نقدینگی

Financial flexibility is defined as the capability to respond cost-effectively to changes in the business environment and to adapt to the impact of these changes on organizational goals. In the context of banks, financial flexibility refers to the ability to adjust policies and manage financial resources to maintain performance amidst economic shocks and environmental fluctuations. The primary aim of this research is to identify and rank the dimensions and components of financial flexibility in banks using the Analytic Hierarchy Process (AHP). This study is classified as applied-developmental in terms of its objective and descriptive-survey (Delphi) in terms of data collection methodology. An exploratory review of specialized literature was conducted, followed by the development of a questionnaire to collect insights from banking experts on financial flexibility in banks. The validity of the theoretical framework and the components of financial flexibility were scrutinized and evaluated. Through expert consensus and statistical tests, including mean, one-sample t-test, and Kendall's coefficient of concordance, nine components were identified: liquidity, capital adequacy, banking competitiveness, profitability, asset quality and financial structure, management stability and sustainability, sensitivity of operations to market risk, banking risks, and market size, along with 62 indicators for measuring these components. The AHP method was employed for ranking the components, and the results demonstrated that liquidity had the highest rank with a score of 0.252, whereas the sensitivity of operations to market risk had the lowest rank with a score of 0.041. Furthermore, the findings indicated that internal dimensions within banks play a more critical role in financial flexibility compared to external dimensions.

High and volatile inflation has had numerous adverse effects on the Iranian economy. Effective inflation-targeting policies require a thorough understanding of the key drivers of inflation. This study aims to identify the most important determinants of inflation in the Iranian economy from 2008 to 2022. In this study, tree-based ensemble methods, which are a class of intelligent machine-learning techniques, have been utilized. Furthermore, Shapley Additive Explanations (SHAP) are utilized to interpret model predictions and determine feature importance. Model performance is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE). Results indicate that Gradient Boosting (GB), Random Forest (RF), and Extreme Gradient Boosting (XGB) exhibit the lowest error rates across all three metrics. The findings reveal that broad money growth is the most significant determinant of inflation, contributing an average of 72% across all models. The exchange rate, while a contributing factor, plays a less substantial role compared to broad money, accounting for approximately 17% of the inflationary pressures.

High and volatile inflation rates constitute a significant economic challenge for Iran, particularly in recent years. Diverse perspectives exist among experts regarding the underlying factors and appropriate solutions. This paper presents a unified framework for understanding the causes of inflation in the Iranian economy and outlines corresponding policy recommendations. This framework categorizes inflationary drivers into two distinct groups: long-term and short-term factors. The primary long-term driver, contributing to Iran's persistently higher inflation compared to other nations, is identified as excessive liquidity growth exceeding production growth. This assertion is supported by empirical evidence. Notably, liquidity growth itself is an endogenous outcome of income-expenditure imbalances within the Iranian economy. This disparity manifests as insufficient expenditure growth relative to national income growth at the macroeconomic level. Conversely, short-term inflation fluctuations (around the long-term trend) are primarily influenced by the anchor of inflation expectations (the unofficial exchange rate in the Iranian economy) and the monetary policymaker's response to these fluctuations. Consequently, short-term policy interventions should prioritize minimizing exchange rate volatility around the long-term real exchange rate trend, implementing robust rial governance, and strengthening the central bank's monetary policy framework. Long-term effectiveness necessitates measures such as controlling both the quantity and quality of liquidity, reforming the banking system and addressing unsound banking practices, restructuring the budget to improve the operational balance, reducing excess liquidity, and redefining the nominal anchor.

In recent years, one of the challenges facing governments has always been the issue of financing the budget deficit. Since 1395, the sale of bonds has started to compensate for the budget deficit and these government bonds have also been sold to banks. The purpose of this study is to investigate the effect of selling government bonds to compensate the budget deficit on liquidity The data used in this research is seasonal and for the period 1372:Q2-1400:Q1 and the estimations were done using the system of simultaneous equations and in the framework of recursive models and by the ordinary least squares method .The results indicate that, According to the first equation, the sale of bonds to banks has a positive relationship with the government's debt to banks, in fact, the sale of bonds to banks has increased the government's debt to banks. In the second equation, it was found that the government's debt to the banks has a positive relationship with the banks' debt to the central bank, Therefore, it can be said that the sale of bonds to banks has increased the debt of banks to the central bank. Also based on liquidity equation, The positive relationship between government debt to banks and liquidity and the positive relationship between bank debt to the central bank and liquidity has been proven, Therefore, it can be said that the sale of bonds to banks has led to an increase in liquidity.Keywords: deficit financing, sale of bonds to the bank, liquidity, System of simultaneous equations and Recursive Models .

