Dr Reza Akbarian, Mr Farhad Zand, Dr Ahmad Sadraei Javaheri, Dr Hojat Parsa,
Volume 14, Issue 52 (9-2023)
Abstract
Market economies rely on the payment system to facilitate trade and exchange between businesses and consumers in the product market. "Payment" is the transfer of monetary value. The ability to control monetary policy instruments is one of the challenges of monetary policy in Iran. The reduction of the central bank's control over the money supply and the implementation of monetary policy is due to the change that occurs in the monetary base and the monetary multiplier. The structure of stochastic dynamic general equilibrium models, like other general equilibrium models, aims to describe the behavior of the entire economy and use decision interaction analysis. Wisdom is built on different levels.Due to the existence of sanctions and the lack of clear and correct information on the amount of sales of crude oil and other export items and petroleum products and unnecessary complications in doing the economics paper, it is considered closed, but if the correct information in can be considered as the expansion of the economy.The findings of this section indicate that the central bank's reaction to the growth rate of the total index of the real sector of the economy against the reaction to the deviation of the total index from its long-term equilibrium level can be more effective in reducing the real effects of the shocks of the real sector of the economy on macroeconomic variables. . Because the central bank controls the status of asset returns in other parallel markets such as currency, price levels, deposits and loans, and therefore the reaction to the emotional dynamics of the market return against the reaction to the market index level further guarantees macroeconomic stability.
English Habib Habib Shirafken Lamso, English Amir Gholami, English Seyyed Mehdi Ahmadi,
Volume 14, Issue 52 (9-2023)
Abstract
This research aims to model the effective systematic risks of financial recovery in the insurance industry. This research is a type of applied research. The period of research is 11 years (1400-1390). For this purpose, the information on 14 systematic risks affecting the financial solvency of insurance companies was entered into dynamic, selective, and Bayesian averaging models. Based on the error rate, the Bayesian averaging model had the highest accuracy among the selected models. After estimating the model, 5 economic growth risks, inflation uncertainty, exchange rate, sanctions, and KOF index were selected; Also, based on the results of the TVPFAVAR model, it was assessed that the impact shock of the selected variables in the long-term period is stronger than the short-term period, which indicates that the elasticity of financial prosperity is greater than the changes in systematic risk variables compared to the short-term elasticity. Based on the results of economic growth and the KOF index, the positive effect and uncertainty variables of inflation, exchange rate, and sanctions hurt financial wealth in the general trend.
Dc Azam Ahmadyan,
Volume 14, Issue 52 (9-2023)
Abstract
The disclosure of bank information is a requirement of the Basell Committee in global level, as well as regulations governing the disclosure of information by credit institutions in Iran. According to these regulations, banks are obligated to disclose financial information, risk management information, corporate governance and auditing information, and information related to significant events. This article examines the short-term and long-term effect of information disclosure on financial soundness of banks, with emphasis on the size and ownership of banks and using the PMG-ARDL model during 2014 - 2021. Results indicate an inverse U-shaped relationship between information disclosure and the financial soundness of banks. So an increase in information disclosure, the level of financial soundness of banks initially improves, but then decreases after reaching an optimal level. Additionally, there is a U-shaped relationship between information disclosure and the financial soundness of banks based on size. So an increase in disclosure and bank size, the financial soundness of banks initially decreases, but then increases after reaching a minimum point.
Alireza Moradi, Mehdi Mohammadi,
Volume 14, Issue 52 (9-2023)
Abstract
The main goal of this research is the impact of the wage gap between managers and workers on stock returns: the mediating role of investors' supervision. In terms of categorizing the research according to the method of data collection, the current research is of the causal and post-event type. The research method is correlation. In this research, library methods were used to collect information. Library methods have been used to collect information on the theoretical foundations and literature of the topic, library resources, articles and required books have been used, and Kodal website and Rahavard Novin software have also been used to obtain statistical information. In this chapter, using data collected from a statistical sample of 76 companies admitted to the Tehran Stock Exchange in the period of 2015-2022. Hypotheses were tested using Pearson's correlation test and Limer's F test in the Eviews13 software environment. The results of the regression test showed that the wage gap between managers and workers with the mediating role of investors' supervision has a significant effect on stock returns.
