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The use of biweight mid correlation to improve graph based portfolio construction

Research output: Chapter in Book/Report/Conference proceedingConference paper

Original languageEnglish
Title of host publication2016 8th Computer Science and Electronic Engineering Conference, CEEC 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages101-106
Number of pages6
ISBN (Print)9781509020508
DOIs
StatePublished - 27 Jan 2017
Event8th Computer Science and Electronic Engineering Conference, CEEC 2016 - Colchester, United Kingdom
Duration: 28 Sep 201630 Sep 2016

Conference

Conference8th Computer Science and Electronic Engineering Conference, CEEC 2016
CountryUnited Kingdom
CityColchester
Period28/09/201630/09/2016

Documents

  • BicorPaper

    BicorPaper.pdf, 501 KB, application/pdf

    19/05/2017

    Accepted author manuscript

King's Authors

Abstract

An analysis of the correlation between the returns of different securities is of fundamental importance in many areas of finance, such as portfolio optimisation. The most commonly used measure of correlation is the Pearson correlation coefficient; however, this suffers from several problems when applied to data from the real world. We propose an alternative estimator - the Biweight Mid Correlation (Bicor) - as a more robust measure for capturing the relationship between returns. We systematically evaluate Bicor empirically using data from the FTSE 100 constituents, and show that it is more robust when compared with the Pearson correlation coefficient. Finally, we demonstrate that Bicor can be used to improve a graph-based method of portfolio construction. Specifically, we show that when treating the correlation matrix as an adjacency matrix for a graph and using graph centrality to construct portfolios, the use of Bicor leads to better performing portfolios.

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