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1.
动态银行网络系统中系统性风险定量计算方法研究 总被引：2，自引：0，他引：2
采用复杂网络理论研究银行网络系统中的系统性风险问题已有较多的报道.这些研究大多假设银行网络系统是静态的(银行节点是静态的,银行节点间的借贷关系也是静态的),然后在系统性风险已经累积到爆发的情况下,研究风险爆发后,风险在静态网络系统中的传染与网络结构的关系.然而对于系统性风险如何在银行网络中累积直至爆发的问题的研究还很少.系统风险的累积过程需在动态演化的银行网络系统中才能实现,同时观察风险累积过程需对系统风险进行定量估算.因此,本文首先建立带有宏观经济趋势及多期清算的动态银行网络系统模型;提出系统风险的定量计算方法;最后对系统风险进行仿真计算与分析,得到了系统风险变化曲线,显示了系统风险累积的过程.该研究为定量研究动态银行网络系统的风险累积问题奠定了基础. 相似文献
2.
Qianqian Gao 《Entropy (Basel, Switzerland)》2022,24(9)
Global financial systems are increasingly interconnected, and risks can spread more easily, potentially causing systemic risks. Research on systemic risk based on multi-layer financial networks is relatively scarce, and studies usually focus on only one type of risk. This paper develops a model of the multi-layer financial network system based on three types of links: firm-bank credit, asset-bank portfolio, and interbank lending, which simulates systemic risk under three risk sources: firm credit default, asset depreciation, and bank bankruptcy. The impact of the multi-layer financial network structure, default risk threshold, and bank asset allocation strategy is further explored. It has been shown that the larger the risk shock, the greater the systemic risk under different risk sources, and the risk propagation cycle tends to rise and then decline. As centralized nodes in the multi-layer financial network system, bank nodes may play both blocking and propagation roles under different risk sources. Furthermore, the multi-layer financial network system is most susceptible to bank bankruptcy risk, followed by firm credit default risk. Further research indicates that increasing the average degree of firms in the bank–firm credit network, the density of the bank-asset portfolio network, and the bank capital adequacy ratio all contribute to reducing systemic risk under the three risk sources. Additionally, the more assets a bank holds in a single market, the more vulnerable it is to the risks associated with that market. 相似文献
3.
银行风险传导研究是系统性金融风险测度与防范的重点.文献中主要研究静态银行网络拓扑结构和银行系统性风险量化,较少考虑银行网络之间的状态转变.针对上述问题,提出时变状态网络模型.根据模型,首先用kmeans方法对各个时间段的银行网络分类,然后通过有向最小生成树(DMST, directed minimum spanning tree)分析每一类银行网络的拓扑结构,最后联合利用平面最大过滤图(PMFG, planar maximally filtered graph)方法构建时变银行状态网络,该网络可用作银行风险源头的寻找和传导时变性分析.利用时变状态网络模型研究我国15家上市商业银行2007年第四季度到2019第一季度同业拆借数据.结果表明,银行状态网络之间的短期连续跳跃性可有效描述金融危机的发生,比如2008年全球金融危机发生前后出现了两个状态间的短期跳跃,从2013年\"钱荒\"到2015年的股灾阶段,先后出现了四个状态间的短期跳跃.同时,各个有向银行状态网络的出度和传染效应成正比,入度和银行面临风险的稳健程度成反比.时序的银行状态网络具有记忆性特征,这可以为央行防范系统性风险提供决策依据. 相似文献
4.
基于元胞自动机的复杂信息系统安全风险传播研究 总被引：2，自引：0，他引：2
基于元胞自动机建立复杂信息系统安全风险传播模型, 研究复杂信息系统安全风险在最近邻耦合网络、 随机网络, Watts-Strogatz 小世界网络和Barabasi-Albert无标度网络 四种网络拓扑下的传播问题. 通过研究安全风险传播模型在四种网络拓扑下安全风险的传播阈值, 与现有的传播阈值研究成果进行比较, 验证模型的正确性, 并分析验证网络拓扑结构中度分布的异质化程度越高传播阈值越小的结论. 通过对安全风险的传播演化趋势进行研究, 分析验证网络度分布的异质化程度越高、安全风险影响范围越小、传播速度越快的结论, 并指出度分布的异质化程度越高、模型后期的免疫机制对控制安全风险传播的效果越缓慢. 通过对安全风险在传播最早期就趋于消亡的情况进行研究, 分析得出安全风险在传播之初就趋于消亡的消亡率与传播率之间呈现近似负指数的关系, 并且初期的感染源越多安全风险的消亡率越低. 分析了影响复杂信息系统安全风险传播的关键要素, 对复杂信息系统中安全风险传播的控制具有指导作用.关键词：复杂信息系统复杂网络安全风险传播元胞自动机 相似文献
5.
