Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2001-07

AUTHORS

Bong H. Han, David Manry, Wayne Shaw

ABSTRACT

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations. More... »

PAGES

81-98

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1011209621712

DOI

http://dx.doi.org/10.1023/a:1011209621712

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037363855


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1403", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Econometrics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/14", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Economics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Ajou University", 
          "id": "https://www.grid.ac/institutes/grid.251916.8", 
          "name": [
            "College of Business, Ajou University, 442-749, Suwon, Kyonggi - Do, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Bong H.", 
        "id": "sg:person.014360422332.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014360422332.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of New Orleans", 
          "id": "https://www.grid.ac/institutes/grid.266835.c", 
          "name": [
            "Department of Accounting, University of New Orleans, 70148-1530, New Orleans, LA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Manry", 
        "givenName": "David", 
        "id": "sg:person.011462751344.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011462751344.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Southern Methodist University", 
          "id": "https://www.grid.ac/institutes/grid.263864.d", 
          "name": [
            "Cox School of Business, Southern Methodist University, P.O. Box 750333, 75275-0333, Dallas, TX"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shaw", 
        "givenName": "Wayne", 
        "id": "sg:person.011350652074.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011350652074.24"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0304-405x(77)90041-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001219827"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-4101(88)90023-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009288547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-405x(93)90004-u", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011123382"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1540-6261.1992.tb04398.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013253575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-4101(87)90017-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013574893"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-4101(92)90025-w", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027066614"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0148558x9200700205", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032475996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0148558x9200700205", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032475996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-4101(82)90015-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035719558"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-4101(82)90015-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035719558"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-405x(83)90056-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037344359"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1468-5957.00307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052938197"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1912934", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069640376"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1913322", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069640657"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2330778", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069892738"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2491062", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069940730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2469/faj.v34.n4.65", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070833790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3905/joi.5.1.17", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071561330"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2001-07", 
    "datePublishedReg": "2001-07-01", 
    "description": "This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1023/a:1011209621712", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136353", 
        "issn": [
          "0924-865X", 
          "1573-7179"
        ], 
        "name": "Review of Quantitative Finance and Accounting", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "17"
      }
    ], 
    "name": "Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias", 
    "pagination": "81-98", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b1fc8b4f1edc238e32e10a1e3a6300691311b4749689d27a0690e4ecdd633cf5"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1023/a:1011209621712"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1037363855"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1023/a:1011209621712", 
      "https://app.dimensions.ai/details/publication/pub.1037363855"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:48", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8664_00000500.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1023/A:1011209621712"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1023/a:1011209621712'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1011209621712'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1011209621712'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1011209621712'


 

This table displays all metadata directly associated to this object as RDF triples.

