content in the Big Data Analysis of volatility spillovers of user generated content in the Tehran Stock Exchange

Document Type : Original Article

Authors
Sediegheh Taghieh 1
HAMID Khajehmahmoodabadi 2
sayed yahya abtahi 2
seyed hasan hatami nasab 3
1 PhD student in financial engineering, Yazd Branch, Islamic Azad University, Yazd, Iran.
2 Department of Financial Management, Yazd Branch, Islamic Azad University, Yazd, Iran
3 Department of Business Management, Yazd Branch, Islamic Azad University, Yazd, Iran
10.30495/jik.2023.76064.4444
Abstract
The present article content in the Big Data Analysis of volatility spillovers of user generated content in the Tehran Stock Exchange. In this research, the variables of stock return rate of each product, positive and negative comments, Google searches about the product, new product announcement, business development, executive amendments and legal issues for Iran Khodro and Saipa stocks have been used to estimate the models. The data of Iran Khodro shares from 1397 to 1400 and Saipa shares from 1400 to 1400 were collected from the stock exchange website. The random sampling method is simple. The results of the research showed that there is a significant and direct relationship between legal issues in Iran Khodro shares and positive comment fluctuations, there is a significant and direct relationship between legal issues in Iran Khodro shares and negative comment fluctuations, between legal issues in Iran Khodro shares and There is a significant and direct relationship between Google fluctuations, there is a significant and direct relationship between legal issues in Saipa shares and positive comment fluctuations, and there is a significant and direct relationship between legal issues in Iran Khodro shares and negative comment
Keywords
big data analysis
fluctuating production content contagion
Tehran Stock Exchange
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