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Title:An evaluation of univariate time-series models of quarterly earnings per share and their generalization to models with autoregressive conditionally heteroscedastic disturbances
Author(s):Roy, Daniel
Doctoral Committee Chair(s):McKeown, James C.
Department / Program:Accountancy
Discipline:Accountancy
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Business Administration, Accounting
Abstract:This study evaluates time-series models of quarterly earnings per share (EPS) in order to determine whether there are any changes in the residual variance to be modeled by the GARCH procedure. The results of statistical analyses indicate the presence of GARCH effect in the residuals generated from ARIMA models for quarterly EPS. Furthermore, based on Akaike's information criterion, modeling the GARCH effect appears to be desirable. However, the results of forecast accuracy comparisons provide no evidence that the ARIMA-GARCH specification results in more accurate forecasts than the conventional ARIMA models.
Issue Date:1992
Type:Text
Language:English
URI:http://hdl.handle.net/2142/23358
Rights Information:Copyright 1992 Roy, Daniel
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9236585
OCLC Identifier:(UMI)AAI9236585


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