Measuring the Volatility Connectedness of Industries in Tehran Stock Exchange - The Novel Approach of Spectral Variance Decomposition
Quarterly Journal of Securities Exchange

Quarterly Journal of Securities Exchange

Measuring the Volatility Connectedness of Industries in Tehran Stock Exchange - The Novel Approach of Spectral Variance Decomposition

Document Type : Original Article

Authors
1 Department of Financial Engineering, Faculty of Industrial Engineering, K. N. Toosi University of Technology,, Tehran, Iran.
2 Associate professor at the Department of Industrial Engineering K. N. Toosi University of Technology, Tehran, Iran.
3 MSc. Department of Financial Management, Kharazmi University, Tehran, Iran
Abstract
The study of volatility connectedness in the stock market is one of the essential issues in finance. This study aims to measure the volatility connectedness in different industries of the Tehran Stock Exchange in different time horizons. The research data were collected daily from March 2015 to September 2021 and examined by spectral variance decomposition. Findings of research show that short-term volatility connectedness accounts for a significant proportion of connectedness relationships among stock exchange industries. This means that the impact of shocks on the Tehran Stock Exchange industry is more short-term. At all time horizons, a significant percentage of the variance of the forecast error was due to shocks within the same industry. In addition, dynamic volatility connectedness also indicates that it increases significantly with the increase of excitement in the Tehran Stock Exchange. The results of this study help to better analyze by investors and risk hedging of investment companies.
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Subjects

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