<?xml version="1.0" encoding="utf-8"?>
<ags:resources xmlns:ags="http://purl.org/agmes/1.1/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:agls="http://www.naa.gov.au/recordkeeping/gov_online/agls/1.2" xmlns:dcterms="http://purl.org/dc/terms/">
<ags:resource>
					<dc:title><![CDATA[Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Abounoori, Esmaiel]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Abdollahi, Mohammadreza]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[Volatility transmission]]></dc:subject>
				<dc:subject><![CDATA[MGARCH]]></dc:subject>
				<dc:subject><![CDATA[Modeling Volatility]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[This paper uses a multivariate GARCH model to simultaneously estimate the mean and conditional variance using daily returns among different Tehran sector indexes from Tir 1386 to Tir 1391. Since different financial assets are traded based on these sector indexes, it is important for financial market participants to understand the volatility transmission mechanism over time and across sectors in order to make optimal portfolio allocation decisions. Results show significant transmission of shocks and volatility among different sectors. These findings support the idea of cross-market hedging and sharing of common information by investors in these sectors.    ]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36628_3dbb24322744cda445e3920e80a50fdf.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36628]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[Risk Reduction of Portfolio based on Generalized Autoregressive Conditional Heteroscedasticity Model in Tehran Stock Exchange]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Eslami Bidgoli, Gholamreza]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Khan Ahmadi, Fatemeh]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[Mean Variance Model]]></dc:subject>
				<dc:subject><![CDATA[Generalized Autoregressive Conditional Heteroscedasticity Model]]></dc:subject>
				<dc:subject><![CDATA[Correlation Matrices]]></dc:subject>
				<dc:subject><![CDATA[risk management]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[Return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. The structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. It’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. In this research, it has been approved optimization based on conditional variance and standardized residuals correlation in Constant Correlation Generalized Autoregressive Conditional Heteroscedasticity model leads to less portfolio risk and improvement the portfolio manager performance.
 ]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36630_d543cb69f2bf0d78b22f02fbb002ee18.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36630]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[Financial Ranking of Firms Listed in Tehran Stock Exchange Corporations Using MADM and Mixed Methods]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Anvary Rostamy, Ali Asghar]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Hoseinian, Shahamat]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Rezaei Asl, Morteza]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[MADM Methods Mixed Method]]></dc:subject>
				<dc:subject><![CDATA[Ranking]]></dc:subject>
				<dc:subject><![CDATA[Tehran Stock Exchange]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[Nowadays, liveliness and rapid maintenance of the development process of the companies are dependent on the accurate and complete understanding of the merits of the financial activities. Since these merits are relative concepts that are based on comparisons, lists of ranking and comparison of industries with each other act as useful signposts for managers, politicians, and investors. The point of importance is the ranking model, ranking criteria and appropriate mathematical techniques for ranking. Ranking of stock exchange is performed through usual procedures and so far there has not been a comprehensive technique to recognize superior companies in Tehran stock exchange. In this study, Tehran stock exchange companies are ranked through MCDM methods such as: TOPSIS, ELECTRE, SAW, VIKOR, LINMAP, TAXONOMY, and DEA technique. Regarding the differences among the rankings, the final ranking of the companies is calculated with the use of mixed methods and a conceptual algorithm is ultimately advised.]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36632_04510bd6b6b8eb4301c5f05bd1bfdcfc.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36632]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[Investigating the Prices Manipulation in the Tehran Stock Exchange by Using the SVM Model]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Falah Shams, Mir Feyz]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Rashnoo, Mahdi]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Rashnoo, Mahdi]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[Price manipulation]]></dc:subject>
				<dc:subject><![CDATA[Duration Dependence Test]]></dc:subject>
