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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Journal of Asset Management and Financing</JournalTitle>
				<Issn>2383-1189</Issn>
				<Volume>7</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2019</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Checking conformity of Tehran Stock Exchange Data with Benford’s Law</ArticleTitle>
<VernacularTitle>Checking conformity of Tehran Stock Exchange Data with Benford’s Law</VernacularTitle>
			<FirstPage>103</FirstPage>
			<LastPage>112</LastPage>
			<ELocationID EIdType="pii">21322</ELocationID>
			
<ELocationID EIdType="doi">10.22108/amf.2017.21322</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Somayeh</FirstName>
					<LastName>Poorhossein</LastName>
<Affiliation>Instructor, Department of Accounting, Faculty of Accounting, Islamic Azad University Mobarakeh Branch, Isfahan, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>10</Month>
					<Day>10</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong&gt;Objective: &lt;/strong&gt;In general, when a financial market works ordinarily, the probability distribution of the first significant digit of the returns of the assets listed therein follows Benford’s law, but does not necessarily follow this distribution in the case of anomalous events. This law shows the contingency of various digits in a set of numbers thus it can be used for assessing data sets that occur naturally. &lt;br /&gt;&lt;strong&gt;Method: &lt;/strong&gt;The present study applied Benford law in order to investigate the empirical probability distribution of the first and the second digit of daily stocks return in listed companies in the Tehran Stock Exchange during 1384 – 1393. &lt;br /&gt;&lt;strong&gt;Results: &lt;/strong&gt;The findings show that the data of daily stocks return in listed companies in the Tehran Stock Exchange that used in the present study do not obey the Benford law. This can be due to some reasons such as different data transformation or influential conditions in the Iran stock market.</Abstract>
			<OtherAbstract Language="FA">&lt;strong&gt;Objective: &lt;/strong&gt;In general, when a financial market works ordinarily, the probability distribution of the first significant digit of the returns of the assets listed therein follows Benford’s law, but does not necessarily follow this distribution in the case of anomalous events. This law shows the contingency of various digits in a set of numbers thus it can be used for assessing data sets that occur naturally. &lt;br /&gt;&lt;strong&gt;Method: &lt;/strong&gt;The present study applied Benford law in order to investigate the empirical probability distribution of the first and the second digit of daily stocks return in listed companies in the Tehran Stock Exchange during 1384 – 1393. &lt;br /&gt;&lt;strong&gt;Results: &lt;/strong&gt;The findings show that the data of daily stocks return in listed companies in the Tehran Stock Exchange that used in the present study do not obey the Benford law. This can be due to some reasons such as different data transformation or influential conditions in the Iran stock market.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Benford law</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Stock return</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Data quality</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://amf.ui.ac.ir/article_21322_7fae29821d4db8bda58328569583b609.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
