Please wait a minute...
文章检索
复杂系统与复杂性科学  2018, Vol. 15 Issue (1): 38-44    DOI: 10.13306/j.1672-3813.2018.01.006
  本期目录 | 过刊浏览 | 高级检索 |
国际资本流动网络复杂性研究的总体框架
应尚军, 纪小妹, 吴婷婷
上海对外经贸大学金融管理学院,上海 201620
The General Framework on the Complexity of International Capital Flow Network
YING Shangjun, JI Xiaomei, WU Tingting
School of Finance,Shanghai University of International Business and Economics, Shanghai 201620,China
全文: PDF(901 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 围绕国际资本流动网络复杂性的研究范式、研究方法和研究工具对现有学术文献进行了综述和展望。研究表明,基于离散空间网络的复杂性科学研究范式非常适合国际资本流动网络复杂性研究。“复杂离散网络构建——系统演化——输入输出关系分析——决策建议”这一流程可以很好地融合在研究流程之中。同属国际资金交互网络的国际贸易资金流动网络构建及其拓扑结构分析,可在数据可获得性越来越高的背景下应用于国际资本流动网络复杂性的研究中。经过对网络节点和邻居模式的拓展,新定义的广义元胞自动机模型可以作为承担国际资本流动网络演化及参数计算的有力工具。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
应尚军
纪小妹
吴婷婷
应尚军
纪小妹
吴婷婷
关键词 国际资本流动复杂网络复杂性元胞自动机    
Abstract:Reviews and prospects the existing academic literature in terms of research paradigms, research methods and research tools on the complexity of international capital flow network. Studies show that the research paradigm ofcomplexity science based on discrete spatial network is pretty suitablefor the research on the complexity of international capital flow network. And the procedure, consisting of "construction of complex discrete network—system evolution—relationship analysis on input and output—proposals fordecision making ", can work quite well while doing this research. Besides, the construction and topological structure analysis of international trade capital flow network, which also belongs to international fund interactive network, could be applied to the research on the complexity of international capital flow network in the context of increasing data availability. And after the expansion on network node and neighbor mode, the newly defined generalized cellular automaton model could be used as a powerful tool for evolution and parameter calculation of international capital flow network.
Key wordsinternational capital flow    complex network    complexity    cellular automaton
收稿日期: 2018-01-09      出版日期: 2019-01-10
:  F830.9  
  N949  
基金资助:国家自然科学基金(71571116);国家社会科学基金青年项目(16CGJ006)
作者简介: 应尚军(1974),男,浙江淳安人,博士,教授,主要研究方向为金融复杂系统、资产定价、项目管理。
引用本文:   
应尚军, 纪小妹, 吴婷婷. 国际资本流动网络复杂性研究的总体框架[J]. 复杂系统与复杂性科学, 2018, 15(1): 38-44.
YING Shangjun, JI Xiaomei, WU Tingting. The General Framework on the Complexity of International Capital Flow Network[J]. Complex Systems and Complexity Science, 2018, 15(1): 38-44.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2018.01.006      或      https://fzkx.qdu.edu.cn/CN/Y2018/V15/I1/38
[1]Schweiter F, Fagiolo G, Sornette D, et al. Economic networks: the new challenges[J]. Science, 2009, 325(5939):422425.
[2]米歇尔·沃尔德罗普.复杂——诞生于秩序与混沌边缘的科学[M]. 陈玲.北京:生活·读书·新知三联书店, 1997.
[3]张维, 武自强, 张永杰,等. 基于复杂金融系统视角的计算实验金融:进展与展望[J]. 管理科学学报, 2013, 16(6):8594.
Zhang W, Wu Z Q, Zhang Y J, et. al.Agent-based computational financeon complex financial system perspective: progress and prospects[J].Journal of Management Sciences in China, 2013, 16(6):8594.
[4]应尚军, 范英. 股票市场的演化与复杂[M]. 北京: 经济管理出版社, 2013.
[5]Schelling T C. Dynamic models of segregation[J]. Journal of Mathematical Sociology, 1971, 1:143186.
[6]Erdosn P andPalka Z. Trees in random graphs[J]. Diserete Mathematies, 1983, 46(2):145150.
[7]Holland J H. Adaptation in Natural and Artificial Systems[M]. Cambridge, MA: MIT Press, 1992.