129 TRIPLES      21 PREDICATES      43 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1023/a:1011209621712 schema:about anzsrc-for:14
2 anzsrc-for:1403
3 schema:author N97ed1dac33b7406cb9363f638d10af1c
4 schema:citation https://doi.org/10.1016/0165-4101(82)90015-5
5 https://doi.org/10.1016/0165-4101(87)90017-6
6 https://doi.org/10.1016/0165-4101(88)90023-7
7 https://doi.org/10.1016/0165-4101(92)90025-w
8 https://doi.org/10.1016/0304-405x(77)90041-1
9 https://doi.org/10.1016/0304-405x(83)90056-9
10 https://doi.org/10.1016/0304-405x(93)90004-u
11 https://doi.org/10.1111/1468-5957.00307
12 https://doi.org/10.1111/j.1540-6261.1992.tb04398.x
13 https://doi.org/10.1177/0148558x9200700205
14 https://doi.org/10.2307/1912934
15 https://doi.org/10.2307/1913322
16 https://doi.org/10.2307/2330778
17 https://doi.org/10.2307/2491062
18 https://doi.org/10.2469/faj.v34.n4.65
19 https://doi.org/10.3905/joi.5.1.17
20 schema:datePublished 2001-07
21 schema:datePublishedReg 2001-07-01
22 schema:description This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.
23 schema:genre research_article
24 schema:inLanguage en
25 schema:isAccessibleForFree false
26 schema:isPartOf N0372880cf7a846cf984408b631b5d691
27 N7138c31b2a22491c8a8b507d9d9c5b5b
28 sg:journal.1136353
29 schema:name Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias
30 schema:pagination 81-98
31 schema:productId Nd10fd1fa3bc8417abf219c28377ae9be
32 Ndb597646484b47efa487a84e1a5640c0
33 Nf229fa87acf14ca6bc01964ba4a8802d
34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037363855
35 https://doi.org/10.1023/a:1011209621712
36 schema:sdDatePublished 2019-04-10T15:48
37 schema:sdLicense https://scigraph.springernature.com/explorer/license/
38 schema:sdPublisher N3253dc2c3b104aed90adc9c54872d6a5
39 schema:url http://link.springer.com/10.1023/A:1011209621712
40 sgo:license sg:explorer/license/
41 sgo:sdDataset articles
42 rdf:type schema:ScholarlyArticle
43 N0372880cf7a846cf984408b631b5d691 schema:issueNumber 1
44 rdf:type schema:PublicationIssue
45 N3253dc2c3b104aed90adc9c54872d6a5 schema:name Springer Nature - SN SciGraph project
46 rdf:type schema:Organization
47 N507c51d6e0524f918dce1fb64ef4fb07 rdf:first sg:person.011462751344.45
48 rdf:rest Nd4a18a209da34774880f6719a013db33
49 N7138c31b2a22491c8a8b507d9d9c5b5b schema:volumeNumber 17
50 rdf:type schema:PublicationVolume
51 N97ed1dac33b7406cb9363f638d10af1c rdf:first sg:person.014360422332.08
52 rdf:rest N507c51d6e0524f918dce1fb64ef4fb07
53 Nd10fd1fa3bc8417abf219c28377ae9be schema:name doi
54 schema:value 10.1023/a:1011209621712
55 rdf:type schema:PropertyValue
56 Nd4a18a209da34774880f6719a013db33 rdf:first sg:person.011350652074.24
57 rdf:rest rdf:nil
58 Ndb597646484b47efa487a84e1a5640c0 schema:name readcube_id
59 schema:value b1fc8b4f1edc238e32e10a1e3a6300691311b4749689d27a0690e4ecdd633cf5
60 rdf:type schema:PropertyValue
61 Nf229fa87acf14ca6bc01964ba4a8802d schema:name dimensions_id
62 schema:value pub.1037363855
63 rdf:type schema:PropertyValue
64 anzsrc-for:14 schema:inDefinedTermSet anzsrc-for:
65 schema:name Economics
66 rdf:type schema:DefinedTerm
67 anzsrc-for:1403 schema:inDefinedTermSet anzsrc-for:
68 schema:name Econometrics
69 rdf:type schema:DefinedTerm
70 sg:journal.1136353 schema:issn 0924-865X
71 1573-7179
72 schema:name Review of Quantitative Finance and Accounting
73 rdf:type schema:Periodical
74 sg:person.011350652074.24 schema:affiliation https://www.grid.ac/institutes/grid.263864.d
75 schema:familyName Shaw
76 schema:givenName Wayne
77 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011350652074.24
78 rdf:type schema:Person
79 sg:person.011462751344.45 schema:affiliation https://www.grid.ac/institutes/grid.266835.c
80 schema:familyName Manry
81 schema:givenName David
82 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011462751344.45
83 rdf:type schema:Person
84 sg:person.014360422332.08 schema:affiliation https://www.grid.ac/institutes/grid.251916.8
85 schema:familyName Han
86 schema:givenName Bong H.
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014360422332.08
88 rdf:type schema:Person
89 https://doi.org/10.1016/0165-4101(82)90015-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035719558
90 rdf:type schema:CreativeWork
91 https://doi.org/10.1016/0165-4101(87)90017-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013574893
92 rdf:type schema:CreativeWork
93 https://doi.org/10.1016/0165-4101(88)90023-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009288547
94 rdf:type schema:CreativeWork
95 https://doi.org/10.1016/0165-4101(92)90025-w schema:sameAs https://app.dimensions.ai/details/publication/pub.1027066614
96 rdf:type schema:CreativeWork
97 https://doi.org/10.1016/0304-405x(77)90041-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001219827
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1016/0304-405x(83)90056-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037344359
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1016/0304-405x(93)90004-u schema:sameAs https://app.dimensions.ai/details/publication/pub.1011123382
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1111/1468-5957.00307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052938197
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1111/j.1540-6261.1992.tb04398.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1013253575
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1177/0148558x9200700205 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032475996
108 rdf:type schema:CreativeWork
109 https://doi.org/10.2307/1912934 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069640376
110 rdf:type schema:CreativeWork
111 https://doi.org/10.2307/1913322 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069640657
112 rdf:type schema:CreativeWork
113 https://doi.org/10.2307/2330778 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069892738
114 rdf:type schema:CreativeWork
115 https://doi.org/10.2307/2491062 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069940730
116 rdf:type schema:CreativeWork
117 https://doi.org/10.2469/faj.v34.n4.65 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070833790
118 rdf:type schema:CreativeWork
119 https://doi.org/10.3905/joi.5.1.17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071561330
120 rdf:type schema:CreativeWork
121 https://www.grid.ac/institutes/grid.251916.8 schema:alternateName Ajou University
122 schema:name College of Business, Ajou University, 442-749, Suwon, Kyonggi - Do, Korea
123 rdf:type schema:Organization
124 https://www.grid.ac/institutes/grid.263864.d schema:alternateName Southern Methodist University
125 schema:name Cox School of Business, Southern Methodist University, P.O. Box 750333, 75275-0333, Dallas, TX
126 rdf:type schema:Organization
127 https://www.grid.ac/institutes/grid.266835.c schema:alternateName University of New Orleans
128 schema:name Department of Accounting, University of New Orleans, 70148-1530, New Orleans, LA
129 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...