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Editorial Board A Refereed Monthly International Journal of Management
Prof. B. P. Sharma
(Editor in Chief)
Prof. Mahima Birla
(Additional Editor in Chief)
Dr. Khushbu Agarwal
(Editor)
Ms. Asha Galundia
(Circulation Manager)

 Editorial Team

Dr. Devendra Shrimali
Dr. Dharmesh Motwani
 

Impact of Monetary and Financial Policy on the Volume of Trading in the Tehran Stock Exchange

Mahdi Yaghoubi

Department of accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

 

Alireza Moradi (Ph.D)*

Department of economics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

 

Babak Jamshidinavid (Ph.D)

Department of accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

 

Mehrdad Ghanbari (Ph.D)

Department of accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

.

*Corresponding Author: alirezamoradi_econ@iauksh.ac.ir

 

Abstract

Monetary and financial policies are one of the most important macroeconomic policies that affect stock market to large extent. The knowledge of how these policies influence is the important step in national and regional planning and development. The purpose of this research is analyzing the impact of the monetary and fiscal policies on Iran's capital market since 25 years. The data in this research is taken from the period ranging from year 1991 to year 2016.  The number of observations of this research was 100 observations. This research is analytical and quasi-experimental. The research design is descriptive and applied.  , in terms of purpose is applied, in terms of implementation logic is deductive, in terms of.  In this research, out of 360 models, 2 final models were extracted and analyzed. In analyzing the data to determine the effect of the independent variable on the dependent variable multiple Regression was used, as well as to compare the different governments the Wald test was used and to test the root of the Dickey Fuller test are used. The results of this study showed that the effect of the monetary and financial policies on volume of transactions in the capital market is significant.

 

Keywords: Monetary and Financial Policies, Volume of Transactions, Number of Transactions.

 

 

  1. Introduction

The capital market is considered to be the most efficient framework for investment and financing of firms and households in the national economy. From the perspective of economic development, the design of a leading economy requires efficient and successful market-makers. The capital market is a full-blown example of national economic events, and its cumulative movements are reflected in the published news or even confidential information that affects corporate fianancial reports (Zomorodian et al., 2015). The capital market is considered as one of the most important markets in the economy of each country due to the small funds allocated for implementation of major investment projects. Economists call the capital market as the engine of economic development that provides long-term financial resources. In the current situation and given the dynamics of the economy and the rapid development of world markets, the capital market of each country has been increasingly considered as a prerequisite for the use of all capacities and achieving full employment (Saleh Abadi, 2013). It is believed that prices in the capital market and also the index of the total stock market value are affected by some macroeconomic variables such as interest rate, currency, inflation and political events such as elections, especially government policy (Beishack et al., 2015; Zomorodian et al., 2015; Nunezhad et al., 2012; Moradi, 2013; Chatziantoniou et al., 2013). The study of the role and influence of monetary and financial policies of the government in the whole of Iran's economy is tangible and obvious to all. But in this article, the impact of these policies on Iran's capital market and the effects of macroeconomic variables on macroeconomic indicators will be examined.

 

 

 

  1. Problem Statement

Along with the basic assumptions of two asset pricing models and the arbitrage pricing model in determining the factors influencing the return on equity, governments as a major observer and policy-maker in key economic issues play a tangible role in the capital market, and one of the government's duties is to provide programs that can boost the capital market by influencing macroeconomic variables. The importance of stability in government policies (including monetary and fiscal policies) is twice important for developing countries, including Iran, because these countries have irregular financial markets and changes in government policies and macro economic variables is  rapid and, therefore, financial markets and especially the capital markets of these countries face many problems (Zomorodian et al., 2015).

Monetary policies are approved by the monetary authorities of the country (head of the central bank and the monetary and credit council). The purpose of implementing monetary policy is to regulate the economic situation in such a way that inflation and unemployment in society will be minimized. Monetary authorities use this device to control the amount of money, liquidity, and ultimately inflation. Implementing an expansionary monetary policy will increase liquidity, part of this liquidity will be absorbed into the stock market, and thus the stock market will be affected by the application of monetary policy (Nunezhad et al., 2012). There is also a positive correlation between the growth rate of liquidity (as a representative of monetary policy) and inflation with the return on stock market indices (Moradi, 2013). On the other hand, unanticipated changes in monetary policy reduce the stock price index to a greater extent than unanticipated changes in financial policy. Also, two variables of inflation and liquidity in the short and long term have a positive effect on the stock market (Zomorodian, 2015).

