Extraction of the Essential Constituents of the S&P 500 Index

Ray R. Hashemi, Omid M. Ardakani, Azita A. Bahrami, Jeffrey A. Young

Research output: Contribution to book or proceedingConference articlepeer-review

2 Scopus citations

Abstract

The S&P 500 index is a leading indicator of the stock market and U.S. equities which is highly influenced by its essential constituents. Traditionally, such constituents are identified by the market capitalization weighting scheme. However, the literature rejects the efficiency of the weighting method. In contrast, we introduce data mining approaches of the entropy and rough sets as two separate methods for extraction of the essential S&P 500 constituents. The legitimacy of the findings in comparison with the S&P 500 weighting scheme have been investigated using the discrete time Markov Chain Models (MCM) and Hidden Markov Chain Models (HMCM) which lend themselves easily to the nature of the time-series data. The investigation is done against data for the full sample and pre/post crisis subsamples collected for the period of 16 years. We find the entropy method provides the highest forecasting accuracy measure for the full sample and post-crisis subsample.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
EditorsFernando G. Tinetti, Quoc-Nam Tran, Leonidas Deligiannidis, Mary Qu Yang, Mary Qu Yang, Hamid R. Arabnia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages351-356
Number of pages6
ISBN (Electronic)9781538626528
DOIs
StatePublished - Dec 4 2018
Event2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 - Las Vegas, United States
Duration: Dec 14 2017Dec 16 2017

Publication series

NameProceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017

Conference

Conference2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
Country/TerritoryUnited States
CityLas Vegas
Period12/14/1712/16/17

Scopus Subject Areas

  • Computer Science (miscellaneous)
  • Artificial Intelligence
  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • Entropy
  • Essential Constituents of the SP index
  • Hidden Markov Chain Model
  • Markov Chain Model
  • Rough Sets
  • S&P 500 Index

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