Behavioral Modeling of Stock Index Volatility with Emphasis on Market Risk and Trading Volume Fluctuations Using Structural Vector Autoregression Models
Keywords:
Stock index volatility, Market risk, Trading volume volatility, Bitcoin rate, Global gold ounceAbstract
The capital market is one of the most critical sectors of the economy, and its status is closely linked to the overall economic structure of a country. Due to the transparency and speed of transactions, the stock exchange is recognized as a significant investment option. In other words, an active stock market facilitates corporate financing and channels idle and often unproductive small-scale capital into productive ventures. In most countries, stock indices are considered one of the most reliable primary indicators for evaluating financial markets. The Tehran Stock Exchange's overall index reflects the general trend of Iran’s capital market and indicates the broader status of the investment landscape. Therefore, understanding and analyzing the overall index and its fluctuations can assist capital market participants in making more informed decisions. Additionally, the stock index is widely used by financial researchers to compare the performance of the capital market with other markets and to measure the impact of various factors on market returns. This study is applied in terms of its objective and descriptive-analytical in terms of its nature. It falls within the category of ex-post facto research (using data from March 20, 2012, to March 19, 2024). The estimation method employed in the study is the Structural Vector Autoregression (SVAR) approach. The present article examines behavioral modeling of stock index volatility with a focus on market risk and trading volume fluctuations. Initially, the research model is specified, followed by stationarity testing using the Phillips-Perron method. Next, cointegration tests are conducted using the Johansen-Juselius approach. Subsequently, the model is estimated, and stability tests, impulse response functions (IRF), and variance decomposition analyses are carried out. The results of model estimation indicate that the coefficients of most key variables influencing the Tehran Stock Exchange’s overall index volatility align with the theoretical foundations of the subject. The main variables that are essential and interpretable within the results of the SVAR model include impulses originating from market risk premium, global gold ounce price fluctuations, exchange rate fluctuations, Bitcoin price volatility, OPEC oil price volatility, and fluctuations in stock trading volume. Based on the estimation results, Bitcoin price and market risk premium have no significant impact on stock index volatility. However, the other explanatory variables in the model significantly affect stock index fluctuations at a 95% confidence level.
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Copyright (c) 2025 Mahsa Rahavi (Author); Gholamreza Zomordian (Corresponding author); Bahman Bani Mahd (Author)
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