 

The increase in debt to banks by central bank and non state sector to bank leads to higher liquidity in the market. The increase of both variables is an expansionary monetary policy that increases the stock price index. If monetary policy is expansionary, it reduces the discount rate and, as a result, increases stock prices and future economic activities will increase, and vice versa (Ioannidis & Kontonikas, 2007). Presidential postgraduate courses in Iran after the 8-year Iran-Iraq war divided into four years of Construction (1989 to 1996), the Reform period (1997 to 2004), the period of Justice (2005 to 2012), and the period of government of Omid (2013 to 2017).

The present study seeks to investigate the impact of Monetary and Financial Policy on the Volume of Trading in the Tehran Stock Exchange between year 1991 to year 2016. The study intended to measure the degree of effectiveness and determine how much the monetary and financial policies and government income affect the capital market?

 

  1. Theoretical Concepts

Monetary policy: Monetary policy is a set of measures used by central banks (monetary policy officer) to control the economic activities of the community. Monetary policy will have an expansion if it leads to an increase in money supply, otherwise, it will be a contraction. Monetary policy is carried out through changes in the volume of money, changes in the growth of money and interest rates, or in terms of granting monetary facilities (Toothchian, 1996).

Financial policy: The financial policy is a kind of policy which is trying to achieve certain economic goals through instruments such as changes in government and tax expenditures. The purpose of financial policies in the advanced industrial countries and developing countries is somewhat different. In industrialized countries, the objectives are mainly to eliminate inflation, eliminate bottlenecks and achieve full employment, while for developing countries, the main goal of fiscal and financial policies is to increase economic growth and increase government revenues and total supply gives (Laopodis Nikiforos, 2009).

 

Liquidity by factors influencing its supply: Includes all the variables in the balance sheet of the banking system, each change in them has an effect on liquidity. (Taken from the Central Bank site)

Income distribution policy: In the economic culture, income distribution is referred to as the mechanisms by which national income is distributed among individuals and groups that are somehow involved in economic activities. In other words, income distribution describes how people share a community of national income and the degree of inequality between incomes of individuals in that society (Naziri et al., 2014).

 

Inflation: In economics, inflation means increase in general level of prices of most of the commodities over a given time period. The inflation rate is equal to the change in a price index, usually the consumer price index (Raei & Pouyanfar, 2008).

 

Volume of trading: The volume of trading is the volume of the money or a number of stocks that are traded within a period of time. In more complete terms, the volume of shares that changes over a specified period of ownership, and can also be defined as the number of buyers or the number of times in a given period (Laopodis Nikiforos, 2006). The number of shares exchanged during a period is called trading volume.

 

Number of transactions: Number of times a transaction is the number of times a company changes its ownership in each day (Nofrisati, 1999). In this research, we will review the number of the transaction quarterly.

 

  1. Literature Review

Ebrahimi and Farnaghi (2017) investigated the relationship between monetary and financial policies and stock market liquidity by using econometric models. For this purpose, using SVAR and Markov Switching Models and using Tehran Stock Exchange data in the period of 11997-2014, studied the factors affecting the liquidity of the stock market. Also, among the parallel markets, the growth rate of bank interest has the most negative effect on the liquidity of the stock market and the growth of the exchange rate does not have a significant effect on it. Also, the growth rate of housing prices has a weak negative effect on stock market liquidity.

Hosseinpour and Zara-Nezhad (2017) addressed the issue of extending the volume and size of government expensiture and its implications for macroeconomic variables. In their research, they argued that state intervention and the size of its activities play a decisive role in the state of the economy; hence, one of the main duties of the government is to create jobs for everyone in order to reach the level of complete employment.

Dehmardeh & Jafre (2016) examined the relationship between macroeconomic variables and volume of stock market trading, and the position of government size of the state among the D-8 countries of the Organization for Economic Co-operation and Development and its relation with the degree of openness commercially using panel data from 2000 to 2012. In this research, the trade intensity index was used as one of the subgroups of commercial openness. Co-integration test to ensure the long-term relationship between the variables has been estimated and the data are estimated based on the fixed effect model and the least squares weighting method.

 

Moradi & Najafizadeh (2013) studied the optimal monetary policy and stock market volatility. The results of their study indicated that the first attempt to reduce money supply would reduce the losses of the central bank. Second, the shock of the internal expectations explains the fluctuations of the stock market and a significant portion of the changes in real values, lead to a move between stock prices.  

