Monetary & Financial Economics

Original Article Exchange

The Mediating Effect of Overconfidence of managers on the Relationship between Attribution Bias and Performance of Companies Listed in Tehran Stock Exchange

Amin Nazemi; Shahrokh Sheidaee

Volume 30, Issue 26 , July 2023

https://doi.org/10.22067/mfe.2023.82897.1308

Abstract

The aim of the study is to investigate the mediating effect of overconfidence of managers in the relationship between documentary bias and the performance of companies listed on the Tehran Stock Exchange. The current research is applied and from the methodological point of view, the correlation is causal ... Read More

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The Critically Evaluation of the Baumol – Tobin Inventory Theory of Money Demand

Mostafa Karimzadeh

Volume 23, Issue 12 , February 2017, , Pages 217-234

https://doi.org/10.22067/pm.v23i12.45376

Abstract

Money is the one of the most important human innovations that has essential role in facilitating of transactions and economic evolution. Which added its performance with development and complicated of societies. The money market has like all other markets, both a demand side and a supply side. In this ... Read More Money is the one of the most important human innovations that has essential role in facilitating of transactions and economic evolution. Which added its performance with development and complicated of societies. The money market has like all other markets, both a demand side and a supply side. In this paper we examine the demand side. Since the 1930s, economists have developed the theory underlying the demand for money along several different lines, each of which provides a different answer to the basic question: If bonds earn interest and money doesn’t, why should a person hold money? While the way the various theories this question differs, in general they come down to a demand for money function. The cognition of effective factors on money demand is one of the most important economic topics. To answer this problem, some of the economists try to present several money demand theories. In this paper we will evaluate the inventory approach to transaction demand developed by both Baumol and Tobin. They show that there is a transactions need for money to smooth out the difference between income and expenditure streams and the higher the interest rate – the return on holding bonds instead of money – the smaller these transactions demand balances should be. Theoretical Framework Keynes had designated the transactions demand for money as due to the transactions motive but had not provided a theory for its determination. In particular, he had assumed that this demand depended linearly on current income but did not depend on interest rates. Subsequent contributions by Baumol and Tobin in the 1950s established the theory of the transactions demand for money. These contributions showed that this demand depends not only on income but also on the interest rate on bonds. Further, there are economies of scale in money holdings. The transactions demand for money is derived under the assumption of certainty of the yields on bonds, as well as of the amounts and time patterns of income and expenditures. Baumol (1952) and Tobin (1956) presented their money demand theory by using inventory approach. Developments since the 1950s have extended and broadened the Baumol–Tobin transactions demand analysis, without rejecting it. The most significant extension of this analysis has been to the case where there is uncertainty in the timings of the receipts and payments. The demand for money under this type of uncertainty is usually labeled as the precautionary demand for money. This section presents Baumol’s (1952) version of the inventory analysis of the transactions demand for money. This analysis considers the choice between two assets, “money” and “bonds,” whose discriminating characteristic is that money serves as the medium for payments in the purchase of commodities whereas bonds do not; hence, commodities trade against money, not against bonds. There is no uncertainty in the model, so the yield on bonds is known with certainty. The real-world counterpart of such bonds is interest-paying savings deposits or such riskless short-term financial assets as Treasury bills. Longer-term bonds whose yield is uncertain are not really considered in Baumol’s analysis. Baumol’s other assumptions are: 1. Money holdings do not pay interest. Bond holdings do so at the nominal rate R. There are no own-service costs of holding money or bonds, but there are transfer costs from one to the other, as outlined later. Bonds can be savings deposits or other financial assets. 2. There is no uncertainty even in the timing or amount of the individual’s receipts and expenditures. 3. The individual intends to finance an amount $Y of expenditures, which occur in a steady stream through the given period, and already possesses the funds to meet these expenditures. Since money is the medium of payments in the model, all payments are made in money. 4. The individual intends to cash bonds in lots of $W spaced evenly through the period. For every withdrawal, he incurs a “brokerage (bonds–money transfer) cost” that has two components: a fixed cost of $B0 and a variable cost of B1 per dollar withdrawn. Examples of such brokerage costs are broker’s commission, banking charges and own (or personal) costs in terms of time and convenience for withdrawals from bonds. The overall cost per withdrawal of $W is $(B0 +B1W). They explained that individuals have two cost about money demand: the cost of interest rate of money (first cost) and the cost of refer to bank (second cost). The most important contribution of their theory is that interest rate influences transactions demand of money. Results & Discussion Our paper lead to this occlusion that development of electronic money and banking, causes the Baumol – Tobin theory faces essential critical and challenges. In recent age with development of electronic money and banking, the cost of refer to the bank is very low. Conclusion & Suggestion Hence we can assume that this cost is zero. By assumption that the cost of refer to the bank is zero, the inventory theory isn’t appropriate approach to money demand.