Cash management is simply defined as making the right amount of money available at the right time and the right place to meet the government's obligations in the most cost-effective way. The main features of modern cash management are centralized government bank accounts and the establishment of a Treasury Single Account. A TSA is a unified structure of government bank accounts that gives a consolidated view of government cash resources. The main issues facing this study are where the best place is to keep the main account of the Treasury Single Account and what the best structure of this account is. In this article, by examining the experiences of more than fifty selected countries, the structure and location of the TSA were examined. Empirical evidence indicates that the TSA systems established in most countries fall somewhere in between centralized and decentralized models. Based on the findings of the study, it was concluded that TSAs main account in most countries under review is in the central bank. In Iran, the structure of this account is of a hybrid type with an approach that tends to be centralized and its location is in the central bank.

Liquidity is considered one of the important assets of economic units and enterprises, which plays a significant role in financial decisions. Organizations usually face imbalances in assets and liabilities that must be balanced. If an organization is not successful in balancing such a gap, there will be a liquidity risk and several adverse consequences such as the risk of inability to pay debts, the risk of reputation and credit, etc. will occur. Liquidity management includes preventing the inability to pay debts (bankruptcy), reducing the period of accounts receivable, increasing the amount of collections, and such cases. Investors, lenders and managers pay special attention to the financial statements of companies so that they can evaluate liquidity risk by using liquidity ratios, which is liquidity management.On the other hand, working capital management is a liquidity management tool and one of the strategies for achieving desirable liquidity for companies, so that desirable liquidity for companies is maintained to the extent that they are not exposed to surplus or shortage of liquidity. In addition, economic sanctions increase inflation and disrupt money transfers and liquidity management. Accordingly, the purpose of this study is to investigate the impact of economic sanctions on liquidity management (based on operating capital factor), in listed companies in Tehran Stock Exchange. To test the research hypotheses, the financial information of the 126 companies (1260 years-companies) accepted in Tehran Stock Exchange was used between 2011 and 2020, given the tightening of sanctions in 2011. The necessary data were extracted by referring to the financial statements and accompanying explanatory notes in the companies admitted to the Tehran Stock Exchange, available in the Codal, the website of the Tehran Stock Exchange Organization, and Rahvard Novin software. The final analysis of the collected data was done using Eviews and Stata econometric software. After measuring the variables of the research, multivariate linear regression analysis was used to test the research hypothesis. The experience of recent years shows that Iran has always struggled with the issue of economic sanctions. In terms of time, sanctions on Iran after the Islamic Revolution can be divided as follows: the initial period of the Islamic Revolution and hostage-taking (1979-1981); the period of Iraq's imposed war against Iran (1981-1988); Reconstruction period (1989-1992); Clinton era, bilateral restraint (1993-2001); After September 11, 2001 and after the resolutions of the Security Council. In the period from 2011 to 2014, the international sanctions against Iran caused a decrease of more than 17% in the real GDP of the country. In the period between 2012 and 2015, the most severe banking sanctions, including those of the United States, the United Nations, and the European Union, were imposed on Iranian banks and their SWIFT system was shut down. For this reason, studies investigating Iran's sanctions usually choose this period as the period of economic sanctions; Because it was unique in terms of intensity and depth and significantly overshadowed the economic and business indicators of the companies. The severity of the effects and consequences of the recent sanctions make it relevant to examine its impact on variables such as the company's liquidity.The results of the statistical tests indicate that economic sanctions have a negative impact on the liquidity management of the company by imposing restrictions on the purchase, sale, GDP, technology and contraction of economic activities (inactivity in the economy). In an alternative practice, the research model was also fitted with clustered standard error (cluster panel). The results of the model estimation with the panel cluster method (sensitivity test) support the main results of the research and state that sanctions have a negative effect on the company's liquidity management. Economic sanctions cause disruption in growth, financial flexibility, efficiency of economic activities, employment, profitability and consequently liquidity management by creating an unhealthy environment in the business environment and restrictions on doing business. Hence, companies perform worse in times of economic sanctions. Based on the results of the research and considering the negative effect of economic sanctions on liquidity management in companies, it is suggested that the statesmen and other authorities of the country pay more attention to the general policies of the economy in order to strengthen the economy of Iran. Regarding the impact of sanctions on liquidity management, there are two solutions to deal with it: a) Coordination of political and economic officials in the path of not sanctioning the country, which is of course bound to preserve the values of the society. b) The existence of alternative markets with which it is possible to exchange in the conditions of sanctions and the strengthening of any type of regional union and alternative market. The limitation of the current research is that the variable that is considered to measure sanctions is a virtual variable that depends on time and is defined in a period of time, and in this period, it cannot be confidently claimed that it is the only event that affects the macro economy of Iran. is sanctioned; Rather, other events, such as the deterioration of the balance sheets of banks and energy price reforms (implemented in 2010), etc., which have occurred in this period of time, can also affect the generalization of the results.