Liya (2010), in an essay entitled "Bubbles and Credit Limitations," studied the bubble theory of stock price.  Firms face risky investment opportunities, in-house credit constraints, and limit debt obligations in such cases. The credit limit is derived from the incentive constraints in the optimal contracts, which ensures that firms do not default on the balance of debt repayments. In this study, stock price bubbles emerge through the mechanism of the loop of positive feedback. Stock market bubbles lead to more liquidity control and improve the efficiency of investment by reducing the incentive and then increasing the lending capacity.

 

Mousavi Jahromi and Rostami (2015) studied the effects of monetary policy impacts on the total stock price index in Tehran Stock Exchange. Their research was carried out by using econometric techniques using time series data from Iran during the period from 1991 to 2000. In order to investigate the effects of monetary policy impulses, in the first step, using the Hodic-Prescott filter, impulses are predicted and unpredictable impulses of monetary policy and positive and negative impacts of politics. Money split up.

 

Ebrahimi et al. (2014) investigated the effect of monetary and financial policies on stock returns, and in order to do this research, seasonal time series data were used and for testing and analyzing the results, various methods of econometric analysis of statistical models (VAR) and ( ARDL) and also as suitable software such as E-views and Microfit. The dependent variable of the research is the return on the stock market, which was used to measure the changes in the total stock price index in the stock market (TEPIX).

 

Akinkuotu, (2013) investigated the Nigerian capital market response to the shock of monetary and financial policies for the period 1981-2012. The results of this study show that there is a reverse relationship between government spending and stock market performance, but there is a direct relationship between liquidity expansion and stock market performance.

 

  1. Research Methodology

This research is analytical and quasi-experimental in nature. The nature of research design is descriptive and applied. The data used in the study is quantitative. Financial modeling has been applied on the data to extract results. The data from this research is taken in between year 1991 to 2016 on quarterly basis.  The number of observations of this research was 100 and economic data was collected using central bank reports and capital market data through the software of Rahavard Novin and the site of the Tehran Stock Exchange.  The variables of the research were tested using software E-views (version 9). In this study, numerical variables of monetary and financial policies became nominal according to the price index.

 

5.1 Research hypotheses

1) There is a phase wise (Four periods of Iranian Economic Development) significant difference in the impact of government’s monetary policy on the volume of transaction in Tehran stock market during selected period.  

2) There is a phase wise (Four periods of Iranian Economic Development) significant difference in the impact of the government's revenue policy on the volume of transaction in Tehran stock market during selected period.  .

3) There is a significant difference between the impacts of government financial policy on the volume of transaction in Tehran stock market during selected period.  .

4) There is a significant difference between the impact of government monetary policy on the volume of transaction in Tehran stock market during selected period.  .

5) There is a significant difference between the impact of the government's profit-making policy on the on the volume of transaction in Tehran stock market during selected period.  

6) There is a significant difference between the impact of government policy on the volume of transaction in Tehran stock market during different phases.  

 

5.2 Test hypotheses

The first, second, and third hypotheses of this study have been tested using the model presented in Table 3.

 

5.3 Estimated Model

Considering 180 variables and the implementation of optimal model in order to test the hypothesis and putting different variables at the end, the output model was extracted and the remaining variables were eliminated due to insignificant and non-optimal condition conditions. Table 3 is the result of modeling with research variables and among the 180 initial models of this model as the most optimal output model with all significant coefficients the final selection has been made.

 

Table-1 Results of the first and second hypotheses and other tests

Dependent Variable: number of transactions

Prob.

