Designing a Comprehensive Stress Index for the Tehran Stock Exchange and Its Causal Relationship with the Gold Coin and Foreign Exchange Markets
Keywords:
Comprehensive Stress Index (SSI), DCC-MGARCH model, machine learning, Granger causality test, gold coin market, foreign exchange marketAbstract
This study aims to design a Comprehensive Stress Index (SSI) for the Tehran Stock Exchange using multivariate GARCH models (DCC-MGARCH) and machine learning (Random Forest) and to examine its causal relationship with the gold coin and foreign exchange markets. Daily time series data of selected Tehran Stock Exchange indices from November 22, 2014, to November 21, 2024, were collected and analyzed. First, the systemic risk (∆CoVaR) of each index was calculated; then, the optimal weights were determined using the Random Forest model, and the SSI was constructed following the methodology of Holo and colleagues (2012). Stability, shock, and predictability tests confirmed the validity of the index. The Granger causality test revealed a significant one-way causal relationship from the foreign exchange market to the SSI (p-value = 0.028), while no significant relationship was observed with the gold coin market. These findings highlight the influence of exchange rate fluctuations on the systemic risk of the stock market and provide a useful tool for policymakers.
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Copyright (c) 2025 Elham Babaheidarian (Author); Farhad Hanifi; Mirfiz Fallah Shams (Author)
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