Mr Nader Hashemnezhad, Dr Sajjad Barkhordari, Dr Ghahreman Abdoli,
Volume 14, Issue 52 (9-2023)
Abstract
Bitcoin is the leader of cryptocurrencies and has the largest market value as a digital asset in most international investment portfolios. However, compared to traditional assets, the nature of this cryptocurrency is not clear from a behavioral perspective. Examining this by following the behavior of the distribution tail or limit behaviors is one of the methods that can help researchers about the nature of this cryptocurrency, because this corresponds to the investigation of limit behaviors and in critical times of this currency. In this regard, this research has used quantile regression to estimate CAViaR models. In addition, to study the effect of each variable on the Bitcoin trend, the GARCH approach has also been used.
The results of this research for the daily period from 2018 June 26 to 2022 May 11, Wednesday, showed that by analyzing the 5% percentile quantile regression, examining the behavior of the right tail of Bitcoin distribution, the behavioral similarity of this currency with all the investigated assets is confirmed. This shows that in a situation where the returns of traditional financial markets are positive and the markets are rising, the behavior of cryptocurrencies aligns with the general behavior of the markets. However, examining the behavior of the left tail of the distribution of the variables shows that Bitcoin has no similarity in behavior with the rest of the traditional assets. In other words, when markets are bearish, Bitcoin's behavior is not aligned with traditional markets. However, the return of the homogenous index does not affect the trend of Bitcoin, which was predictable due to the non-compliance of domestic financial markets with international markets due to Iran's economic isolation and international sanctions. Therefore, until the period investigated by this study, Bitcoin has shown a behavior other than known assets and investing in it is still facing the risk of capital burnout, so it is recommended that investors observe risk management in the arrangement of their portfolios.
Fatemeh Ansari, Shahab Jahangiri, Ali Rezazade,
Volume 14, Issue 53 (12-2023)
Abstract
Objective: The aim of this research is to provide a practical guide for investing in the Tehran Stock Exchange by combining technical analysis techniques with advanced machine learning methods. Focusing on the analysis of buy and sell signals in selected indices of the Tehran Stock Exchange, the study seeks to evaluate the effectiveness of machine learning models in predicting market trends.
Materials and Methods: In this study, the daily data of six selected indices of the Tehran Stock Exchange, including financial, petroleum products, automotive, pharmaceutical, food, and basic metals indices, were analyzed from 2020 to January 2025. Four machine learning models, including Linear Model, Random Forest, Artificial Neural Network, and Support Vector Regression, were utilized alongside two technical analysis strategies, TEMA and MACD, to generate and evaluate buy and sell signals.
Results: The results indicated that machine learning models, particularly Random Forest and Artificial Neural Network, performed better in identifying buy and sell signals when combined with TEMA and MACD strategies. These models were able to predict market trends with higher accuracy, and the signals they generated were mostly consistent with actual price changes. The food, automotivation and financial and basic metals indices demonstrated greater sensitivity to these analyses.
Conclusion: The combination of machine learning methods with technical analysis strategies can provide investors with a powerful tool for decision-making in the Tehran Stock Exchange. This research demonstrated that using these methods can not only improve the accuracy of buy and sell signals but also reduce investment risk and increase returns. Utilizing these models can be recommended as part of an investment strategy for analysts and investors.
Originality: This research is the first quantitative study that seeks to conceptualize buy and sell signals using the combined method of machine learning and technical analysis as one of the basic tools to guide investors. |
Majid Shafiei, Parviz Rostamzadeh, Mohammad Rastegar, Zahra Dehghan Shabani,
Volume 14, Issue 53 (12-2023)
Abstract
The stock market, as one of the vital components of the capital market, is an important part of the country's economy that can manage the flow of capital, optimize capital allocation, and thereby contribute to economic growth and development. More accurate prediction of the stock market trend can help investors' decision-making for higher returns by reducing risk. In general, the stock market is constantly changing and many factors influence the trend of this market, so predicting the patterns of movement in the stock exchange requires sufficient information about the past and influencing factors of the market. This article is part of the forecast of the stock market index of Iran, seeking to interpret the model and identify the most influential economic variable on the price index prediction. For this purpose, daily stock market and economic data, during the period 1394-1401 were used. Machine learning models are also used for prediction and the Shapley Additive exPlanations (SHAP) to interpret how to predict and determine the most important variables in the predictive model. Based on results from tree-based ensemble methods, the proposed model in this study, ExtraTrees, performed best based on predictive error criteria. In the study of the feature importance is also based on the ExtraTrees model, in order of the dollar rate (Nima), unemployment rate, dollar rate of market and liquidity, the most important economic variables influencing the forecast model. Also, according to other models used in the research, liquidity is the most effective variable on the stock index trend. Finally, it can be said that the most effective monetary variables on the stock market index in Iran are liquidity and exchange rate variables, so monetary policymakers and stock market investors should be more sensitive to these variables in their decisions.