t-Statistic

Std. Error

Coefficient

Symbol

Variable

0.0186

-2.402730

20530173

-49328455

C

Constance government 4

0.0187

2.400419

20569598

49375657

D1

Constance government 1

0.0165

2.450094

20828625

51032078

D2

Constance government 2

0.0070

2.767473

20906887

57859245

D3

Constance government 3

0.0000

-6.790948

585.8939

-3978.775

EXPG

Expenditure government 4

0.0000

6.255845

644.5312

4032.087

EXPG*D1

Expenditure government 1

0.0000

5.952802

684.5657

4075.084

EXPG*D2

Expenditure government 2

0.0000

6.573655

596.2329

3919.429

EXPG*D3

Expenditure government 3

0.0000

6.128079

446.2846

2734.867

BD

Budget deficit government4

0.0031

-3.053528

875.4176

-2673.112

BD*D1

Budget deficit government1

0.0000

-5.121857

517.6867

-2651.517

BD*D2

Budget deficit government2

0.0000

-5.010919

480.8307

-2409.403

BD*D3

Budget deficit government3

0.0000

7.374017

49.16304

362.5291

M2

Liquidity government 4

0.0233

-2.312628

160.1513

-370.3704

M2*D1

Liquidity government 1

0.0000

-4.864685

66.36745

-322.8567

M2*D2

Liquidity government 2

0.0000

-6.202558

53.79032

-333.6376

M2*D3

Liquidity government 3

0.0165

2.448680

52069121

1.28E+08

g

Gini gover4

0.0165

-2.448859

52069187

-1.28E+08

g*D1

Gini gover1

0.0139

-2.514237

52841645

-1.33E+08

g*D2

Gini gover2

0.0062

-2.812879

52825456

-1.49E+08

g*D3

Gini gover3

0.960712

R-squared

28.52444

Akaike info criterion

0.951381

Adjusted R-squared

29.04547

Schwarz criterion

102.9611

F-statistic

28.73531

Hannan-Quinn criter.

0.000000

Prob(F-statistic)

2.157987

Durbin-Watson stat

Source: Results obtained using E-views software.

 

Table-2 Root test unit

RES_ATPX01 has a unit root

t-Statistic

Prob.

-4.300174

 0.0048

1% level

-4.056461

 

5% level

-3.457301

 

10% level

-3.154562

 

Variable

Coefficient

Std. Error

t-Statistic

Prob.

RES_ANT4(-1)

-0.833151

0.193748

-4.300174

0.0000

             

Source: Results obtained using E-views software.

 

Considering the significance level less than 0.05 and the amount of the statistical value is higher and it can be claimed that this model has no single root. So the null hypothesis is rejected.

These three hypotheses have been tested using least squares regression test. The results of the test of hypotheses in Table 1 show that the significance level of the F statistic is less than 5%, it can be said that the model for this hypothesis is significant at the 95% confidence level and according to the coefficient of determination, 0.951. Statistics are used to check the independence of the errors. If the value of test is between 1.5 and 2.5 in the Durbin-Watson test, the assumption of the correlation between the errors is rejected and regression can be used. The Durbin-Watson Amount is according to table 2.157987, which is within range.

Table-3 Wald test Income Total Government Costs in Different Governments

Test Statistic

Value

df

Probability

F-statistic

11.62963

(4, 80)

0.0000

Chi-square

46.51851

4

0.0000

Source: Results obtained using E-views software.

 

Table-4 Wald test of deficit during various government regimes

Test Statistic

Value

df

Probability

F-statistic

 10.24208

(4, 80)

 0.0000

Chi-square

 40.96831

 4

 0.0000

Source: Results obtained using E-views software.

 

Table-5 Wald test of the Volumes of Liquidity during various government regimes

Test Statistic

Value

df

Probability

F-statistic

 14.23069

(4, 80)

 0.0000

Chi-square

 56.92278

 4

 0.0000

Source: Results obtained using E-views software.

 

Table-6 Wald test of the Gini coefficient during various government regimes

Test Statistic

Value

df

Probability

F-statistic

 2.992442

(4, 80)

 0.0235

Chi-square

 11.96977

 4

 0.0176

Source: Results obtained using E-views software.

 

According to the results of Table 5, which indicates that the significance level of the F and K statistics is less than 5%, then the assumption of equality of government expenditures, budget deficit, liquidity and Gini coefficient, in different government tenure is rejected and shows that there is a significant difference in government spending in different governments.

H4: There is a significant difference in the impact of government monetary policy on the volume of transactions between the four periods of construction, reform, justice, and hope governance.

H5: There is a significant difference in the impact of the government's profit-making policy on the volume of transactions in the four periods of construction, reform, justice, and hope governance.

H6: There is a significant difference in the impact of government financial policy on volumes of transactions in the four periods of construction, reform, justice, and hope governance.

Considering the creation of 180 models and the implementation of these models in order to test the hypothesis and putting different variables at the end, the output model was extracted and the remaining models were eliminated due to insignificant and non-optimal condition conditions. Table 7 is the result of modeling with research variables and among the 180 initial models of this model, the optimal output model with all significant coefficients is the final choice.