Karime Chahun-Jimnez Rolando Rubilar Hanns de la Fuente-Mella Víctor Leiva 《Entropy (Basel, Switzerland)》2021,23(1)
In this research, statistical models are formulated to study the effect of the health crisis arising from COVID-19 in global markets. Breakpoints in the price series of stock indexes are considered. Such indexes are used as an approximation of the stock markets in different countries, taking into account that they are indicative of these markets because of their composition. The main results obtained in this investigation highlight that countries with better institutional and economic conditions are less affected by the pandemic. In addition, the effect of the health index in the models is associated with their non-significant parameters. This is due to that the health index used in the modeling would not determine the different capacities of the countries analyzed to respond efficiently to the pandemic effect. Therefore, the contagion is the preponderant factor when analyzing the structural breakdown that occurred in the world economy. 相似文献
6.
The major issue in the evolution of housing prices is risk of housing price contagion. To model this issue, we constructed housing multilayer networks using transfer entropy, generalized variance decomposition, directed minimum spanning trees, and directed planar maximally filtered graph methods, as well as China’s comprehensive indices of housing price and urban real housing prices from 2012 to 2021. The results of our housing multilayer networks show that the topological indices (degree, PageRank, eigenvector, etc.) of new first-tier cities (Tianjin, Qingdao, and Shenyang) rank higher than those of conventional first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzheng). 相似文献
7.
Miguel Rebollo Rosa María Benito Juan Carlos Losada Javier Galeano 《Entropy (Basel, Switzerland)》2021,23(5)
The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society’s resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. The results are compared with the pilot project’s impact testing of the Spanish contact tracing app (RadarCOVID). The paper also depicts the results combining both strategies: contact tracing to detect potential infections and risk maps to avoid movements into conflictive areas. Although some works affirm that contact tracing apps need 60% of users to control the propagation, our results indicate that a 40% could be enough. On the other hand, the elaboration of risk maps could work with only 20% of active installations, but the effect is to delay the propagation instead of reducing the contagion. With both active strategies, this methodology is able to significantly reduce infected people with fewer participants. 相似文献
8.
We find numerical and empirical evidence for dynamical, structural and topological phase transitions on the (German) Frankfurt Stock Exchange (FSE) in the temporal vicinity of the worldwide financial crash. Using the Minimal Spanning Tree (MST) technique, a particularly useful canonical tool of the graph theory, two transitions of the topology of a complex network representing the FSE were found. The first transition is from a hierarchical scale-free MST representing the stock market before the recent worldwide financial crash, to a superstar-like MST decorated by a scale-free hierarchy of trees representing the market’s state for the period containing the crash. Subsequently, a transition is observed from this transient, (meta)stable state of the crash to a hierarchical scale-free MST decorated by several star-like trees after the worldwide financial crash. The phase transitions observed are analogous to the ones we obtained earlier for the Warsaw Stock Exchange and more pronounced than those found by Onnela–Chakraborti–Kaski–Kertész for the S&P 500 index in the vicinity of Black Monday (October 19, 1987) and also in the vicinity of January 1, 1998. Our results provide an empirical foundation for the future theory of dynamical, structural and topological phase transitions on financial markets. 相似文献
9.
作为经济物理学的一个重要专题,文章简要介绍了金融风险管理的基本框架和主要内容,包括风险界定、风险来源、风险度量、风险处置等.特别地,展示了物理学在金融风险管理中的可能应用,讨论了物理学家对金融风险管理可能做出的贡献. 相似文献
10.
作为经济物理学的一个重要专题,文章简要介绍了金融风险管理的基本框架和主要内容,包括风险界定、风险来源、风险度量、风险处置等.特别地,展示了物理学在金融风险管理中的可能应用, 讨论了物理学家对金融风险管理可能做出的贡献. 相似文献
11.
We introduce simplicial persistence, a measure of time evolution of motifs in networks obtained from correlation filtering. We observe long memory in the evolution of structures, with a two power law decay regimes in the number of persistent simplicial complexes. Null models of the underlying time series are tested to investigate properties of the generative process and its evolutional constraints. Networks are generated with both a topological embedding network filtering technique called TMFG and by thresholding, showing that the TMFG method identifies high order structures throughout the market sample, where thresholding methods fail. The decay exponents of these long memory processes are used to characterise financial markets based on their efficiency and liquidity. We find that more liquid markets tend to have a slower persistence decay. This appears to be in contrast with the common understanding that efficient markets are more random. We argue that they are indeed less predictable for what concerns the dynamics of each single variable but they are more predictable for what concerns the collective evolution of the variables. This could imply higher fragility to systemic shocks. 相似文献
12.
一个科研合作网的双粒子图自适应演化模型 总被引：14，自引：0，他引：14
建议一个描述研究项目负责人与研究助手之间的科研合作网络的双粒子图自适应发展模型.模型考虑每个项目负责人或研究助手作为作用者采取的选择、决策、竞争以及由此导致的自身和整个网络的进化.对模型的各种不同投影单粒子图进行的数值模拟所得结果都与美国的数学和神经科学工作者在1991-1998年间合作的统计结果很好地符合,说明自适应复杂网络可以自组织向小世界、无标度的结构.也讨论了双粒子图的不同投影单粒子图模拟所得结果的异同.关键词：复杂网络复杂自适应系统科研合作网双粒子图 相似文献
13.
The principle that ‘the brand effect is attractive’ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general framework that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general,the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes’ properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment,the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model. 相似文献
14.