This paper seeks to explore the nonlinear association between liquidity indicators and debt repayment capacity in relation to asset returns. For this purpose, the Panel Smooth Transition Regression (PSTR) method was employed to examine the nonlinear impact of liquidity indicators (including the ratios of current assets to total deposits, total loans granted to total deposits, and total loans granted to total assets and debt payment capacity indicators (such as the debt ratio and interest coverage ratio) on asset returns from 2011 to 2020. The findings revealed a nonlinear effect of all calculated indicators on asset returns. The magnitude and manner of the independent variables' influence on asset returns varied at different levels, with noticeable distinctions in the effect before and after the threshold value of 1.0586. In light of these results, bank policymakers can strategically select an optimal liquidity level to enhance bank profitability based on asset returns.

The present study aimed to examine the transfer, reception, and the spillover of volatility from March 1982 to September 2022, using the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency. The results indicated that the primary relationship among the volatility of the analyzed variables is of long-term nature, with the exchange rate emerging as the dominant factor in explaining the volatility of the examined network. In the short term, liquidity serves as the primary transmitter of volatility to inflation and the exchange rate. However, in the medium and long term, the exchange rate becomes the primary transmitter of volatility to inflation, while liquidity acts as the net receiver of currency volatility. Additionally, the long-term impact of the exchange rate is more pronounced. Failure to control currency volatility can lead to inflation turbulence by transferring volatility to liquidity, underscoring the significance of exchange rate stability in managing liquidity and inflation.

One of the primary goals of economic policy is to achieve full employment. The economic policy affects employment through monetary and fiscal policies. Considering this effect, this study aims to investigate the asymmetric dynamic effect of liquidity growth on the unemployment rate by nonlinear autoregressive distributed lag (NRDL) approach in Iran in the period between 2005:4 to 2022:4. The results indicate the existence of asymmetry in the short term. Accordingly, a one percent positive change in liquidity growth leads to an increase in the unemployment rate by 0.21 percent, and a one percent negative change in liquidity growth leads to a decrease in the unemployment rate by 0.25. Although the effect of liquidity changes on the unemployment rate is almost low, the asymmetric effects of monetary policy that are applied by liquidity changes are evident

The purpose of this paper is to investigate the impact of banks' liquidity shock on their excess reserves and the business cycles in Iran's economy. In order to benefit from the functional tasks of the banking system in the real sector of the economy, it is necessary to control the liquidity in the hands of the bank. The liquidity management by the bank includes predicting liquidity needs and providing them at the lowest possible cost. The main reason for the liquidity risk is that most bank resources are provided from short-term deposits, while the bank facilities are used to invest in assets that have a relatively low degree of liquidity. Therefore, a main task of the bank should be creating a balance between short-term financial obligations and long-term investments. Maintaining insufficient amounts of liquidity exposes the bank to the risk of not being able to fulfill its obligations and pushes it toward bankruptcy. Also, maintaining large amounts of liquidity causes inefficient allocation of resources, reduction of the interest rate on deposits and, as a result, losing the market.