Development of Earning Manipulation Prediction Model Applying Hybrid Neural Network and Cosmology Based Algorithms

Nahid Maleki Nia; reza tehrani; Akbar Tabriz Akbar; Mirfeiz Fallah shams

Volume 28, Issue 21 , November 2021, , Pages 57-86

https://doi.org/10.22067/mfe.2021.71593.1099

Abstract

Extended abstract1- INTRODUCTIONAccurately predicting earning manipulation in order to detect and identify manipulation of financial statements has always been one of the most fundamental challenges ahead of financial reports users. Because of increasing financial reporting fraud, this fact resulted ... Read More Extended abstract1- INTRODUCTIONAccurately predicting earning manipulation in order to detect and identify manipulation of financial statements has always been one of the most fundamental challenges ahead of financial reports users. Because of increasing financial reporting fraud, this fact resulted in investor distrust of capital markets in recent years. The purpose of this study is to answer the questions whether it is possible to detect earning manipulation in financial statements based on the Beneish model? is it possible to detect earning manipulation in financial statements based on the proposed model? and does the proposed model predict better than the Beneish model in detecting earning manipulation? The findings of this research can be concidered by investors, creditors, auditors, regulators and other users to help them in making decisions and offering appropriate solutions. In order to detect earning manipulation and enhance the predictive accuracy of the earning manipulation model, it has been designed and presented a developed model based on Beneish model (1999). this study uses corporate governance variables i.e., audit committee structure, legal inspector and independent auditor, board of director's structure and corporate ownership structure requirements.2- THEORETICAL FRAMEWORK Benish (1999) investigated 74 earning-manipulator companies applying probit analysis during 1982-1992. He assigned the number 1 to the manipulative companies and the number zero to the non-manipulative companies and calculated the coefficients of the independent variables. The cut-off point of this model was -1.78. Therefore, if the M-score is greater than -1.78, it is likely that the company is earning manipulator. The overall accuracy of the model was confirmed at 76%.By using eight accounting variables in its model, Beneish showed that the probability of earning manipulation increases with unusual increase in receivables, decrease in gross profit margin, decrease in asset quality, sales growth and increase in accruals. But what is hidden from view in this model, is the attention to the control of mechanism to reduce transaction and agency costs. Studies conducted to develop the Beneish model have also been based solely on accounting data and have ignored the implications of control mechanisms in model development. Therefore, in order to improve the predictive power of the beneish model, corporate governance system can be considered as a deterrent factor from earning manipulation.3- METHODOLOGY The data of this study are drawn from the annual financial statements and reports of a sample of 81 non-financial listed companies on TSE over the period 2012-2018 i.e., 