A causality analysis aims at estimating the interactions of the observed variables and subsequently the connectivity structure of the observed dynamical system or stochastic process. The partial mutual information from mixed embedding (PMIME) is found appropriate for the causality analysis of continuous-valued time series, even of high dimension, as it applies a dimension reduction by selecting the most relevant lag variables of all the observed variables to the response, using conditional mutual information (CMI). The presence of lag components of the driving variable in this vector implies a direct causal (driving-response) effect. In this study, the PMIME is appropriately adapted to discrete-valued multivariate time series, called the discrete PMIME (DPMIME). An appropriate estimation of the discrete probability distributions and CMI for discrete variables is implemented in the DPMIME. Further, the asymptotic distribution of the estimated CMI is derived, allowing for a parametric significance test for the CMI in the DPMIME, whereas for the PMIME, there is no parametric test for the CMI and the test is performed using resampling. Monte Carlo simulations are performed using different generating systems of discrete-valued time series. The simulation suggests that the parametric significance test for the CMI in the progressive algorithm of the DPMIME is compared favorably to the corresponding resampling significance test, and the accuracy of the DPMIME in the estimation of direct causality converges with the time-series length to the accuracy of the PMIME. Further, the DPMIME is used to investigate whether the global financial crisis has an effect on the causality network of the financial world market. 相似文献
15.
Modeling the information of social contagion processes has recently attracted a substantial amount of interest from researchers due to its wide applicability in network science, multi-agent-systems, information science, and marketing. Unlike in biological spreading, the existence of a reinforcement effect in social contagion necessitates considering the complexity of individuals in the systems. Although many studies acknowledged the heterogeneity of the individuals in their adoption of information, there are no studies that take into account the individuals’ uncertainty during their adoption decision-making. This resulted in less than optimal modeling of social contagion dynamics in the existence of phase transition in the final adoption size versus transmission probability. We employed the Inverse Born Problem (IBP) to represent probabilistic entities as complex probability amplitudes in edge-based compartmental theory, and demonstrated that our novel approach performs better in the prediction of social contagion dynamics through extensive simulations on random regular networks. 相似文献
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17.
随着网络服务的发展,社交网络逐渐成为信息传播的新媒介.因此,研究网络舆情演化具有重要意义和实用价值.为了更好地研究网络舆论,在信息熵的基础上,提出了一个社交网络观点演化模型.此模型存在以下两个特点:一是可以反映个体面对正负两种观点趋向做出抉择时的心理过程;二是可以反映个体形成新观点时主观因素和客观因素的影响.在仿真实验中,讨论了舆论环境对个体观点演化的影响,初始观点和自信度对观点演化的影响,以及意见领袖对群体观点演化的影响.实验结果表明,该模型可以反映真实社交网络中个体的心理学特征,比如个体的观点形成会受到舆论环境的影响,自信的个体不愿意接受他人的观点,当意见领袖存在时群体的观点会受到影响等. 相似文献
18.
基于一个普适性的灾害蔓延动力学模型,在三种网络拓扑结构(随机网、小世界网和无标度网)下,仿真分析了网络中心性对灾害蔓延速度和扩散趋势的影响.通过改变初始蔓延条件来分析网络初始状态对蔓延效率的影响,并着重讨论了在四种初始崩溃节点选取策略下灾害蔓延最终状态的差异.结果表明:对于四种攻击策略,网络最终状态有着明显的差异,网络对随机攻击具有较强的抵御能力,而对于目标,攻击却显示较强的脆弱性,或许,三种网络表现出不同的脆弱程度.最后,在一个实际网络上对理论分析结果进行了验证. 相似文献
19.
SARS疫情分析及对北京疫情走势的预测 总被引：5，自引：0，他引：5
在考虑每个SARS病人每日平均传染概率和他的直接传染的平均期限的基础上，建立了一个统计分析模型．分析表明，每个病人可以造成直接感染他人的期限平均在20天左右，这个值在不同地区和不同疫情阶段似乎变化不大．病人的平均每天感染率与社会状况有关，在疫情爆发期较大，在疫情控制期要小很多．北京后期如果控制在香港后期的感染率水平上，则有望在6月上中旬下降到日增几例．然后再经过约一个月，即7月上中旬达到日增0病例，而累积总病例数将达到3100多．但如果北京的新病例下降速度与广东类似的话，则要再多花至少一个月，才能达到上述的效果，且累积总病例数会达到3800左右． 相似文献
20.
The interdependence of financial institutions is primarily responsible for creating a systemic hierarchy in the industry. In this paper, an Adaptive Hierarchical Network Model is proposed to study the problem of hierarchical relationships arising from different individuals in the economic domain. In the presented dynamically evolving network model, new directed edges are generated depending on the existing nodes and the hierarchical structures among the network, and these edges decay over time. When the preference of nodes in the network for higher ranks exceeds a certain threshold value, the equality state in the network becomes unstable and rank states emerge. Meanwhile, we select four real data sets for model evaluation and observe the resilience in the network hierarchy evolution and the differences formed by different patterns of hierarchy preference mechanisms, which help us better understand data science and network dynamics evolution. 相似文献