Economic sector identification in a set of stocks traded at the New York Stock Exchange: a comparative analysis

Research output: Contribution to conferenceOtherpeer-review

9 Citations (Scopus)

Abstract

We review some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a set of stocks traded at the New York Stock Exchange. The investigated time series are recorded at a daily time horizon.All the considered methods are able to detect economic information and the presence of clusters characterized by the economic sector of stocks. However, different methodologies provide different information about the considered set. Our comparative analysis suggests that the application of just a single method could not be able to extract all the economic information present in the correlation coefficient matrix of a set of stocks.
Original languageEnglish
Pages66010T-1-66010T-12
Number of pages12
Publication statusPublished - 2007

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Economic sector identification in a set of stocks traded at the New York Stock Exchange: a comparative analysis'. Together they form a unique fingerprint.

Cite this