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Modeling systemic risk and dependence structure between cryptocurrency and stock markets using a variational mode decomposition-based copula meth (VMD- Copula)
Roghaye Mohsi Nia, Ali Rezazadeh, Yousef Mohammadzadeh, Shahab Jahangiri,
Volume 15, Issue 55 (5-2024)
Abstract
The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency and the stock market index. In this study, the total index of Tehran Stock Exchange has been used as a representative of the developing stock market and the index (S&P500) has been used as a representative of the developed stock market. using daily data during the period from 8 August 2015 to 21 February 2023. The results show that there is no structural dependence between the return Bitcoin and Iran stock market , either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicates that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Also, in the long term, for the return of Bitcoin cryptocurrency and the S&P500 stock index, Clayton's copula function was chosen in the first place as the appropriate model to explain the correlation. There is no correlation between the returns of Bitcoin and the s&p500 stock index in the short term. The findings of this study indicate the important role of cryptocurrencies in investors' portfolios as they act as a diversified option for investors and confirm that cryptocurrencies are a new investment asset class. Furthermore, it analyzes the upside and downside risk spillovers between stock markets and the cryptocurrency market by quantifying market risk measures, namely the conditional VaR (CoVaR) and the delta CoVaR (ΔCoVaR). The results indicate that Bitcoin, Ethereum and Ripple cannot be considered a strong hedge during the time of crisis. The speculative nature of cryptocurrencies and risks embedded in Bitcoin, Ethereum, and Ripple increases the risk flow to stock markets during a crisis, thus rendering the hedging costlier.  increases the risk flow to stock markets during a crisis, thus rendering the hedging costlier.
 
Investigating the impact of monetary, financial and exchange market conditions on fuel smuggling in the Iranian economy using the SVAR model
Mrs Zahra Hashemi, Prof Nazar Dahmarde,
Volume 15, Issue 55 (5-2024)
Abstract
The article examines the impact of monetary, financial and exchange market pressure indexes on fuel and petroleum products smuggling in Iran's economy by applying SVAR structural vector autoregression model based on seasonal data of 1390-1400. the model results show that the impulse response from the domestic and FOB Persian Gulf price difference of petroleum products, fuel smuggling constantly aggravates and its effect is increasing. In addition, the impulse response of the financial condition index and monetary conditional index is not very important, and the impulse from the exchange market pressure index has a negative effect at first, and after 5 periods of shock, it becomes zero and its effect becomes positive.
The results of the variance decomposition analysis show that in different periods, the fluctuations of the fuel smuggling variable are explained by the difference between domestic and FOB Persian Gulf price differenence of petroleum products. In fact, fixing the domestic oil products price below the export parity price is a very inefficient way to subsidize domestic oil consumption. In addition to the waste caused by low price, it has provided rents for smugglers and worsens the country's fiscal imbalance.

Combined Analysis of Dynamic and Nonlinear Dependence between Housing Market Volatility and Construction Firms
Saeed Kianpoor, Reza Shamsollahi, Jafar Zarin,
Volume 15, Issue 57 (11-2024)
Abstract 
Objective: The aim of this research is to investigate the dynamic and nonlinear dependence between housing market fluctuations and the returns of construction companies on the Tehran Stock Exchange.
Materials and Methods: The data used include construction service returns, land price returns, inflation, exchange rate returns, stock index returns, industrial production returns, and rental returns in the period 1991 to 2023 using T-GARCH, Copula-GARCH, and DCC-GARCH.
Results: The results indicate the existence of strong and nonlinear dependencies between the returns of construction services and housing market variables, especially the returns of land prices and rents. The T-GARCH model showed a high fit (R-squared=0.969) and confirmed that past shocks have a significant impact on current fluctuations. The Copula-GARCH model confirmed the nonlinear dependencies with an average correlation coefficient of 0.31, while the rolling correlation analysis in the DCC-GARCH model indicated dynamic changes in dependencies in different economic periods. The Kendall-Tao correlations in boom (0.928) and recession (0.923) periods also showed a small but significant difference in the intensity of dependencies. The sensitivity analysis showed that changes in industrial production have a significant impact on the returns of construction services.
Conclusion: These findings are useful for investors and policymakers in risk management and setting economic policies in the Iranian housing market.

Modeling the Impact of Money Market Variables on Tehran Stock Index: The Moderating Role of Economic Policy Uncertainty in ARDL Framework
Mohammad Kaveh Barahooei Jahanshahi, Ali Barahooei Jahanshahi, Mehdi Sadeghi Shahedani,
Volume 15, Issue 58 (2-2025)
Abstract
The present study aims to model and investigate the impact of money market variables on stock market performance (capital market). Money market variables can directly or indirectly affect stock market performance. This research examines the influence of interest rates, exchange rates, inflation rates, liquidity, and legal reserve rates on the stock price index. Additionally, another objective of this study is to investigate the effect of economic policy uncertainty on the relationship between monetary variables and the aggregate stock price index, and how monetary variables are guided and their impact on the stock market. The research period spans ten years, from 1392 to 1401. The hypothesis testing results, using seasonal time series data and the Autoregressive Distributed Lag (ARDL) model, indicated that the effect of money supply and exchange rate on the aggregate stock price index is positive and significant. However, the effects of the interest rate and legal reserve rate are not significant. Furthermore, based on an index for economic policy certainty, this research demonstrates that the relationship between the interbank interest rate, money supply, legal reserve rate, and exchange rate with the aggregate price index is influenced by economic policy uncertainty.

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