				<dc:subject><![CDATA[Support vector Machine]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[Phenomenon of price manipulation is one of the factors which have caused mistrust of the investors to the stock market and inhibits its growth and prosperity. Entering the shareholders into the stock market, on one hand leads to increase in the general level of revenues and on the other hand causes inexpensive financing for companies. In this research, at first by using duration dependence test and among the 379 companies, 95 cases were identified as the manipulated companies. Then prediction accuracy of SVM model on prices manipulation in the stock market was examined. SVM model is one of the models which is used for classifying and separating the groups which their under examining data should be linear. It was tried to resolve the problem of not being linear data by using PCA. The research results show that the model correctly predicted to the extent of 81percent of manipulations]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36633_c596a39bc83bb0a2e6004b9fa02c8a41.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36633]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[The Cross-correlation Structure of Tehran Stock Exchange Indexes by Multifractal Detrended Fluctuation Analysis]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Tehrani, Reza]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Namaki, Ali]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Hedayatifar, Leyla]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[MF-DXA]]></dc:subject>
				<dc:subject><![CDATA[Financial Index]]></dc:subject>
				<dc:subject><![CDATA[Industrial Index]]></dc:subject>
				<dc:subject><![CDATA[Price index]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[One of the latest approaches for analyzing the coupled time series is MF-DXA. This technique has been used in many disciplines such as finance. In this paper, we have analyzed Tehran Stock Exchange indexes by MF-DXA and have found a scaling behavior between the Industrial, Financial and Price indexes. By surrogating, we could see that the effects of low probability events in Industrial and Financial index are more important than the Price index. In essence, we have found that the today return of each index depends on its previous returns and on the previous returns of the other indexes. This technique is useful in risk and portfolio managements.]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36635_cff1e5f6bd0bf40aa6c3aec857ea7908.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36635]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[The Relationship between Return and the Bid-Ask Spread in Tehran Stock Exchange]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Ghalibaf Asl, Hasan]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Razaghi, Mohadeseh]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[The Bid-Ask Spread]]></dc:subject>
				<dc:subject><![CDATA[Market Microstructure]]></dc:subject>
				<dc:subject><![CDATA[Size]]></dc:subject>
				<dc:subject><![CDATA[Beta]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[This paper studies the relationship between return and the Bid-Ask Spread in Tehran Stock Exchange. The research has been done according to Amihud and Mendelson’s model (1986). It should be mentioned that portfolio beta and size are added as explanatory variables into the model. The study period is from Day 1382 to Tir 1389. Based on the pooling of cross section and time series data used to estimate and test the model, the obtained results confirmed that there is a positive relationship between the market-observed return and the Bid-Ask Spread in Tehran stock exchange same as Amihud and Mendelson’s model.
 ]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36636_e06dbe1e5346e0826876fa04c4ee5e81.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36636]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>
<ags:resource>
					<dc:title><![CDATA[The Calculation of Optimal Interest Rate of Fire Insurance Catastrophe Bonds in Iran using Extreme Value Theory]]></dc:title>
					<dc:creator>
					<ags:creatorPersonal><![CDATA[Gorgani, Mostafa]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Asl Hadad, Ahmad]]></ags:creatorPersonal>
<ags:creatorPersonal><![CDATA[Shahriar, Behnam]]></ags:creatorPersonal>

			</dc:creator>
			<dc:publisher>
				<ags:publisherName><![CDATA[University of Tehran]]></ags:publisherName>
			</dc:publisher>
			<dc:date><dcterms:dateIssued><![CDATA[2012]]></dcterms:dateIssued></dc:date>
				<dc:subject><![CDATA[Catastrophe Bonds]]></dc:subject>
				<dc:subject><![CDATA[Value at Risk]]></dc:subject>
				<dc:subject><![CDATA[Generalized Pareto Distribution]]></dc:subject>
				<dc:subject><![CDATA[Normal Power Distribution]]></dc:subject>
				<dc:subject><![CDATA[Bootstrap Simulation]]></dc:subject>
			<dc:description>
				<ags:descriptionNotes><![CDATA[Includes references]]></ags:descriptionNotes>
				<dcterms:abstract><![CDATA[In recent decades, issuing of Catastrophe Bonds for covering the catastrophe losses such as earthquakes, floods, etc. are getting more widespread. The purpose of this paper is determination of the optimal interest rates for investors of these securities, so that it becomes attractive for them. This paper uses fire insurance data in the period of 1328 to 1388 and considers the Peaks over Threshold (POT) for measuring the catastrophe bonds value at risk. The u threshold has been selected with using normal power approximation, and the difference between it and the VaR higher than this threshold has been considered as catastrophe bonds risk. Finally, the optimal rate for these bonds, with maturity of 3 years and in 1000 nominal value of the currency, is calculated to 21.52%.
 ]]></dcterms:abstract>
			</dc:description>
            <dc:identifier scheme="dcterms:URI"><![CDATA[https://jfr.ut.ac.ir/article_36637_48b9b865711b2ad49d29d894d611c11c.pdf]]></dc:identifier>
			<dc:identifier scheme="ags:DOI"><![CDATA[10.22059/jfr.2012.36637]]></dc:identifier>
			<dc:type><![CDATA[Journal Article]]></dc:type>
			<dc:format><dcterms:medium><![CDATA[text]]></dcterms:medium></dc:format>
			<dc:language><![CDATA[English]]></dc:language>
			<dc:source><![CDATA[https://jfr.ut.ac.ir/]]></dc:source>
			<dc:source><![CDATA[Financial Research Journal]]></dc:source>
		</ags:resource>

</ags:resources>