[8]Dawid H. Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models[M]. Heidelberg: Springer Verlag, 1996.
[9]Epstein J M, Axtell R. Growing Artificial Societies from the Bottom Up[M]. Cambridge, Ma: Mit Press, 1996.
[10] Watts D J, Strogatz S H. Collective dynamics of small-world networks[J]. Nature, 1998, (393):440442.
[11] Barabasi A L, Albert R. Emergence of sealing in random networks[J]. Science, 1999, (286):509512.
[12] 王维红. 国际贸易网络中金融危机跨国传播:基于复杂网络理论[D]. 上海:东华大学, 2012.
Wang W H. Financial crisis propagation in international trade network: based on complex network theory[D]. Shanghai: Donghua University,2012.
[13] Callaway D S, Newman M E, Steven H S, et. al. Network robustness and fragility: percolation on random graphs[J]. Physical Review Letters, 2000, 85(5):54685471.
[14] Vragovic I, Louis E, Diaz-Guilera A. Efficiency of informational transfer in regular and complex networks[J]. Phys E, 2005, 71(3): 19.
[15] 任小叶. 基于复杂网络的金融市场建模方法研究[D]. 合肥:中国科技大学博士学位论文, 2013.
Ren Xiaoye. Research on financial market modeling based on complex networks[D]. Hefei: University of Science and Technology of China, 2013.
[16] 崔迪. 群落结构的复杂网络及其交通行为的研究[D]. 北京:北京交通大学, 2009.
Cui Di. Studies on complex networks with community structure and its traffic behavior[D].Beijing: Beijing Jiaotong University, 2009.
[17] 李勇. 复杂网络理论与应用研究[D]. 广州: 华南理工大学, 2005.
Li Yong. Researches on the theory and application of complex network[D]. Guangzhou: South China University of Technology, 2005.
[18] Newman M E. The structure and function of complex networks[J]. SIAM Review, 2003, (45):167256.
[19] Ji Q, Zhang H Y, Fan Y. Identification of global oil trade patterns: an empirical research based on complex network[J]. Theory Energy Conversion and Management, 2014, (85):856865.
[20] 程淑佳, 赵映慧, 李秀敏. 基于复杂网络理论的原油贸易空间格局差异分析[J]. 中国人口资源与环境, 2013, 23(8):2025.
Cheng S J, Zhao Y H, Li X M. Differences in spatial pattern of main nations’ crude oil trade on complicated network theory[J]. China Population, Research and Environment, 2014, (85):856865.
[21] 杨鑫, 安海忠, 高湘昀. 国际天然气贸易关系网络结构特征研究:基于复杂网络理论[J]. 资源与产业, 2012, 14(2):8187.
Yang Xin, An Haizhong, Gao Xiangyun. Structural features of global gas trading relationship network based on complex network theory[J]. Resources & Industries, 2012, 14(2):8187.
[22] 郝晓晴, 安海忠, 陈玉蓉,等. 基于复杂网络的国际铁矿石贸易演变规律研究[J]. 经济地理, 2013, 33(1):9297.
Hao Xiaoqing, An Haizhong, Chen Yurong, et al. Research on evolution of international iron ore trade based on complex network theory[J]. Economic Geography, 2013, 33(1):9297.
[23] 傅庆玲, 石海佳, 李杨,等. 复杂网络视角的有机化学品国际贸易分析[J]. 广州化工, 2013, 41(12):17.
Fu Q L, Shi H J, Li Y, et. al. Network analysis of global organic chemicals trade[J].Guangzhou Chemical Industry, 2013, 41(12):17.
[24] 任素婷, 崔雪峰, 樊瑛. 复杂网络视角下中国国际贸易地位的探究[J]. 北京师范大学学报(自然科学版), 2013, 49(1):9095.
Ren Suting, Cui Xuefeng, Fan Ying. Analysis of china’s position in international trade based on a complex network perspective[J]. Journal of Beijing Normal University (Natural Science), 2013, 49(1):9095.
[25] Kali R, Reyes J. Financial Contagion on the International Trade Network[J]. Economic Inquiry, 2010, 48(4):10721101.
[26] Ercsey-Ravasz M, Toroczkai Z, Lakner Z, et al. Complexity of the International Agro-Food Trade Network and Its Impact on Food Safety[J]. PLoS ONE, 2012, 7(5):18.
