{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/23461"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/23461","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The incremental predictive ability of individual financial analysts","abstract":"\"Financial analysts are among the most influential group of users of financial accounting information. Because the FASB has advocated usefulness as the \"\"overriding criterion\"\" (FASB, 1980, p.26) to judge accounting choices, accountants have a stake in understanding this important group of financial statement users. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to models. This is in contrast to the robust result from years of judgment/decision making (JDM) research that human predictions are inferior to statistical model predictions. Prior accounting studies have also documented that analysts exhibit optimism when forecasting earnings.\"","abstract_html":""Financial analysts are among the most influential group of users of financial accounting information. Because the FASB has advocated usefulness as the ""overriding criterion"" (FASB, 1980, p.26) to judge accounting choices, accountants have a stake in understanding this important group of financial statement users. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to models. This is in contrast to the robust result from years of judgment/decision making (JDM) research that human predictions are inferior to statistical model predictions. Prior accounting studies have also documented that analysts exhibit optimism when forecasting earnings."","abstract_has_math":false,"creators":["Giullian, Marc Andrew"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Accountancy","degree_department":null,"school":null,"contributors":["Kleinmuntz, Don N."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T14:15:02Z","date_published":"2011-05-07T14:15:02Z","updated_at":"2026-07-22T22:25:22Z","subjects":["Business Administration, Accounting"],"languages":["eng"],"rights":["Copyright 1996 Giullian, Marc Andrew"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9780591198249","AAI9712284","(UMI)AAI9712284"],"render_values":[{"text":"9780591198249","href":null,"code":true},{"text":"AAI9712284","href":null,"code":true},{"text":"(UMI)AAI9712284","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/23461","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kleinmuntz, Don N."]},{"key":"dc:creator","label":"Author","values":["Giullian, Marc Andrew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T14:15:02Z","10000-01-01","1996"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Accountancy"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Business Administration, Accounting"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1996 Giullian, Marc Andrew"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9780591198249","AAI9712284","(UMI)AAI9712284","http://hdl.handle.net/2142/23461"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["\"Financial analysts are among the most influential group of users of financial accounting information. Because the FASB has advocated usefulness as the \"\"overriding criterion\"\" (FASB, 1980, p.26) to judge accounting choices, accountants have a stake in understanding this important group of financial statement users. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to models. This is in contrast to the robust result from years of judgment/decision making (JDM) research that human predictions are inferior to statistical model predictions. Prior accounting studies have also documented that analysts exhibit optimism when forecasting earnings.\"","Humans can make a significant contribution to accurate forecasting in spite of cognitive limitations. Some skills people bring to bear are cue identification, rapid adaptability to environmental changes and the evaluation of qualitative factors. Although statistical models are not well-equipped to utilize qualitative factors and be adaptable, they do offer consistency and significant computational power. Thus, the strengths of humans and statistical models in forecasting are complementary.","This research documents the incremental predictive ability of both individual financial analysts and statistical models in forecasting earnings. It also provides evidence that both individual financial analysts' and statistical models' incremental predictive ability varies between industries. In addition, tests show a pessimistic bias for individual analysts, contrary to prior studies. Additional evidence is presented regarding forecast accuracy for four different forecast generation methods.","Made available in DSpace on 2011-05-07T14:15:02Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9712284.pdf: 2847093 bytes, checksum: d119ab4c6f71e7181c64e4c93a70b32d (MD5) Previous issue date: 1996","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:04:38Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:30:54-05:00 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"]},{"key":"dc:title","label":"Title","values":["The incremental predictive ability of individual financial analysts"]}]}],"canonical_facts":{"dc:contributor":["Kleinmuntz, Don N."],"dc:creator":["Giullian, Marc Andrew"],"dc:date":["2011-05-07T14:15:02Z","10000-01-01","1996"],"dc:description":["\"Financial analysts are among the most influential group of users of financial accounting information. Because the FASB has advocated usefulness as the \"\"overriding criterion\"\" (FASB, 1980, p.26) to judge accounting choices, accountants have a stake in understanding this important group of financial statement users. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to models. This is in contrast to the robust result from years of judgment/decision making (JDM) research that human predictions are inferior to statistical model predictions. Prior accounting studies have also documented that analysts exhibit optimism when forecasting earnings.\"","Humans can make a significant contribution to accurate forecasting in spite of cognitive limitations. Some skills people bring to bear are cue identification, rapid adaptability to environmental changes and the evaluation of qualitative factors. Although statistical models are not well-equipped to utilize qualitative factors and be adaptable, they do offer consistency and significant computational power. Thus, the strengths of humans and statistical models in forecasting are complementary.","This research documents the incremental predictive ability of both individual financial analysts and statistical models in forecasting earnings. It also provides evidence that both individual financial analysts' and statistical models' incremental predictive ability varies between industries. In addition, tests show a pessimistic bias for individual analysts, contrary to prior studies. Additional evidence is presented regarding forecast accuracy for four different forecast generation methods.","Made available in DSpace on 2011-05-07T14:15:02Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9712284.pdf: 2847093 bytes, checksum: d119ab4c6f71e7181c64e4c93a70b32d (MD5) Previous issue date: 1996","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:04:38Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:30:54-05:00 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"],"dc:identifier":["9780591198249","AAI9712284","(UMI)AAI9712284","http://hdl.handle.net/2142/23461"],"dc:language":["eng"],"dc:rights":["Copyright 1996 Giullian, Marc Andrew"],"dc:subject":["Business Administration, Accounting"],"dc:title":["The incremental predictive ability of individual financial analysts"],"dc:type":["text"],"thesis:degree_discipline":["Accountancy"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:22Z"}