567 firm-year observations and analyzed by the hybrid multi-layer perceptron (MLP) neural network and cosmology based algorithms i.e., black-hole based optimization (BHBO), big bang-big crunch (BBBC) and galactic swarm optimization (GSO). It has been applied feed forward net to design the initial and final neural network model by structure of 8-17-1-1 for Beneish model (1999) and of 25-17-1-1 for the proposed model.This study also compares models based on hybrid neural networks and cosmological algorithms and the best and weakest cosmological algorithms are determined in neural network training to detect earning manipulation.4- RESULTS & DISCUSSIONThe numerical value of the area under the curve (AUC) of the receiver operating characteristic gives an idea about the detection power which it has been in the rejected range of 0.74 to 0.55 for the Beneish model (1999) and in the accepted range of 0.97 to 0.75 for the proposed model. The best cut-off points and the best accuracy of the Beneish model (1999) have been estimated up to 0.4014, 63.49%, respectively, by the hybrid multi-layer perceptron neural network and big bang-big crunch algorithm (MLP-BBBC). The best cut-off point and the best accuracy of the proposed model have been estimated up to 0.4023 and 87.30 percent, respectively, by the hybrid multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO). The estimated accuracy of the model by the hybrid methods of multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO), hybrid multi-layer perceptron neural network and big bang-big crunch algorithm (MLP-BBBC) and hybrid multi-layer perceptron neural network and black-hole based optimization algorithm (MLP-BHBO) has been increased from 59.08, 63.49 and 57.5 percentages to 87.3, 79.72 and 74.25 percentages, respectively.5- CONCLUSIONS & SUGGESTIONSThis evidence indicates that predictive power of the model has been enhanced in detecting earning-manipulator companies and training error of the network has been decreased up to 12.7 percentages by hybrid method of multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO). Therefore, it can be concluded that the integration of corporate governance variables as non-accounting variables to the Beneish model (1999) has been more effective in detecting and identifying earning manipulation. This evidence is consistent with this fact that a significant reduction in mean square error (MSE) is up to 23.81% and as a result the predictive power of proposed model has been significantly improved. The area under the curve of the black-hole based optimization (BHBO) and big bang-big crunch (BBBC) algorithms is covered by the galactic swarm optimization (GSO) algorithm in the proposed model. Also the area under the curve of the black-hole based optimization (BHBO) and galactic swarm optimization (GSO) algorithms is covered by the big bang-big crunch (BBBC) algorithm in Beneish model(1999). Therefore, the best algorithms for training the multi-layer perceptron neural network belong to the galactic swarm optimization (GSO) algorithm in the proposed model by the 12.7% error and to the Big Bang- Big Crunch (BB-BC) algorithm in Beneish model (1999) by the 36.51% error compared to the other cosmological algorithms in this study to detect and identify of manipulator companies.

