Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model

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...

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Main Authors: Esmaiel Abounoori, Mohammadreza Abdollahi
Format: Article
Language:fas
Published: University of Tehran 2012-07-01
Series:تحقیقات مالی
Subjects:
Online Access:https://jfr.ut.ac.ir/article_36628_3dbb24322744cda445e3920e80a50fdf.pdf
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author Esmaiel Abounoori
Mohammadreza Abdollahi
author_facet Esmaiel Abounoori
Mohammadreza Abdollahi
author_sort Esmaiel Abounoori
collection DOAJ
description 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. <br />  <br />
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spelling doaj.art-88f80d7289d34e4ca9f36693921be5982022-12-22T02:00:48ZfasUniversity of Tehranتحقیقات مالی1024-81532423-53772012-07-0114111610.22059/jfr.2012.3662836628Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH ModelEsmaiel Abounoori0Mohammadreza Abdollahi1. Professor of Econometrics & Social Statistics, Department of Economics, University of Semnan, IranPh.D. student in Financial Economics, Department of Economics, Allameh Tabatabai University, Tehran, IranThis 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. <br />  <br />https://jfr.ut.ac.ir/article_36628_3dbb24322744cda445e3920e80a50fdf.pdfvolatility transmissionmgarchmodeling volatility
spellingShingle Esmaiel Abounoori
Mohammadreza Abdollahi
Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
تحقیقات مالی
volatility transmission
mgarch
modeling volatility
title Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
title_full Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
title_fullStr Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
title_full_unstemmed Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
title_short Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model
title_sort modeling different sector volatility of iran stock exchange using multivariate garch model
topic volatility transmission
mgarch
modeling volatility
url https://jfr.ut.ac.ir/article_36628_3dbb24322744cda445e3920e80a50fdf.pdf
work_keys_str_mv AT esmaielabounoori modelingdifferentsectorvolatilityofiranstockexchangeusingmultivariategarchmodel
AT mohammadrezaabdollahi modelingdifferentsectorvolatilityofiranstockexchangeusingmultivariategarchmodel