Cluster analysis for stable processes

Tsutomu Watanabe*, Hiroshi Shiraishi, Masanobu Taniguchi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


It is known that various financial time series, e.g., daily log returns on a share price, foreign exchange rates, excess bond returns, etc., exhibit heavy-tailed behavior. Recently, discriminant analysis has been applied to financial time series, such as, the problem of credit rating for companies. In this article, we investigate the problem of classifying an -stable linear process into one of two categories with indices 1 and 2, respectively. We propose some discriminant criteria. It is shown that our discriminant statistics are consistent. The misclassification probabilities are also evaluated under contiguous hypotheses. Some numerical studies for an (AR(1)) process are given.

Original languageEnglish
Pages (from-to)1630-1642
Number of pages13
JournalCommunications in Statistics - Theory and Methods
Issue number8-9
Publication statusPublished - 2010 Jan


  • Discriminant analysis
  • Functional limit theorem
  • Integrated periodogram
  • Linear process
  • Stable process

ASJC Scopus subject areas

  • Statistics and Probability


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