Parvaneh Salatin, Mahdi Molania, Mahmood Mahmoodzadeh, Mohammad Hosein Fatehi,
Volume 14, Issue 53 (12-2023)
Abstract
Today, information and communication technology affects all aspects of human life. The result of which is a transformation in all methods of production and distribution to education, exchanges and human relations. On the other hand, the requirement for the realization of economic development and growth is the higher growth rate in poor and underdeveloped areas than in rich and developed areas, which is proposed as the hypothesis of convergence. In this regard, regional inequalities are a fundamental challenge for the development of regions and these inequalities are a serious threat to create a balanced development of regions. Therefore, the main goal of the current study is to investigate the convergence of Fava among the provinces of the country. The results using the Nahar and Inder method during the period of 2002-2013 showed that out of the 30 investigated provinces, divergence in land use occurred in 22 provinces. Also, at the infrastructure level, the average slope of 31 provinces is positive, but the t-value is significant for the provinces of South Khorasan, Khuzestan, Alborz and Fars, which shows that digital divergence has occurred in these provinces during the period under review. Therefore, it can be seen that although in terms of infrastructure, we have had less divergence at the level of the provinces, but in terms of usage, this gap and divergence has increased.
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Learned Shima Jahangiry, Dr Mostafa Rajabi, Dr Mostafa Emadzadeh, Dr Majid Sameti,
Volume 14, Issue 54 (2-2024)
Abstract
In Islamic and conventional banks, there may always be differences in efficiency, cost gap ratio and credit risk; Therefore, the purpose of this study was to investigate the relationship between credit risk, cost gap ratio and efficiency of banks in selected Islamic and conventional countries. For this purpose, credit risk, efficiency and cost gap ratio were calculated for 50 Islamic banks and 50 non-Islamic (conventional) banks during the years 2013-2019 and regard, the results of the t-test showed that the credit risk, inefficiency and cost gap ratio are higher in Islamic banks than conventional banks. Also, the results of the Granger causality test showed that there is a bidirectional causality relationship between inefficiency and credit risk. But this relationship is a little weak. There is no causal relationship between credit risk and cost gap ratio, and there is a strong two-way causality relationship between inefficiency and cost gap ratio. The results in Islamic banks are almost similar to all banks. However, in Islamic banks, credit risk is not the Grangerian cause of inefficiency. Also, the significance level of other causal relationships is much higher. For conventional banks, there is no causal relationship between inefficiency and credit risk. There is no causal relationship between credit risk and cost gap ratio, and there is a two-way causality relationship between inefficiency and cost gap ratio. In addition, the results of variance analysis indicate that the cost gap and inefficiency have a close relationship with each other and their effectiveness is high. Credit risk also has a more or less effect on inefficiency during future periods. In Islamic banks, the effects of inefficiency and cost gap on credit risk are slightly higher. But the inefficiency of the cost gap has a high effectiveness. In conventional banks, credit risk has the same effectiveness as Islamic banks, but its effectiveness is somewhat less. Also, inefficiency has less effects than the cost gap. The cost gap, like Islamic banks, has a high effectiveness of inefficiency, and this effectiveness decreases over time.
Ghasem Palouj, Seyed Fakhreddin Fakhrhosseini,
Volume 14, Issue 54 (2-2024)
Abstract
This study explores how monetary and fiscal policies influence certain macroeconomic variables through a multi-sector stochastic dynamic general equilibrium (DSGE) model that includes input-output (IO) analysis. The focus is on the industrial sector, taking into account the specific conditions for Iran. The research uses quarterly data from Spring 2006 to Spring 2023 and references the 2016 input-output table provided by the Central Bank. In the nonlinear model, the original 89 activities from the input-output table have been simplified to 9, which includes the industrial sector and eight other sectors. Model parameters are estimated based on previous studies of the Iranian economy and data from the input-output table. The model's effectiveness is assessed by comparing simulation results with real-world data, which shows a strong correlation. The simulations indicate that increases in the money supply result in only a small rise in both total and industrial output. This leads to a slight decrease in total employment, while employment in the industrial sector experiences a minor increase. Similarly, increases in government spending show tiny improvements in overall and industrial output, accompanied by a slight drop in total employment and a small rise in the industrial sector. The findings suggest that the effects of monetary and fiscal policy shocks on output and employment, when accounting for input-output relationships and dividing the economy into nine sectors, better reflect the realities of the Iranian economy. Given the minimal influence of these policies on boosting production and economic growth, it is essential for them to be targeted and supported by additional measures and strategies.
