Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model

Min Hsien Chiang, Ray Yeutien Chou, Li Min Wang

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

An outlier detection procedure in the lognormal logarithmic conditional autoregressive range (lognormal Log-CARR) model is proposed. The proposed test statistic is demonstrated to be well-sized and to have good power using Monte Carlo simulations. Furthermore, the outlier detection procedure suffers less from the masking effect caused by multiple outliers. The results of an empirical investigation show that the proposed method can effectively detect volatility outliers and improve forecasting accuracy.

Original languageEnglish
Pages (from-to)126-144
Number of pages19
JournalOxford Bulletin of Economics and Statistics
Volume78
Issue number1
DOIs
Publication statusPublished - 2016 Feb 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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