 

Table-7 Test results of the fourth, fifth and sixth hypotheses

Dependent Variable: Volume of transactions

Prob.

t-Statistic

Std. Error

Coefficient

Symbol

Variable

0.1392

1.493129

2.12E+10

3.17E+10

C

Constance government 4

0.3791

-0.884359

3.49E+10

-3.08E+10

D1

Constance government 1

0.0001

4.189123

1.11E+10

4.63E+10

D2

Constance government 2

0.0022

-3.158497

2.34E+10

-7.38E+10

D3

Constance government 3

0.0000

12.89812

607113.3

7830622.

M2

Liquidity government 4

0.0048

-2.901202

2723071.

-7900180.

M2*D1

Liquidity government 1

0.0000

-9.530199

900772.3

-8584539.

M2*D2

Liquidity government 2

0.0000

-11.19099

644200.4

-7209242.

M2*D3

Liquidity government 3

0.0000

-5.535807

9752677.

-53988942

EXPG

Expenditure government 4

0.0000

7.585235

9200859.

69790680

EXPG*D1

Expenditure government 1

0.0000

9.241696

7779977.

71900185

EXPG*D2

Expenditure government 2

0.0000

9.500485

7060030.

67073712

EXPG*D3

Expenditure government 3

0.0000

-4.392522

1.21E+09

-5.29E+09

BR

Bank Rate government 4

0.0011

3.388727

1.55E+09

5.25E+09

BR*D1

Bank Rate government 1

0.0000

5.785876

1.40E+09

8.07E+09

BR*D3

Bank Rate government 3

0.0282

-2.234175

6898894.

-15413335

TOTR

Total Revenue government4

0.0163

2.453261

6974794.

17110991

BD

Budget deficit government4

0.915163

R-squared

47.21601

Akaike info criterion

0.898809

Adjusted R-squared

47.65889

Schwarz criterion

55.95939

F-statistic

47.39525

Hannan-Quinn criter.

0.000000

Prob(F-statistic)

1.574604

Durbin-Watson stat

Source: Results obtained using E-views software.

 

Table-8 The root test of the unit

RES_ATPX01 has a unit root

t-Statistic

Prob.

-8.727501

 0.0000

1% level

-3.591400

 

5% level

-3.039600

 

10% level

-2.749000

 

Variable

Coefficient

Std. Error

t-Statistic

Prob.

GLSRESID(-1)

-0.916419

0.105004

-8.727501

0.0000

             

Source: Results obtained using E-views software.

 

The fourth, fifth and sixth hypotheses have been tested using generalized least squares regression test. The results of Table 8 show that the significance level of the F statistic is less than 5%. It can be said that the model for this hypothesis is significant at the 95% confidence level and has a credit score of 0.89 according to the coefficient of determination of 0.89 Durbin-Watson statistics are used to check the independence of the errors. The Durbin-Watson Amount is in accordance with Table 1.57, which is within range. e has been used to resolve the self-correlation of a previous period.

 

Table-9 Wald test the Volumes of Liquidity in Different Governments

Test Statistic

Value

df

Probability

F-statistic

 44.09535

(4, 83)

 0.0000

Chi-square

 176.3814

 4

 0.0000

Source: Results obtained using E-views software.

 

Tables-10 Wald test the Government's Expenditures in Different Governments

Test Statistic

Value

df

Probability

F-statistic

 24.52095

(4, 83)

 0.0000

Chi-square

 98.08379

 4

 0.0000

Source: Results obtained using E-views software.

 

Table-11 Wald test Bank Profit in Different Governments

Test Statistic

Value

df

Probability

F-statistic

 11.64482

(3, 83)

 0.0000

Chi-square

 34.93445

 3

 0.0000

Source: Results obtained using E-views software.

 

According to the results of Table 10, which indicates that the level of significance of the F and K statistics is less than 5%, then the assumption of the equivalence of liquidity, government expenditure and bank profits during different government regimes is rejected and shows that the difference in the volume of liquidity during different phases.

 

  1. Conclusion and Recommendations

It can be seen that there is a significant difference in the impact of monetary, financial, bank profit and government income distribution on the number of transactions and volume of transactions in the capital market during the four periods of Reconstruction, reform, justice, and planning period in Iran. In other words, monetary, financial, bank profit and income distribution of different governments in the past 25 years have had a significant effect on the total index of the stock exchange. So it can be concluded that the policies of each government were having different results and influences on capital market.  The further researches can be carried on dimensions such as; Impact of Economic Growth in the last 25 years on Iran’s Capital Market and impact of crude oil price fluctuations and other factors such as Gold price on Iran’s capital market.