[27] Mahutga M C. The persistence of structural inequality—A network analysis of international trade 19652000[J]. Social Force, 2006, 84(4):18631889.
[28] 程淑佳, 王肇钧. 复杂网络理论下世界原油贸易空间格局演进研究[J]. 地理科学, 2011, 31(11):13421348.
Cheng Shujia, Wang Zhaojun. Evolution of spatial pattern of world crude oil trade based on complicated network theory[J].ScientiaGeographicaSinica, 2011, 31(11):13421348.
[29] Ruzzenenti F, Garlaschelli D, Basosi R. Complex networks and symmetry II: reciprocity and evolution of world trade[J]. Symmetry, 2010, (2): 17101744.
[30] 曹监平, 晁静. 国际资本流动的政治经济学分析—基于全球生产网络的视角[J]. 郑州师范教育, 2013, 2(1):9296.
Cao Jianping, Chao Jing. Political economy analysis of international capital flows: a perspective from international production network[J]. Journal of Zhengzhou Normal Education, 2013, 2(1):9296.
[31] Arthur W B, Durlauf S N. The Economy as an Evolving Complex System Ⅱ[M]. New Jersey: AddisonWesley, 1997.
[32] 应尚军,魏一鸣,蔡嗣经.元胞自动机及其在经济学中的应用[J].中国管理科学,2000,(11):272278.
Ying Shangjun, Wei Yiming, Cai Sijing. On cellular automata and its application to economics[J]. Chinese Journal of Management Science, 2000,(11):272278.
[33] 应尚军,魏一鸣,蔡嗣经.基于元胞自动机的股票市场投资行为模拟[J].系统工程学报,2001,16(5):382388.
Ying Shangjun, Wei Yiming, Cai Sijing. Cellular automata based behavior simulation of stock market investment[J]. Journal of Systems Engineering, 2001,16(5):382388.
[34] Wei Y M, Ying S J, Fan Y, et.al. The cellular automaton model of investment behavior in the stock market[J]. Physica A: Statistical Mechanics and Its Applications, 2003, 325(3/4):507516.
[35] 应尚军, 魏一鸣, 范英,等. 基于元胞自动机的股票市场复杂性研究——投资者心理与市场行为[J]. 系统工程理论与实践, 2003, 23(12):1824.
Ying Shangjun, Wei Yiming, Fan Ying, et al. Study on complexity of stock market based on cellular automata[J]. Systems Engineering-Theory & Practice, 2003, 23(12):1824.
[36] 应尚军. 矿业资本市场复杂性研究[D]. 北京科技大学博士学位论文, 2003.
Ying Shangjun. Research on complexity of mining capital market[D].University of Science and Technology BeijingPhD dissertations, 2003.
[37] 应尚军, 范英, 魏一鸣, 等. 基于投资分析的股票市场演化元胞自动机模型[J]. 管理评论, 2004, 16(11):49.
Ying Shangjun, Fan Ying, Wei Yiming, et. al. An investment analysis based cellular automaton model for evolving simulation in stock market[J]. Management Review, 2004, 16(11):49.
[38] Fan Y, Ying S J, Wang B H, et. al. The effect of investor psychology on the complexity of stock market: an analysis based on cellular automaton model[J]. Computers & Industrial Engineering, 2009, 56(1):6369.
[39] 应尚军, 唐瑞, 蔡嗣经. 股票市场的外部因素与市场均衡[J]. 合肥工业大学学报, 2006, (9):11061110.
Ying Shangjun, Tang Rui, Cai Sijing. Relationship between outside factors and market equilibrium in stock markets[J]. Journal of Hefei University of Technology, 2006, (9):11061110.
[40] 应尚军, 范英, 魏一鸣. 单支股票市场的元胞自动机模型及其动力学研究[J]. 系统工程, 2006, 24(7):3136.
Ying Shangjun, Fan Ying, Wei Yiming. A CA model for single stock market and its dynamical analysis[J]. Systems Engineering, 2006, 24(7):3136.
[41] 应尚军. 沪深股市动力学特征及其与从众心理的关系研究[J]. 中国管理科学, 2012, 20(专辑):439444.
Ying S J. Study on dynamic characteristics of Chinese stock market and its relationship with imitation psychology[J].Chinese Journal of Management Science, 2012, 20(Special Issue):439444.
