Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30487| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Michaelides, Michael | - |
| dc.date.accessioned | 2023-09-22T11:48:31Z | - |
| dc.date.available | 2023-09-22T11:48:31Z | - |
| dc.date.issued | 2021-07 | - |
| dc.identifier.citation | Finance Research Letters, vol. 41, 2021 | en_US |
| dc.identifier.issn | 15446123 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14279/30487 | - |
| dc.description.abstract | The vast majority of empirical studies in finance employ large enough sample sizes and use the conventional thresholds for statistical significance. This routine practice can potentially lead to spurious statistically significant results. The primary aim of this paper is to present a rule of thumb that can be used to determine the appropriate thresholds for statistical significance for a given sample size. The paper argues that the list of statistically significant findings in the broader finance literature is likely to be much shorter after accounting for large sample size bias. | en_US |
| dc.format | en_US | |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | Finance Research Letters | en_US |
| dc.rights | © Elsevier | en_US |
| dc.subject | Methodological crisis | en_US |
| dc.subject | Publication bias | en_US |
| dc.subject | Large sample size | en_US |
| dc.subject | High statistical power | en_US |
| dc.subject | Spurious statistical significance | en_US |
| dc.subject | Appropriate significance thresholds | en_US |
| dc.title | Large sample size bias in empirical finance | en_US |
| dc.type | Article | en_US |
| dc.collaboration | Allegheny College | en_US |
| dc.subject.category | Economics and Business | en_US |
| dc.journals | Subscription | en_US |
| dc.country | United States | en_US |
| dc.subject.field | Social Sciences | en_US |
| dc.publication | Peer Reviewed | en_US |
| dc.identifier.doi | 10.1016/j.frl.2020.101835 | en_US |
| dc.identifier.scopus | 2-s2.0-85096088601 | - |
| dc.identifier.url | http://dx.doi.org/10.1016/j.frl.2020.101835 | - |
| dc.relation.volume | 41 | en_US |
| cut.common.academicyear | 2021-2022 | en_US |
| dc.identifier.external | 142551182 | - |
| item.grantfulltext | none | - |
| item.openairetype | article | - |
| item.fulltext | No Fulltext | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
| item.cerifentitytype | Publications | - |
| item.languageiso639-1 | en | - |
| crisitem.author.dept | Department of Finance, Accounting and Management Science | - |
| crisitem.author.faculty | Faculty of Management and Economics | - |
| crisitem.author.orcid | 0009-0009-6727-5563 | - |
| crisitem.author.parentorg | Faculty of Management and Economics | - |
| Appears in Collections: | Άρθρα/Articles | |
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