A Graphical Tool for Describing the Temporal Evolution of Clusters in Financial Stock Markets

被引：7

作者：

Arratia, Argimiro ^{[1
]}

Cabana, Alejandra ^{[2
]}

机构：

[1] Univ Politecn Cataluna, Barcelona, Spain

[2] Univ Autonoma Barcelona, E-08193 Barcelona, Spain

来源：

COMPUTATIONAL ECONOMICS | 2013年 / 41卷 / 02期

关键词：

Financial time series; Clustering; Graph combinatorics; TIME-SERIES;

D O I：

10.1007/s10614-012-9327-x

中图分类号：

F [经济];

学科分类号：

02 ;

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.

引用

页码：213 / 231

页数：19

共 15 条

[1]

Brockwell PJ, 2016, SPRINGER TEXTS STAT, P1, DOI 10.1007/978-3-319-29854-2

[2]

Cormen T., 2001, Introduction to Algorithms

[3]

Embrechts P., 2002, RISK MANAGEMENT VALU

[4]

Friedman J., 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, V1

[5]

Garey M. R., 1979, Computers and intractability. A guide to the theory of NP-completeness

[6]

Gibbons J. D., 1969, NONPARAMETRIC STAT I

[7]

Graham B., 2006, INTELLIGENT INVESTOR

[8] Clustering of time series data - a survey [J].

Liao, TW .

PATTERN RECOGNITION, 2005, 38 (11) :1857-1874

[9] Clustering heteroskedastic time series by model-based procedures [J].

Otranto, Edoardo .

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2008, 52 (10) :4685-4698

[10]

Pournelle G. H., 1953, Journal of Mammalogy, V34, P133, DOI 10.1890/0012-9658(2002)083[1421:SDEOLC]2.0.CO

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