Stock Market in Economic Growth: The Case of MENA Countries

Mohammad Ali Aboutorabi; Mohammad ali Falahi

Volume 20, Issue 6 , August 2013, , Pages 29-47

https://doi.org/10.22067/pm.v20i6.36349

Abstract

According to the relationship between financial development and economic growth, the question is whether the type of financial structure (bank-based or market-based financial system) can affect the economic growth? This paper attempts to find an answer to the above mentioned question by surviving the ... Read More

Mixed- Asset Portfolio Optimization

soudeh sabahi; Farimah Mokhatab Rafiei; MohammadAli Rastegar

Volume 27, Issue 19 , June 2021, , Pages 249-278

https://doi.org/10.22067/pm.v27i19.84579

Abstract

Introduction At the core of any investment lies the return on investment. To gain a favorable return, an investor should take investment-related risks. The interaction between risk and return can lead to decisions on asset allocation. A key strategy in investment discussions is diversification ... Read More Introduction At the core of any investment lies the return on investment. To gain a favorable return, an investor should take investment-related risks. The interaction between risk and return can lead to decisions on asset allocation. A key strategy in investment discussions is diversification in investment portfolio. Investment strategy is undetermined in different assets such as security, gold, currency and cryptocurrency. Despite the temporary recession and success of certain assets, it is hard to prioritize investment among assets (in terms of risk and return) to ensure that the investor makes the highest profit at the lowest risk. Thus, the present research used the Mean-CVaR model along with the Extreme value theory (EVT) based on Copula’s theory to estimate the correlations among time series. It used the dynamic conditional correlation (DCC) estimation method to measure the joint distribution of assets regardless of the normality assumption of data, collinearity, priorities and weights of investment in assets as optimal values. Theoretical Framework Diversification of conventional investment portfolio which only involves cash and security with alternative assets such as goods, currency and estate helps to decrease the correlation of assets and increase its resistance to severe changes in stock market. It, thus, helps to improve the performance of investment portfolio (Fischer & Lind-Braucher, 2010). Moreover, due to the low correlation between conventional assets and cryptocurrency and its high-efficiency, cryptocurrency is a good instrument to be combined with diverse investment portfolios and can increase the Sharpe ratio (Chuen et al., 2017). One assumption of the distribution of financial return time series is the normality of data. However, in actuality, many financial return time series are not normal. When the normality assumption is violated, Value at Risk (VaR) is a proper measure. Risk exposure value is not an integrated risk measurement and due to the lack of sub-aggregation property, may be inefficient in optimizing investment portfolio. Thus, researches introduced Conditional Value at Risk (CVaR) as an integrated measure and an alternative for VaR. Methodology As the return on financial assets is marked by a fat tail and is not marked by a normal distribution of data, to better predict the distribution of series, EVT was used. Moreover, Copula’s theory was adopted and the structure of correlations among series as time-varying was modelled via the dynamic conditional correlation estimation and the joint distribution of assets was analyzed regardless of data normality and collinearity. Then, the Mean-CVaR model was used to estimate the risk exposure value and set the investment priorities and weights among assets in Tehran Stock Exchange, Gold Coin, USD and Bitcoin as optimized values. In this research, for an optimal allocation of investment among four above assets in daily return, Tehran Stock Exchange index (TEPIX) was used. The daily return on investment in Gold Coin (the old version) was estimated in Rials. That of USD was estimated in Rials in Tehran free market. Finally, the daily return on investment in Bitcoin was estimated in Rials between October 2014 and April 2018. Results & Discussion A negative correlation was estimated via DCC-Copula between certain assets, which shows that when a particular asset gains higher return on investment (than the mean value), the other asset does not follow the same trend. Thus, investors are capable of diversifying their portfolio accordingly. Prediction of return on assets showed that the highest expected daily return on investment belonged, respectively, to Bitcoin, Gold Coin, Dollar and Tehran Stock Exchange. Moreover, as the optimized weights showed for zero CVaR, due to the low variance, the greatest investment weight was investment in Tehran Stock Exchange. The higher the investor’s risk-taking, the greater the investment weight of Gold Coin and Bitcoin. Conclusions & Suggestions Considering the investor’s risk-taking level, if s/he tolerates the least risks, s/he is suggested to make the most investment in securities. An increase in the minimum expected return on investment is followed by an increase in the investment share of Gold Coin and Bitcoin. Thus highly risk-taking investors are suggested to invest in Bitcoin and low risk-taking counterparts are suggested to invest in Gold Con. Considering the conditional Sharp (C-Sharp) ratio optimal portfolio indicated a better performance of various portfolios than any other asset, and the best performance of the portfolio includes Gold Coin with more than 70% and Dollars and Bitcoins with an equal weight. Furthermore, according to the C-Sharp ratio in the optimal portfolio, the minimum weight of Gold Coin is 60% and the maximum share of Dollar and Bitcoin is 20%.

