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

Argimiro Arratia; Alejandra Cabaña

doi:https://doi.org/10.1007/s10614-012-9327-x

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

Argimiro Arratia^*, Alejandra Cabaña

^*Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer-review

5 Citations (Scopus)

Abstract

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. © 2012 Springer Science+Business Media New York.

Original language	English
Pages (from-to)	213-231
Number of pages	19
Journal	Computational Economics
Volume	41
Issue number	2
DOIs	https://doi.org/10.1007/s10614-012-9327-x
Publication status	Published - 1 Jan 2013

Keywords

Clustering
Financial time series
Graph combinatorics

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https://doi.org/10.1007/s10614-012-9327-x

https://ddd.uab.cat/record/126135

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abstract = "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. {\textcopyright} 2012 Springer Science+Business Media New York.",

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AB - 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. © 2012 Springer Science+Business Media New York.

KW - Clustering

KW - Financial time series

KW - Graph combinatorics

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

Abstract

Keywords

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