Testing and Locating Variance Changepoints with Application to Stock Prices

Jie Chen, A. K. Gupta

Research output: Contribution to journalArticlepeer-review

204 Scopus citations


This article explores testing and locating multiple variance changepoints in a sequence of independent Gaussian random variables (assuming known and common mean). This type of problem is very common in applied economics and finance. A binary procedure combined with the Schwarz information criterion (SIC) is used to search all of the possible variance changepoints existing in the sequence. The simulated power of the proposed procedure is compared to that of the CUSUM procedure used by Inclán and Tiao to cope with variance changepoints. The SIC and unbiased SIC for this problem are derived. To obtain the percentage points of the SIC criterion, the asymptotic null distribution of a function of the SIC is obtained, and then the approximate percentage points of the SIC are tabulated. Finally, the results are applied to the weekly stock prices. The unknown but common mean case is also outlined at the end.

Original languageEnglish (US)
Pages (from-to)739-747
Number of pages9
JournalJournal of the American Statistical Association
Issue number438
StatePublished - Jun 1 1997
Externally publishedYes


  • Asymptotic distribution
  • Consistency
  • Cumulative sum
  • Hypothesis testing
  • Information criterion
  • Return series
  • Unbiased estimator

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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