Cluster analysis of imputed financial data using an augmentation-based algorithm

Halima Bensmail, R. P. DeGennaro

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper introduces and applies a new statistical modelling technique to carry out cluster analysis on imputed financial companies data that offer a direct investment plan. We show how this new method correctly classifies the companies without Dividend Reinvestment Plans (DRIPS), and determines misclassified companies.

Original languageEnglish
Title of host publicationStatistical Data Mining and Knowledge Discovery
PublisherCRC Press
Pages513-528
Number of pages16
ISBN (Electronic)9780203497159
ISBN (Print)9781584883449
Publication statusPublished - 1 Jan 2003

Fingerprint

Cluster analysis
Industry
Dividends
Direct investment
Modeling
Augmentation
Financial data

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)
  • Computer Science(all)

Cite this

Bensmail, H., & DeGennaro, R. P. (2003). Cluster analysis of imputed financial data using an augmentation-based algorithm. In Statistical Data Mining and Knowledge Discovery (pp. 513-528). CRC Press.

Cluster analysis of imputed financial data using an augmentation-based algorithm. / Bensmail, Halima; DeGennaro, R. P.

Statistical Data Mining and Knowledge Discovery. CRC Press, 2003. p. 513-528.

Research output: Chapter in Book/Report/Conference proceedingChapter

Bensmail, H & DeGennaro, RP 2003, Cluster analysis of imputed financial data using an augmentation-based algorithm. in Statistical Data Mining and Knowledge Discovery. CRC Press, pp. 513-528.
Bensmail H, DeGennaro RP. Cluster analysis of imputed financial data using an augmentation-based algorithm. In Statistical Data Mining and Knowledge Discovery. CRC Press. 2003. p. 513-528
Bensmail, Halima ; DeGennaro, R. P. / Cluster analysis of imputed financial data using an augmentation-based algorithm. Statistical Data Mining and Knowledge Discovery. CRC Press, 2003. pp. 513-528
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