Journal of Money and Economy

In economies where banks play a key role in aggregating savings and allocating credit to various sectors, it is crucial to evaluate the performance of the banking system using appropriate methods. This research paper presents a model for evaluating the efficiency of commercial banks listed in the Tehran Stock Exchange during the period from 2015 to 2020, with a focus on the impact of credit risk. The study employs a two-step descriptive-correlation retrospective method to rank the banks and explain the role of credit risk in their efficiency. Specifically, the efficiency of the banks is determined using inputs and outputs based on DEA (Data Envelopment Analysis) models. The calculation of efficiency using ideal SBM (Slacks-Based Measure) and DEA methods reveals that Mellat, Saderat, and Tejaret banks were the most efficient during the study period. Furthermore, Tobit and logistic regression models are used to investigate the relationship between the main determinants of credit risk and the efficiency of commercial banks. The findings indicate a statistically significant relationship between the two factors. Overall, this paper highlights the importance of evaluating the efficiency of the banking system in bank-oriented economies and provides a useful model for doing so. The research paper highlights the significant impact of credit risk on bank efficiency, emphasizing its role in shaping effective risk management strategies within the banking sector. It suggests that banks should prioritize these factors to enhance their operational efficiency.

The present study investigated the effect of imposing international financial sanctions on international risk sharing in developing countries during 2011-2022 using the propensity score matching (PSM) approach. International risk sharing refers to the processes in which countries with different income prospects share the risk of income fluctuations with one another by conducting commercial and financial transactions internationally. Therefore, their income and consumption no longer depend solely on domestic production, but also depend on the production of other countries (countries that own their assets). Since, international capital flows are the main tools for international risk sharing. Imposing international financial sanctions on a country reduces international capital flows and therefore reduces international risk sharing in that country. As the results showed, the impact of financial sanctions on international risk sharing has been negative and significant because the measure of the international risk sharing index in countries that were not subject to sanctions (control group) was 0.5877 and in countries that were subject to sanctions (treatment group) was 0.2431. Therefore, imposing international financial sanctions has reduced risk sharing in developing countries.

Technical and fundamental analysis are the two principal methods for studying financial markets. However, access to internet and social media helps investors make better decisions. Social media has turned into a source of information for investors. Surowiecki (2005) found social media can predict better than individuals, known as the Wisdom of the Crowd. In this study, we tried to evaluate the wisdom of the crowd’s potential to improve stock price prediction accuracy. So, we developed a prediction model by Long Short-Term Memory based on the wisdom of the crowd. Persian users' opinions on Tehran Stock Exchange stocks were gathered for 8 months and classified as buying, sell, or neutral. During the research period, people mentioned 823 stocks and 52 stocks, which had over 100 recommendations, were chosen. Prediction model accuracy was increased for 19 stocks. While, for 33 stocks were not more accurate with the wisdom of the crowds and social media features. It is important to note that investors apply critical thinking. The wisdom of the crowd can be one input to the decision-making process, along with other related factors. The wisdom of the crowd provides an opportunity to access vast and diverse information. Getting opinions from various people can provide valuable insights into economics and investment preferences. The wisdom of the crowd can help reveal the flow of money. The combination of the wisdom of the crowd, fundamental, and technical analysis can be a useful tool for traders in detecting capital flow and profitable opportunities.

The theory of relative purchasing power parity to determine the long-run trend of the exchange rate in Iran is quite sensitive to the base year selection. So, by changing the base year, trends with a level difference of several hundred percent are obtained. It means that the long-run trend of the real exchange rate is not at a constant level. In other words, contrary to the PPP theory, the real exchange rate trend is not stationary. Empirical studies consider the non-stationary change in terms of trade resulting from the changes in the real oil price as one of the reasons. This study examines the nexus between the real exchange rate and terms of trade in Iran from 1960 to 2020, using the autoregressive distributed lag approach to cointegration as the estimation method. We find that higher terms of trade lead to a decline in the actual exchange rate and vice versa. The results indicate a long-run relationship, which means that the condition needed to estimate the long-term trend of the exchange rate in Iran is to have the same terms of trade in the base year.

The aim of this study was to assess the performance of the Iranian currency exchange market by analyzing the dynamic conditional correlation (DCC) between the Iranian currency exchange rate and the free market exchange rate of the US dollar in Iran. This analysis was conducted for both the same day and with a one-day lag, spanning from June 20 to October 30, 2022. The results of the study indicate that the DCC for concurrent days (denoted as dcc0) stood at 48%. Meanwhile, the DCC for the Iranian currency exchange rate with a one-day delay compared to the free market US dollar exchange rate in Iran (referred to as dcc+1) was 17%, and the DCC for the free market US dollar exchange rate with a one-day lag behind the Iranian currency exchange rate (referred to as dcc-1) was 35%.

The primary aim of this study is to investigate the parameters involved in the formulation of the Network Policy-Making, commonly referred to as policy networks, with a particular emphasis on public accountability within the Ministry of Economic Affairs and Finance. This investigation primarily focuses on the electronic Treasury. The statistical population comprises the managers who are employed at the Deputy Ministry for Financial Supervision, a division operating inside the General Directorate of the Ministry of Economic Affairs and Finance. In order to ascertain the appropriate sample size, a questionnaire was administered using a multi-stage cluster sampling approach, resulting in a total sample size of 282 participants. The hypotheses were examined using the structural equation modeling method and the software LISREL. The findings indicated that various factors related to network policy-making, such as organizational sustainable development, organizational goal orientation, participative decision-making, and organizational identity formation, have a positive and significant impact on public accountability.