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.
Samaneh Omidpour, Nader Mehregan, Ali Souri,
Volume 15, Issue 55 (5-2024)
Abstract
Introduction
Inflation, as one of the structural and chronic issues of Iran's economy, has always remained at high levels and has had widespread effects on macroeconomic variables and social welfare. The persistence of high inflation leads to instability in economic, social, and political spheres, to the extent that in some cases, inflationary instability can even result in the downfall of governments. Therefore, understanding the roots of inflation can help policymakers in designing appropriate policies to control and curb it.
Numerous studies have examined the factors influencing inflation and the role of inflation expectations.The literature review revealed that, so far, no comprehensive research has been conducted on the factors affecting inflation, with an emphasis on the nonlinear relationship between inflation expectations and budget deficits within the framework of the New Keynesian approach in Iran. Additionally, the study employs the Hodrick-Prescott filter and the Kalman filter to measure inflation expectations, which is considered an innovative approach. Furthermore, relying on the New Keynesian framework, this study examines the role of the output gap, budget deficit, exchange rate, and inflation expectations in the formation of inflation, specifically identifying the asymmetric impact of inflation expectations.
Method
The aim of this study is to examine the nonlinear effects of inflation expectations and budget deficits on inflation in Iran. For this purpose, the New Keynesian approach and the Nonlinear Autoregressive Distributed Lag (NARDL) method have been used to estimate the model over the period 1988 to 2022. Inflation expectations have been calculated using two methods: the Hodrick-Prescott filter and the Kalman filter.
Results and Discussion
The research findings indicate that the estimated models based on both filters yielded very similar results, demonstrating the robustness of the study's outcomes. Additionally, the results show that variables such as the output gap, inflation expectations, budget deficit, and exchange rate influence the inflation rate. Furthermore, inflation expectations have an asymmetric effect on inflation, where their increase leads to greater persistence and stability of inflation. Moreover, inappropriate fiscal policies exacerbate inflationary pressures by intensifying the budget deficit.
Keywords: Inflationary expectations, budget deficit, inflation, Iran, NARDL.
JEL: E62, E31,H62
Seyed Fakhrodin Fakhrehosseini, Dr Meysam Kaviani,
Volume 15, Issue 55 (5-2024)
Abstract
Predicting financial asset volatility is highly important because this information can help investors make more informed decisions regarding buying and selling. Accurate predictions can also reduce financial risks and identify profitable opportunities. Ultimately, the ability to forecast market changes improves portfolio management strategies and minimizes unexpected losses for investors. This study examines and predicts Bitcoin price volatility by using innovative data analysis models. The Heterogeneous Autoregressive (HAR) model and its variants were selected as the primary tools for modeling volatility because of their high capability to analyze volatility data across different time scales. Given the unique characteristics of cryptocurrency markets and rapid, unpredictable price fluctuations, the use of models that can simultaneously capture both short- and long-term volatility is of significant importance. In this study, high-frequency historical Bitcoin price data from 2018 to 2022, covering 60-minute, daily, weekly, and monthly intervals, were analyzed using the HAR, HARJ, HARQ, and HARQJ models. The results indicate that heterogeneous models have strong predictive power for Bitcoin price volatility, and incorporating jump factors into these models further improves their forecasting accuracy.
Predicting financial asset volatility is highly important because this information can help investors make more informed decisions regarding buying and selling. Accurate predictions can also reduce financial risks and identify profitable opportunities. Ultimately, the ability to forecast market changes improves portfolio management strategies and minimizes unexpected losses for investors. This study examines and predicts Bitcoin price volatility by using innovative data analysis models. The Heterogeneous Autoregressive (HAR) model and its variants were selected as the primary tools for modeling volatility because of their high capability to analyze volatility data across different time scales. Given the unique characteristics of cryptocurrency markets and rapid, unpredictable price fluctuations, the use of models that can simultaneously capture both short- and long-term volatility is of significant importance. In this study, high-frequency historical Bitcoin price data from 2018 to 2022, covering 60-minute, daily, weekly, and monthly intervals, were analyzed using the HAR, HARJ, HARQ, and HARQJ models. The results indicate that heterogeneous models have strong predictive power for Bitcoin price volatility, and incorporating jump factors into these models further improves their forecasting accuracy.