In order to analyze the results, the dynamic stochastic general equilibrium method was used in terms of the structure of the banking system in the period of 1989-2020 based on the frequency of the seasonal data. In the statistical analysis section, the impacts of the impulse from liquidity on the surplus bank reserves, business cycles, and a set of banking and macroeconomic variables were compared and evaluated. The current research model has five parts including household sectors, producers of intermediate goods and final goods, banking sector, government and central bank. The household sector maximizes the expected discounted utility function with respect to the inter-period budget constraint. Intermediary companies seek to minimize the production cost function, and the company producing the final product deals with pricing based on Rotenberg's price stickiness theory. In order to maximize the expected profit function, the banking sector makes its decisions to determine the optimal interest rates of deposits and facilities for both households and companies. It should be mentioned that regarding bank rates for deposits and facilities, although the range of interest rates for deposits and facilities is communicated to the banks, the banks act based on other variables. They have the option to consider the maximum expected profit function based on their requirements, such as the amount of the fixed balance in the customer's account of facility reception or the interest paid to depositors. Finally, the government and the central bank are face with an inter-period budget constraint.

Based on the obtained results, the momentum of liquidity induced by the banking system has led to an increase in their surplus reserves and the occurrence of business cycles and deviations in production. Also, the liquidity shock has led to an increase in the inflation rate and exchange rate in the economy. It is recommended to eliminate the effect of liquidity shocks of the banking system on the economy by using precautionary and unconventional policies. In order to improve the relationship between the Central Bank and the banks, managing the overdrafts of the banks from the Central Bank by guaranteeing the overdrafts and regular financing is an important and fundamental task in the agenda of the Central Bank. The intelligent monitoring of the facilities and transactions in the banking network by the Central Bank can correct the asset and capital structure of banks, improve the risk management system, transparency of financial reporting in banks, organize the non-banking activities of banks and their subsidiaries, and prevent the entry of resources into speculative activities. Also, selling the surplus assets of banks is considered as an important act to reform the functioning of the banking system.

The liquidity shock from the banking system has led to an increase in their excess reserves, the emergence of business cycles and fluctuations in production, and increased inflation rate and exchange rate in the economy. Based on the results, it is recommended to prevent liquidity shocks from the banking system by using conservative and unconventional policies. Since an important part of creating liquidity in the country's economy has been done by banks in the past years, controlling the creation of money and liquidity by banks can play an important role in reducing the growth of liquidity and inflation. Therefore, there is a need for structural reforms and the supervision of the banking system. According to the proposed economic theories and the results obtained from this study, if a change is made in the credit risk, liquidity of commercial banks in money creation, and therefore the profit margin of the banks, monetary policy may be able to directly influence the interest rate in the credit market. In this case, an asymmetry may arise. An increase in the policy-based interest rate always leads to an increase in the interest rate in the credit market because commercial banks have to compensate the costs of re-borrowing and have to earn at least a profit. But if the liquidity risk and credit risk of commercial banks increase due to increased uncertainty, or if the level of banks' requested interest increases, a reduction in the base rate may not be immediately accompanied by a reduction in the credit market rate.

The purpose of this study is to estimate the cryptocurrency tail risk and its effects on macroeconomic variables, especially real exchange rates and liquidity growth in Iran have been evaluated. For this purpose, statistical information for the period 2010-2020 based on the frequency of monthly data has been used. The approach used in this paper was the vector autoregression method with time-varying parameters (TVP-VAR). In the first part, the risk tail index was extracted using the threshold value for cryptocurrencies (bitcoins). Comparing the results of the VAR and TVP-VAR models, it can be seen that the shock from the Bitcoin virtual currency area has led to an initial decline in liquidity growth and exchange rates. However, after 2 periods, the effect of this shock reached its highest value and led to an increase in the growth of liquidity and the exchange rate, and the effect of this shock disappeared in the long run and converged towards the equilibrium value. The results obtained from the shock from the virtual currency area in the VAR model show that the variables of liquidity growth and exchange rate in all three cases have shown a positive reaction to this shock and the effect of this shock has disappeared in the long run.

