiveness.
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