Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012

In our paper we use data mining to compare the volatility structure of high (daily) and low (weekly, monthly) frequencies for seven Romanian companies traded on Bucharest Stock Exchange and three market indices, during 1997-2012. For each of the 10 time series and three frequencies we fit a GARCH-in...

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Main Authors: Iulian PANAIT, Ecaterina Oana SLĂVESCU
Format: Article
Language:English
Published: General Association of Economists from Romania 2012-05-01
Series:Theoretical and Applied Economics
Subjects:
Online Access: http://store.ectap.ro/articole/721.pdf
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spelling doaj-a153163a857c45f3be4fb31bdc5d01642020-11-25T00:19:42ZengGeneral Association of Economists from RomaniaTheoretical and Applied Economics1841-86781844-00292012-05-01XIX5557618418678Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012Iulian PANAIT0Ecaterina Oana SLĂVESCU1 Bucharest Academy of Economic Studies Bucharest Academy of Economic Studies In our paper we use data mining to compare the volatility structure of high (daily) and low (weekly, monthly) frequencies for seven Romanian companies traded on Bucharest Stock Exchange and three market indices, during 1997-2012. For each of the 10 time series and three frequencies we fit a GARCH-in-mean model and we find that persistency is more present in the daily returns as compared with the weekly and monthly series. On the other hand, the GARCH-in-mean failed to confirm (on our data) the theoretical hypothesis that an increase in volatility leads to a rise in future returns, mainly because the variance coefficient from the mean equation of the model was not statistically significant for most of the time series analyzed and on most of the frequencies. The diagnosis that we ran in order the verify the goodness of fit for the model showed that GARCH-in-mean was well fitted on the weekly and monthly time series but behaved less well on the daily time series. http://store.ectap.ro/articole/721.pdf stock returnsvolatilitypersistenceGARCH modelemerging marketsdata mining
collection DOAJ
language English
format Article
sources DOAJ
author Iulian PANAIT
Ecaterina Oana SLĂVESCU
spellingShingle Iulian PANAIT
Ecaterina Oana SLĂVESCU
Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
Theoretical and Applied Economics
stock returns
volatility
persistence
GARCH model
emerging markets
data mining
author_facet Iulian PANAIT
Ecaterina Oana SLĂVESCU
author_sort Iulian PANAIT
title Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
title_short Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
title_full Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
title_fullStr Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
title_full_unstemmed Using Garch-in-Mean Model to Investigate Volatility and Persistence at Different Frequencies for Bucharest Stock Exchange during 1997-2012
title_sort using garch-in-mean model to investigate volatility and persistence at different frequencies for bucharest stock exchange during 1997-2012
publisher General Association of Economists from Romania
series Theoretical and Applied Economics
issn 1841-8678
1844-0029
publishDate 2012-05-01
description In our paper we use data mining to compare the volatility structure of high (daily) and low (weekly, monthly) frequencies for seven Romanian companies traded on Bucharest Stock Exchange and three market indices, during 1997-2012. For each of the 10 time series and three frequencies we fit a GARCH-in-mean model and we find that persistency is more present in the daily returns as compared with the weekly and monthly series. On the other hand, the GARCH-in-mean failed to confirm (on our data) the theoretical hypothesis that an increase in volatility leads to a rise in future returns, mainly because the variance coefficient from the mean equation of the model was not statistically significant for most of the time series analyzed and on most of the frequencies. The diagnosis that we ran in order the verify the goodness of fit for the model showed that GARCH-in-mean was well fitted on the weekly and monthly time series but behaved less well on the daily time series.
topic stock returns
volatility
persistence
GARCH model
emerging markets
data mining
url http://store.ectap.ro/articole/721.pdf
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AT ecaterinaoanaslavescu usinggarchinmeanmodeltoinvestigatevolatilityandpersistenceatdifferentfrequenciesforbuchareststockexchangeduring19972012
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