Abbas Khandan, Peyman Ghasri,
Volume 15, Issue 56 (8-2024)
Abstract
Sustainability of pension funds indicating the balance between contributions and pension expenses, is one of the fundamental principles governing social security systems. Among the things that affect the contributions and pension expenses of the Iran’s Social Security Organization (ISSO)’s fund is the minimum wage which according to Article 41 of Iran’s labor and social security laws, is determined annually by the Iran’s supreme labor council and, every year, becomes a controversial and disputed issue between labor :union:s, employers and the public authorities. An increase in minimum wage have effects on both the received contributions and pension expenses and, as a result, its final effect on the cash balance of ISSO’s fund has been arguable. Considering the issue importance, this paper studies the effect of an increase in minimum wage on ISSO’s contributions, pension expenses and its cash balance during 1961 to 2022 using an econometric time series model of autoregressive distributed lags (ARDL). The results show that a 10% increase in the minimum wage will increase ISSO’s contributions by 25.6% and its pension expenses by 23%. Therefore, comparing the effects, it can be stated that the ISSO’s cash balance would be increased by 2.6% as a results of a 10% increase in minimum wage. To test the result, one more time, the association between an increase in minimum wage and the ISSO’s excess resources was investigated separately. The results once again confirm that the ISSO cash balance would be improved by 3.3% in association with a 10% increase in minimum wage. In this study, it was also shown that the population of contributors, the population of pensioners, the population support ratio, GDP and dummy variables of sanction and Iran-Iraq war have been influential as well.
Mr Seyed Mojtaba Frozan, Dr Amir Gholami, Dr Seyed Mohammad Mehdi Ahmadi,
Volume 15, Issue 56 (8-2024)
Abstract
Creating the necessary conditions for growth and development is one of the goals of any economic system, which requires the application of correct economic policies, the identification and application of the components that affect growth, and as a result, the establishment of economic stability that leads to economic development and maintaining interests. It becomes national. Therefore, in order to achieve economic growth and to be on the path of economic development, it is necessary to consider the factors affecting economic growth. Among them, we can point out the control of inflation (growth of liquidity) and the reduction of income inequality. In this regard, examining the impact of monetary policies on these variables (stability, liquidity and inequality) can be effective and useful. Monetary policies are among the most important macroeconomic policies, which are among the main duties of central banks. Therefore, in this research, we investigate the influence of central bank independence on liquidity growth, unequal distribution of income and economic stability using time series data from 1981 to 2014. In the upcoming study, three sections were considered. The first part is the relationship between central bank independence and liquidity growth, the second part is the relationship between central bank independence and income distribution, and the third part is the relationship between central bank independence and economic stability. In each section, the influence of the economic indicators of the central bank's independence on the desired dependent variables was also examined. The calculated index for central bank independence in this study is a composite index. The results of the hypotheses test showed that the independence of the central bank has a positive and significant relationship with the growth of liquidity in Iran and a negative and significant relationship with the unequal distribution of income during the period under review and finally a positive and significant relationship with economic stability in Iran.
Dr Mahboobeh Khadem Nematollahi, Dr Teymour Mohammadi, Dr Abbas Shakeri, Dr Ali Asghar Salem,
Volume 15, Issue 57 (11-2024)
Abstract
The aim of this paper was to estimate the effects of unconventional monetary policy shocks using Narrative sign restrictions method as a novel method, imposing sign restriction on the impulse responses of real interest rate, GDP, GDP price deflator, nonborrowed reserves as well as Total Reserves in response to monetary policy shocks in Iran. Using Narrative sign restrictions model for the period 1983-2020 enables considering the effects of aforementioned five variables as well as identifying the effect of monetary policy shocks on these variables. Narrative sign restrictions constrain signs based on narrative information. According to the liquidity effect, results of the impulse responses function highlights decreasing real interest rate causes increasing in aggregate demand and GDP. With Narrative sign restrictions, real interest rate shocks also have significant impact on GDP through increasing it. To this aim, according to results and also with regard to the importance of unconventional monetary policy in response to crisis, this policy can be applied for resolving stagflation and this supplement policy can be applied besides other policies of Central Bank.