In recent years, due to the existence of severe sanctions and obstacles governing the sale of oil, it has led to an increase in the exchange rate, and on the other hand, the decrease in foreign exchange resources has led to a decrease in the government's income, and the limitation of the income caused by the financial policies of the government is sufficient to cover the expenses of the government. does not give and as a result the budget deficit has caused many problems in the government's economic system. So far, no comprehensive research has been done in the field of developing the optimal model of monetary policies for liquidity and income distribution. Thus, in this article, we try to investigate the effects of optimal monetary policy on these variables and close the existing research gap. Based on this, the main goal of this research is to investigate the effect of optimal monetary policy on liquidity and inequality of income distribution.

The current research method is practical. The period of the current research was 1357 to 1398. To estimate the model, the self-regression econometric model with distributed interruptions or ARDL was used in Microfit 5 software space.

Optimal monetary policies have a positive and significant effect on the adjustment of liquidity volume. Optimal monetary policies have a positive and significant effect on income equality.

Based on the results of the model, the liquidity situation and income inequality have worsened during the period under review, as a result, the monetary policy in the country did not have the necessary efficiency.

In developing countries, the shocks that enter the economy due to capital market fluctuations have more depth and durability. Because of the two-way connection between the stock market and the real sector of the economy and public attention to this market, examining the stock market shocks is of great importance. Therefore, the present study investigated the extreme fluctuations of the stock market index, which suspected the existence of bubbles. Timing of these bubbles in the market is one of the goals of this study, which was carried out by using the right-tailed unit root tests based on the augmented Dickey-Fuller test. A stock price bubble may be affected by monetary policy. This issue is influenced by the size of the bubble and the type and strength of the applied monetary policy. The impact of monetary policy fluctuations and especially interest rates on stock price bubbles is theoretically uncertain and should be determined empirically. Therefore, another goal of this study is to examine the effects of monetary policy shocks on the formation and timing of the stock market bubble.

The method of Phillips et al.  (2015) has been used to identify and time the stock market bubble. Galli and Gambeti model and TVP-SVAR method were also used to investigate the effect of monetary policy on the stock market bubble.

BSADF (Backward Supreme Augmented Dicky-Fuller) test has been used to determine the dates when the stock market had a bubble. According to this test, in three short periods, from July to September 2005, from April to May 2011, and from October to November 2018, the stock market behaved like a bubble. Regarding the impact of the interest rate shock on the stock market bubble, it can be said that the monetary expansion shock (decrease in the real interest rate) causes the bubble part of the stock price to become larger. In all periods, the response of the bubble part was positive, but over time, has increased, and since the beginning of the 2010s, its response to the shock of interest rate reduction has completely changed. The liquidity shock, also strengthens the size of the bubble. The amount of this influence has also increased greatly over time and has reached its peak in 2017 (the year of the formation of the price bubble in the stock market based on the BSADF test). Therefore, it can be claimed that the increase in the bubble part of the stock price was caused by a positive shock or an increase in liquidity. Regarding the effect of the credit shock on the stock market bubble, it can be said that credits has affected the fundamental part of the stock price, but it does not have much effect on the bubble part of the stock price. In fact, the increase in credits has caused the liquidity restrictions of economic enterprises to be removed and has an effect on their production and sales and finally on their profitability. Therefore, it is expected that with an increase in credits (positive credit shock), most of the fundamental part (current and future profitability) of companies will be affected.

During the last decade, the public attention to the stock market in Iran increased significantly. This issue caused the entry of new funds into this market, which was seen in the bubble-like behavior of the stock price index. In the conventional economic theory, the positive impact of expansionary monetary policies on the bubble is expected, but there are other theories that make the long-term impact of the monetary policy shock on the size of the bubble uncertain and dependent on factors such as the size of the bubble, the stability of the monetary policy, and the type of monetary tool. In order to solve this theoretical ambiguity, the effect of one of these cases, i.e., changing the monetary policy tool, on the stock price bubble was investigated. Before that, the existence of a bubble in the stock market had been checked. Regarding the impact of monetary shocks on the stock price bubble, according to the type of monetary policy instrument, the reaction of the stock price bubble has been different. Interest rate policy and liquidity have had a positive effect on the bubble, but credit policy has not had such an effect. In most of the developed economies, the interest rate change is the most powerful monetary policy tool, as a small change in it can have a large impact on the real sector of these economies. But in our country, according to the empirical findings of this article, the effect of liquidity on the stock market bubbles has been greater than the effect of changing the interest rates on it. This result is a proof of the dominance of liquidity over monetary policies in Iran.

