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Least Square Estimation about the ARCH Model under Ordered Restriction

WANG Xiao-guang1, SONG Li-xin2   

  1. 1. Institute of Mathematics, Jilin University, Changchun 130012, China; 2. Department of Applied Mathematics, Dalian University of Technology, Dalian 116024, China
  • Received:2004-10-08 Revised:1900-01-01 Online:2005-05-26 Published:2005-05-26
  • Contact: WANG Xiao-guang

Abstract: This paper deals with the statistical inference of an au toregressive conditional heteroscedasticity (ARCH) model under restriction. We g ave a criteria function to compute a least squares estimation for the nonnegativ e parameters (α012,…,αq) of the ARCH model, and showed the strong consistency of the estimation. By discuss ing the exact expression and the asymptotic normality of the estimation under ordered restriction (α1≥α2≥…≥αq), we obtained the form of the test statist ical quantity, then solved the testing problem with the parameter space under or dered restriction.

Key words: least squares estimator, strong consistency, asymptoti c normality property, ordered restriction

CLC Number: 

  • O212.1