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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Iranian Financial Engineering Association(IFEA)</PublisherName>
				<JournalTitle>International Journal of Finance &amp; Managerial Accounting</JournalTitle>
				<Issn>2588-4379</Issn>
				<Volume>8</Volume>
				<Issue>29</Issue>
				<PubDate PubStatus="epublish">
					<Year>2023</Year>
					<Month>04</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Evaluating the Effectiveness of GARCH models in the Estimation of Conditional Value at Risk in listed companies of the Tehran Stock Exchange: Accounting Data Approach</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>239</FirstPage>
			<LastPage>249</LastPage>
			<ELocationID EIdType="pii">21140</ELocationID>
			
<ELocationID EIdType="doi">10.30495/ijfma.2023.21140</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Hossein</FirstName>
					<LastName>Aryaeinezhad</LastName>
<Affiliation>PhD Student, Department of Accounting, Islamic Azad University, Aliabad Katoul Branch, Aliabad Katoul, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Arash</FirstName>
					<LastName>Naderian</LastName>
<Affiliation>Assistant professor, Department of Accounting, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-0733-1497</Identifier>

</Author>
<Author>
					<FirstName>Hosein</FirstName>
					<LastName>Didehkhani</LastName>
<Affiliation>Assistant Professor, Department of Financial Engineering , Aliabad Katoul Branch, Islamic Azad University, Aliabad katul , Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Khozein</LastName>
<Affiliation>Assistant Professor of Accounting, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>10</Month>
					<Day>19</Day>
				</PubDate>
			</History>
		<Abstract>Predictions are extremely important for a better decision-making. Uncertainty in decision making makes investors always seek to assess and estimate risk to minimize potential losses. Conditional risk value (CvaR) is considered as a comprehensive measure of risk that has been considered a useful tool in recent years. Due to the characteristics of capital market data, not all models will be able to make accurate predictions, and among the multitude of models, only the models which make predictions can correctly explain this market.&lt;br /&gt;In this study, according to the existing theoretical foundations and using Delphi model and analysis and review of experts, first the accounting variables in the financial statements are effective in predicting the conditional risk value, then the data of accepted companies are used. In Tehran Stock Exchange during 2012-2018, we evaluated the capability of GARCH and Markov index models in predicting conditional risk value as a criterion for predicting coherent risk. The results showed that the estimates made with the GARCH model (1, 1) are closer to reality with the distribution of T-Student.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Accounting Data</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Coherent risk</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Conditional risk value</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Markov Switching</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">GARCH</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijfma.ir/article_21140_930dcd054bee88067db8ded7a2086106.pdf</ArchiveCopySource>
</Article>
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