In recent decades, the role of the capital market and the expansion of financial markets had a relatively high relationship with the economic growth of countries. Countries such as America, Japan, England, South Korea, Singapore and other developed countries have made great use of these financial markets and especially the stock exchange for economic development and growth. In this research, by conducting the ARDL test in the period of 1991-2020, we investigated the long-term and short-term relationships between the variables, with a one percent change in the variables of liquidity and consumer price index, respectively, 26. 4.0.34% will be added to the stock price index of Tehran Stock Exchange. the coefficients of all variables can be interpreted at a significant level of 5%. with a one percent change in the variables of liquidity volume and consumer price index, 1.46, 0.52 percent will be added to the stock price index of Tehran Stock Exchange, respectively. Meanwhile, with a one percent change in monetary base variables and financial development, the stock price index of Tehran Stock Exchange will decrease by 0.86% and 0.67%, respectively. it can be said that with increasing liquidity and after that, the price level increases, the value of assets and production inputs of companies and economic institutions increases. If the price increase of listed companies' products is more than the growth of production costs, the profits of companies will increase and inflation from the future cash flow channel of earnings can have a positive effect on stock prices.

One of the most important concerns of policymakers is achieving high economic growth. Accordingly, in the present study, the effect of oil revenues, human capital, liquidity and investment on economic growth in the period of 1991-2021has been investigated in the form of space-state model. The results of the research showed that the impact of oil revenues, investment and human capital on economic growth was positive and decreased over time. Also, liquidity has a uniform negative effect on economic growth. Therefore, improving the performance of the National Development Fund can provide the basis for a greater positive impact of oil revenues on economic growth. Also, if macroeconomic stability is not established, the increase in liquidity will lead to the transfer of money to non-productive activities and subsequently to the reduction of economic growth. On the other hand, in the conditions of macroeconomic instability, it will not be possible to increase the formation of fixed capital, and in this way, the improvement of economic growth will be limited.

The government's debt to commercial banks can have an effect on the monetary base and liquidity through the effect on the balance sheet of commercial banks and through the balance sheet of the central bank. In Iran's economy, despite the growth of 32.6 and 19.9 percent of public sector debt to commercial banks in 2017 and 2018, which was accompanied by 22.1 and 23.1 percent growth of liquidity, it is formed by examining the components of this hypothesis that the components Government debt to commercial banks can affect liquidity and its components. The data used in this study include the monetary base, liquidity, money, quasi-money, economic growth rate, inflation rate, government debt to commercial banks and government companies and institutions debt to commercial banks, which are from the official statistics of the Central Bank of Iran for the period They were taken in 1998-2020. In this research, it has been tried to investigate and evaluate the effects of government debt to commercial banks on the components of Iran's liquidity by using the method of non-linear regression model with distribution breaks (NARDL). The results show that the shocks of the government's debt to commercial banks in the long and short term have a symmetrical effect on the basis of money, money, liquidity and quasi-money; In addition, the shocks of the government and government institutions' debt to commercial banks also have an asymmetric effect on the dependent variables.

Real Money Balance indicates the impact of the changes in real money stock on real variables of the economy. This paper estimates the real money balance effects on private consumption and aggregate demand by using a structural estimation approach. The data that we use is Iran’s annual data and runs from 1990 through 2019. The variables are real private consumption expenditures, M2 money stock, CPI, GDP, population, central bank’s one-year interest rate, the arithmetic mean of growth rates of the price of durable commodities, the exchange rate, the price of gold, and the price of one square meter of land. The estimation shows that the parameter that indicates the importance of the real money balance effect on private consumption is significantly different from zero (0.952 and 0.814 from two different normalization estimations). In addition, the amount of real money balance effect on aggregate demand equals 1.691 which is significantly different from zero. These results indicate the importance of real money balance effects on private consumption and aggregate demand in Iran’s economy. This means that real money influences all macroeconomic variables and has an important role in monetary transaction mechanisms. This result indicates the importance of monetary policy and shows why we cannot ignore money’s role in the monetary transaction mechanism. It also illustrates the negative impacts of price rise in real variables on economics by decreasing real money balance.