摘要翻译:
我们提出了一种对股票收益的金融时间序列进行聚类的方法,并提出了一种图形设置来量化和可视化这些聚类随着时间的演变。所提出的图形表示允许应用已知的算法来解决经典组合图问题,这些问题可以解释为与投资组合设计和投资策略有关的问题。我们举例说明了集群在时间上演化的这种图形表示,以及它在马德里证券交易所市场的实际数据上的使用。
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英文标题:
《Tracing the temporal evolution of clusters in a financial stock market》
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作者:
Argimiro Arratia and Alejandra Caba\~na
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最新提交年份:
2011
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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:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
We propose a methodology for clustering financial time series of stocks' returns, and a graphical set-up to quantify and visualise the evolution of these clusters through time. The proposed graphical representation allows for the application of well known algorithms for solving classical combinatorial graph problems, which can be interpreted as problems relevant to portfolio design and investment strategies. We illustrate this graph representation of the evolution of clusters in time and its use on real data from the Madrid Stock Exchange market.
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PDF链接:
https://arxiv.org/pdf/1111.3127


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