An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model

The paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks. The result...

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Main Authors: Wu, Simin, Md Yusof, Zahayu, Misiran, Masnita
Format: Article
Language:English
Published: Science Research Publishing 2024
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/30889/1/JMF%2014%2001%202024%20%2001-17.pdf
https://doi.org/10.4236/jmf.2024.141001
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author Wu, Simin
Md Yusof, Zahayu
Misiran, Masnita
author_facet Wu, Simin
Md Yusof, Zahayu
Misiran, Masnita
author_sort Wu, Simin
collection UUM
description The paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks. The results show that the correlation between the Shanghai Composite Index and stocks of agriculture of China exhibits time-varying characteristics and dynamic. The fluctuations in correlation are large. This study fills the blank of comparative study on risk volatility and correlation between different stocks in the same stock market by using DCC-GARCH model
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spelling uum-308892024-06-23T08:26:22Z https://repo.uum.edu.my/id/eprint/30889/ An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model Wu, Simin Md Yusof, Zahayu Misiran, Masnita QA Mathematics The paper selects the daily trading data of three stocks in the agricultural sector of the Chinese stock market from 1st September 2015 to 31st August 2021. It uses the DCC-GARCH model to study the correlation between these stocks to examine the volatility and conductivity of their risks. The results show that the correlation between the Shanghai Composite Index and stocks of agriculture of China exhibits time-varying characteristics and dynamic. The fluctuations in correlation are large. This study fills the blank of comparative study on risk volatility and correlation between different stocks in the same stock market by using DCC-GARCH model Science Research Publishing 2024 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/30889/1/JMF%2014%2001%202024%20%2001-17.pdf Wu, Simin and Md Yusof, Zahayu and Misiran, Masnita (2024) An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model. Journal of Mathematical Finance, 14 (1). pp. 1-17. ISSN 2162-2442 https://www.scirp.org/journal/paperinformation?paperid=129844 https://doi.org/10.4236/jmf.2024.141001 https://doi.org/10.4236/jmf.2024.141001
spellingShingle QA Mathematics
Wu, Simin
Md Yusof, Zahayu
Misiran, Masnita
An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title_full An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title_fullStr An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title_full_unstemmed An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title_short An Empirical Analysis of the Correlation of Agricultural Sectors in the Chinese Stock Market Based on the DCC-GARCH Model
title_sort empirical analysis of the correlation of agricultural sectors in the chinese stock market based on the dcc garch model
topic QA Mathematics
url https://repo.uum.edu.my/id/eprint/30889/1/JMF%2014%2001%202024%20%2001-17.pdf
https://doi.org/10.4236/jmf.2024.141001
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