[42] 应尚军, 范英. 股市演化的遗传元胞自动机模型[J]. 复杂系统与复杂性科学, 2013, 10(1):2637.
Ying Sijin, Fan Ying. Genetic cellular automata model of evolving stock market[J]. Complex Systems and Complexity Science,2013, 10(1):2637.
[43] Ying S J and Fan Y. Complexity In The Chinese Stock Market And Its Relationships With Monetary Policy Intensity[J]. Physica A: Statistical Mechanics and its Applications, 2014, 394(1):338345.
[44] Ying S J, Li X J, Zhong X Q. Initial Value Sensitivity of the Chinese Stock Market and ItsRelationship With the Investment Psychology[J]. International Journal of Modern Physics C, 2015, 26(11): 15501281155012816.
[45] 李昊, 曹宏铎, 邢浩克. 基于复杂网络少数者博弈模型的金融市场仿真研究[J]. 系统工程理论与实践, 2012, 32(9):18821890.
Li Hao, Cao Hongduo, Xing Haoke. Modeling and simulation of complex finance networks based on minority game[J]. Systems Engineering—Theory& Practice, 2012, 32(9):18821890.
[46] 殷成龙. 基于少数者博弈模型和复杂网络理论的人工金融市场建模研究[D]. 杭州:浙江大学, 2007.
Yin Chenglong. Study on modeling of the artificial financial market based on minority game model and complex network[D]. Hangzhou:Zhejiang University Master dissertations,2007.
[1] 聂廷远, 王艳伟, 聂晶晶, 刘鹏飞. 基于注意力机制和复杂网络的FPGA可布性预测[J]. 复杂系统与复杂性科学, 2026, 23(1): 53-59.
[2] 户佐安, 杨江浩, 邓锦程. 考虑多元变量的世界航空网络综合鲁棒性研究[J]. 复杂系统与复杂性科学, 2026, 23(1): 60-69.
[3] 孙小慧, 刘毅, 米玉梅, 吕凯. 韧性视角下城市地铁与常规公交网络关键站点及线路识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 26-36.
[4] 牟奇锋, 李晓倩. 基于邻接矩阵的复杂网络演化融合迭代方法[J]. 复杂系统与复杂性科学, 2026, 23(1): 79-86.
[5] 孙文静, 余路粉, 潘文林, 蓝春江. 基于节点影响因子和贡献因子的复杂网络重要节点识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 87-95.
[6] 卢新彪, 刘泽诚, 陈贵允, 杨铁流, 高兴. 基于图卷积网络的复杂网络能控性提升方法[J]. 复杂系统与复杂性科学, 2025, 22(4): 24-28.
[7] 周青, 李依函, 陈文冲. “互联网+”企业创新生态系统网络演化分析[J]. 复杂系统与复杂性科学, 2025, 22(4): 1-7.
[8] 章浩淳, 寇博潇, 张泰杰, 唐智慧. 基于Granger Causality的滑坡机理网络客观权值确定方法[J]. 复杂系统与复杂性科学, 2025, 22(4): 63-70.
[9] 韩世翔, 闫光辉, 裴华艳. 复杂网络上双向免疫对传染病传播的影响[J]. 复杂系统与复杂性科学, 2025, 22(4): 55-62.
[10] 王红春, 周子祥. 复杂供应链网络中断风险传播趋势建模与仿真[J]. 复杂系统与复杂性科学, 2025, 22(3): 17-24.
[11] 张琦, 汪小帆. 复杂网络观点动力学分析与干预若干研究进展[J]. 复杂系统与复杂性科学, 2025, 22(2): 31-44.
[12] 张明磊, 宋玉蓉, 曲鸿博. 基于图注意力机制的复杂网络关键节点识别[J]. 复杂系统与复杂性科学, 2025, 22(2): 113-119.
[13] 陶昭, 侯忠生. 复杂网络的无模型自适应牵制控制[J]. 复杂系统与复杂性科学, 2025, 22(2): 120-127.
[14] 李伟莎, 王淑良, 宋博. 基于强化学习风电并网策略下的韧性分析[J]. 复杂系统与复杂性科学, 2025, 22(2): 128-134.
[15] 张耀波, 张胜, 王雨萱, 熊聪源. 基于K-shell的复杂网络簇生长维数研究[J]. 复杂系统与复杂性科学, 2025, 22(1): 11-17.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed