全球证券投资网络结构及关联效应分析

发布时间：2018-01-19 16:24

本文关键词： 全球证券投资网络网络分析关联效应分析　出处：《山西财经大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着全球经济一体化进程的加快,国际资本流动发生了许多新的变化,国家之间、地区之间的证券交流与合作更加频繁密切,全球证券市场走向了新的格局。特别是进入21世纪以来,一国或几国(地区)证券市场的波动在全球证券市场内的传递日益明显,而证券业在金融市场中是举足轻重的,其风险抵抗能力会影响整个金融市场的稳定和国民经济的发展速度。在当前复杂的国际国内经济形势下,对全球证券市场进行结构与关联效应分析,客观评价各国(地区)在全球证券市场中的地位,深度剖析全球证券市场运行的内在规律,了解当前全球证券市场的投资格局,不管是对投资者、还是政策制定者都具有非常重要的现实意义。纵观国内外对全球证券市场的研究,多是孤立的去分析某个国家或某几个国家之间的关系,对全球证券市场的研究并没有形成统一的网络,本文运用前人成熟的理论方法并进行适当地改进,从全局的视角对全球证券投资格局进行分析,探讨2006~2015年全球证券投资网络的结构演化,重点是对全球证券投资网络的关联效应进行分析。首先,本文基于国际货币基金组织(IMF)中BOPS(Balance of Payments Statistics)数据库公布的各国(地区)证券投资与证券负债数据,编制了包括中国大陆在内的全球证券投资流量矩阵(GIFS);其次,基于矩阵GIFS构建了以全球各国(地区)为节点,国家之间、地区之间的证券交易流量为权边的全球证券投资网络,并使用网络分析指标对网络的特征进行了分析;最后,建立全球证券投资网络关联乘数模型,分析一个或几个国家(地区)证券投资或证券负债变动对其他地区的冲击,把握不同节点国家(地区)证券市场间的复杂关系与相互影响。基于上述研究,本文得出以下结论:美国、日本、卢森堡、爱尔兰和英国在全球证券市场上位于核心的位置,五国之间的证券交易最为紧密,控制着全球主要的证券投资流量,且这些国家的证券投资发生变动时,对其他国家(地区)的影响巨大。西班牙、意大利、中国香港、加拿大、法国等国家(地区)虽然在全球证券投资中起到一定的作用,但是与核心位置的国家(地区)相比,作用就相形见拙。
[Abstract]:With the acceleration of the process of global economic integration, many new changes have taken place in the international capital flow, and the securities exchanges and cooperation between countries and regions are more frequent and closer. The global securities market has moved towards a new pattern, especially since 21th century, the volatility of the securities market of one or several countries (regions) has become increasingly obvious in the global securities market. The securities industry plays an important role in the financial market, its risk resistance will affect the stability of the entire financial market and the development of the national economy, in the current complex international and domestic economic situation. This paper analyzes the structure and correlation effect of the global securities market, evaluates objectively the position of each country (region) in the global securities market, and deeply analyzes the inherent law of the operation of the global securities market. It is very important for investors and policy makers to understand the current investment pattern of the global securities market. Most are isolated to analyze the relationship between a country or a few countries, the research on the global securities market has not formed a unified network, this paper uses the previous mature theoretical methods and appropriate improvement. This paper analyzes the global securities investment pattern from the overall perspective and discusses the structural evolution of the global securities investment network from 2006 to 2015. The key point is to analyze the correlation effect of global securities investment network. First of all. This article is based on the countries (regions) published in the BOPS(Balance of Payments Statistics database of the International Monetary Fund (IMF). Data on securities investment and securities liabilities. The global portfolio investment flow matrix including mainland China is compiled. Secondly, based on matrix GIFS, the paper constructs a global securities investment network which takes the global countries (regions) as the nodes and the securities exchange flows between countries and regions as the right side. The characteristics of the network are analyzed by using the network analysis index. Finally, a global portfolio investment network correlation multiplier model is established to analyze the impact of one or more countries (regions) on the impact of securities investment or securities liabilities on other regions. Based on the above research, this paper draws the following conclusions: the United States, Japan, Luxembourg. Ireland and the United Kingdom are at the core of the global securities market, with the five countries trading the most closely, controlling the world's major portfolio investment flows, and when these countries' portfolio investment changes. Spain, Italy, Hong Kong, China, Canada, France and other countries (regions) play a role in global portfolio investment. But compared with the core countries (regions), the role is dwarfed.
【学位授予单位】：山西财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F831.51

【参考文献】