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英文标题：
《Systemic Risk Identification, Modelling, Analysis, and Monitoring: An
  Integrated Approach》
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作者：
Antoaneta Sergueiva
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最新提交年份：
2013
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英文摘要：
  Research capacity is critical in understanding systemic risk and informing new regulation. Banking regulation has not kept pace with all the complexities of financial innovation. The academic literature on systemic risk is rapidly expanding. The majority of papers analyse a single source or a consolidated source of risk and its effect. A fraction of publications quantify systemic risk measures or formulate penalties for systemically important financial institutions that are of practical regulatory relevance. The challenges facing systemic risk evaluation and regulation still persist, as the definition of systemic risk is somewhat unsettled and that affects attempts to provide solutions. Our understanding of systemic risk is evolving and the awareness of data relevance is rising gradually; this challenge is reflected in the focus of major international research initiatives. There is a consensus that the direct and indirect costs of a systemic crisis are enormous as opposed to preventing it, and that without regulation the externalities will not be prevented; but there is no consensus yet on the extent and detail of regulation, and research expectations are to facilitate the regulatory process. This report outlines an integrated approach for systemic risk evaluation based on multiple types of interbank exposures through innovative modelling approaches as tensorial multilayer networks, suggests how to relate underlying economic data and how to extend the network to cover financial market information. We reason about data requirements and time scale effects, and outline a multi-model hypernetwork of systemic risk knowledge as a scenario analysis and policy support tool. The argument is that logical steps forward would incorporate the range of risk sources and their interrelated effects as contributions towards an overall systemic risk indicator, would perform an integral analysis of ...
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中文摘要：
研究能力对于理解系统性风险和告知新监管至关重要。银行监管没有跟上金融创新的所有复杂性。关于系统性风险的学术文献正在迅速扩展。大多数论文分析了单一风险源或综合风险源及其影响。一小部分出版物量化了系统性风险度量，或为具有实际监管相关性的系统重要性金融机构制定了惩罚措施。系统性风险评估和监管面临的挑战仍然存在，因为系统性风险的定义有些不确定，这影响了提供解决方案的尝试。我们对系统性风险的理解正在演变，对数据相关性的认识正在逐步提高；这一挑战反映在主要国际研究举措的重点上。人们一致认为，与预防系统性危机相比，系统性危机的直接和间接成本都是巨大的，没有监管，外部性就无法预防；但在监管的范围和细节上还没有达成共识，研究期望能够促进监管过程。本报告概述了系统性风险评估的综合方法，该方法基于多种类型的银行间风险敞口，通过张力多层网络等创新建模方法，建议如何关联基础经济数据，以及如何扩展网络以涵盖金融市场信息。我们考虑了数据需求和时间尺度效应，并概述了系统风险知识的多模型超网络，作为情景分析和政策支持工具。其论点是，合乎逻辑的前进步骤将纳入风险源的范围及其相互关联的影响，作为对整体系统性风险指标的贡献，将对。。。
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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关键词：系统性风险 系统性 Applications Quantitative Contribution