 

 

References

Akinkuotu, O.K. (2013). Comparative Impact of Fiscal and Monetary Shocks on Stock Market Performance in Nigeria, a post field report presented at the African Economic Research Consortium (AERC) bi-annual conference in Nairobi, Kenya.

Beishack, M.R. et al. (2015). "The Impact of Shocks on Monetary and Financial Policies on Iran's Stock Market", Economic Modeling Research, No. 22.

Chatziantoniou, I, Duffy, D. & Filis, G. (2013). Stock Market Response to Monetary and Fiscal Policy Shocks: Multi-country evidence. Economic Modelling, 30, 454–769.

Dehmarde, N. & Jefra, M. (2016). "A Comparative Study of Relationship between Government Size and Business Openness", Quarterly Journal of Economic Research (Sustainable Development and Development), Year 16, No. 4, pp. 105-85.

Ebrahimi, F., Nazari, M.K. & Jafari Saresht, D. (2014). "The Effect of Monetary and Financial Policies on the Return on Tehran Stock Exchange" Master's thesis, Bu-Ali Sina University, Faculty of Economics and Social Sciences.

Ebrahimi, S. & Farnaghi, E. (2017). "Factors Affecting Stock Equity with Emphasis on Monetary and Financial Policies" Quarterly Journal of Economic Research and Policy No. 7.

Hosseinpour, A. & Zara-Nezhad, M. (2017). "The Effect of Government Size on the Unemployment Rate in Iran," Quarterly Journal of Economic Research (Sustainable Growth and Development), Year 16, No. 1, pp. 191-209.

Ioannidis, C & Kontonikas, A. (2007). The Impact of Monetary Policy on Stock Prices. Journal of Policy Modelling, 30, 33 – 53.

Laopodis Nikiforos, T. (2009). Fiscal Policy and Stock Market Efficiency: Evidence for the United States. Quarterly Review of Economics and Finance, 49,633–650.

 Laopodis Nikiforos, T. (2006). Fiscal Policy, Monetary Policy, and the Stock Market. Thesis for Professor of Finance, Department of Finance School of Business, Fairfield University.

Liya, W. (2010). The Effect of Government Policy on China’s Stock Market Gutenberg AG, Feldkirchstrasse 13, FL - 9494 Schaan.

Moradi, A. (2013). "Application of E-views in Econometrics" Tehran, Iran.

Moradi, S & Najafizadeh, S.A. (2013). "The Effect of Monetary Policy on Stock Returns (Case Study: Iran)". The First National Conference on the Outlook of the Iranian Economy.

Musavi Jahromi & Rostami, N. (2015). "Investigating the Impact of Asymmetric Impact of Monetary Policy on Total Index Price Index in Tehran Stock Exchange", Journal of Financial Knowledge, Securities Analysis, Eighth, No.26.

Naziri, M.K., Ebrahimi, F. & Jafari Saresht, D. (2014). "The Effect of Monetary and Financial Policies on Tehran Stock Exchange Returns", Master's thesis, Bu-Ali University of Hamedan.

Nofrisati, M. (1999). The Root and Coexistence in Econometrics. Rasa Cultural Service Institute, First Printing, Tehran.

Nunezhad, M. et al. (2012). "The Effect of Income Distribution Policies on Stock Price Index in Iran" Journal of Economic Sciences, Sixth Year, Number Twenty.

Raei, R. & Pouyanfar, A. (2013). "Advanced Investment Management", Organization for the Study and Compilation of Humanities Books of Universities (SAMT), Tehran.

Saleh Abadi, A. (2013). "The Study of Capital Market Performance in Ninth and Tenth Governments", Financial and Economic Policies Quarterly, 2010, No. 2, pp. 203-216.

Toothchian, I. (1996). Money economy and banking. Tehran: Monetary and Bank Research Institute.

Zomorodian, G. (2015). "Investigating the Impact of Iran's Capital Market on Uncertainty in Income Distribution Policy and Income Distribution", Journal of Financial Engineering and Management of Securities. Number twenty fifth.

Zomorodian, G, Shabanzadeh, M. & Najafi Shariatzadeh, I. (2015). "Investigating the Effectiveness of Iran's Capital Market against Uncertainty in Monetary and Financial Policies", Journal of Financial Engineering and Management of Securities, No.25. Pages 81-106.

 

 
 

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