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McKeown, James C. Roy, Daniel 2011-05-07T14:11:20Z 2011-05-07T14:11:20Z 10000-01-01 1992 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. Made available in DSpace on 2011-05-07T14:11:20Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9236585.pdf: 3502965 bytes, checksum: 483a40a81734457a95c441b764ca3750 (MD5) Previous issue date: 1992 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:03:56Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:30:30-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission ETDs are only available to UIUC Users without author permission U of I Only AAI9236585 (UMI)AAI9236585 http://hdl.handle.net/2142/23358 eng Copyright 1992 Roy, Daniel Business Administration, Accounting An evaluation of univariate time-series models of quarterly earnings per share and their generalization to models with autoregressive conditionally heteroscedastic disturbances text Accountancy Accountancy University of Illinois at Urbana-Champaign Dissertation Ph.D.