The effect of manufacturing purchasing managers index on stock market index in Iran
Subject Areas :
Financial Economics
Sakineh Sejoodi
1
,
Parviz Jafarzadeh Barenji
2
1 - Department of Economics and Management, Tabriz University, Tabriz, Iran. (corresponding author), sakinehsojoodi@gmail.com
2 - Department of Economics and Management, Tabriz University, Tabriz, Iran.
Received: 2023-06-28
Accepted : 2023-08-23
Published : 2023-09-23
Keywords:
G17,
E32,
Granger causality,
Total Stock Price Index,
Manufacturing Stock Price Index,
Keywords: Purchasing Managers Index,
Johansen Cointegration. JEL classification: E27,
Abstract :
Abstract
Considering the increasing development of the stock exchange market and its potential for creating economic growth and development of the country, it is very important to study the factors affecting this market and this issue is very important for all users of this market. The main purpose of this study is to investigate the effect of the manufacturing Purchasing Managers Index (PMI) on the stock price index in Iran. Therefore, the present study has used the monthly data from 2018:10 to 2022:11 and using the Granger causality method and Johansen co-integration to investigate the relationship between Purchasing Managers Index and total stock price index and manufacturing stock price index.
The results indicate that there is a one-way causality from the growth of the manufacturing purchasing managers index to the growth of the total stock price index and the growth of the manufacturing stock price index. Also, based on Johansen's cointegration test, there is a long-term positive relationship between the growth of manufacturing purchasing managers index and the growth of total stock price index, and also between the growth of manufacturing purchasing managers index and the growth of manufacturing stock price index. Given that the increase in PMI indicates economic prosperity in the manufacturing sector, this positive relationship shows that, as expected, stock price indices react positively to improvement signals in the manufacturing sector and negatively to negative signals.
References:
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