A Survey of the Impact of Financial Development on the Relationship between Natural Resource Rents and Augmented Trust in Iran

Mohammad Ali Aboutorabi

Volume 26, Issue 17 , September 2019, , Pages 137-166

https://doi.org/10.22067/pm.v26i18.80387

Abstract

Introduction: While the literature on the role of the financial development on economic growth and development is still expanding, there seems to be a definite consensus among economists regarding its positive impact on economic growth (Beck et al., 2000). This positive impact has led to the formation ... Read More Introduction: While the literature on the role of the financial development on economic growth and development is still expanding, there seems to be a definite consensus among economists regarding its positive impact on economic growth (Beck et al., 2000). This positive impact has led to the formation of researches in this field that have focused on the central role of financial development in the economies of countries. The importance of financial development is particularly important in countries that try to get benefits from the sale of natural resources, as they have failed to get advantages from the benefits of managing these resources in order to achieve sustainable economic growth. According International Monetary Fund (2010), if natural resourcerich developing countries develop their financial systems they will be successful in managing these windfalls. So, they can increase the economy’s absorption capacity of natural resources revenues and stay away from any potential negative effects. Theoretical Framework: The process of Economic growth in natural resource-rich countries focuses on the development of the financial system through four basic ways, namely the transforming of natural capital into four forms of capital, whether tangible (including foreign capital and physical capital) and intangible (including human capital and social capital). Given the particular importance of intangible capital to sustainable economic growth (World Bank, 2012), this article focuses on generalized trust (as an indicator of social capital). In fact, trust between individuals or between individuals and institutions is manifested by sharing information and social norms, and its higher levels are associated with more productive individuals and consequently higher economic growth (Elkhuizen, 2016: 6). Algan and Cahuc (2010) state that trust is one of the key determinants of economic development in all countries. They argue that generalized trust is the main factor to success in achieving economic development (Algan and Cahuc, 2010: 2060). Numerous empirical studies in the field of political science have focused mainly on the pivotal role of trust as an indicator of social capital in economic growth and development (Banfield, 1985; Arrow, 1972; Gambetta, 1988; Coleman, 1990; Greif, 1993; Fukuyama, 1995; and Putnam, 2000). Given the key role of financial system development in achieving sustainable economic growth in resource-rich countries, and on the other hand, the high importance that public confidence plays in achieving the above objective, an important question arises: "Can financial development leads to getting benefits from natural resources revenues in the way of increasing augmented trust in the economy? ". In fact, what is referred to in the literature to the curse of natural resources is related to the negative impact of resources rents on the formation of various forms of capital. So, in countries that have been able to manage these revenues through financial development, the negative impact of natural resources have not been seen (Van der Ploege, 2010). Thus the existence of some natural resource-rich countries that through their developed financial systems have been able to properly manage the sources and inflows of their natural resource revenues and achieve significant economic growth (such as Norway, Australia and The Netherlands), can lead to proposing as an operational model for many resource-rich developing countries, including Iran. Methodology: Overall, from a policy perspective, it is important to understand the impacts of natural resource rents on augmented trust and whether this (positive or negative) effects will be improved through a well-developed financial institutions? In the present paper, in order to answer the basic question of this study, first, macroeconomic indicators that affect augmented trust are identified and then to study the impact of financial system development (in the banking sector) on how these rent affect augmented trust, the rolling regression technique (with fixed windows) based on the ARDL method is applied during the period 1970-2014 in Iran. Results & Discussion: The results of the model estimation show that the multidimensional development of the financial system in the banking sector has the potential to improve the impact of natural resource rent on public confidence in Iran. Therefore, the development of the financial system as a key structural policy is recommended for positive utilization of natural resources in Iran. Conclusions & Suggestions: From a policy perspective, it can be said that given the potential of the financial banking system for getting positive utilization of the rents from natural resources in order to increase augmented trust, special attention should be paid to the factors driving the financial development in Iran. Of course, regard to the flaws in the system, such as the existence of financial repression, the existence of suboptimal controls, and the lack of competitive space among financial intermediaries, we could say that if the obstacles against financial development are eliminated, it can be seen its improving effects on converting natural resources income into social capital accumulation and achieving sustainable growth and development. In this regard, policymakers should pay particular attention to the main channels of financial development in order to enhance the role of it on how resources rents affect generalized trust.

Original Article

Investigating the Factors Affecting the Error of Predicting Iran Government Budget Expenditures

Meysam Pashaee; Mehdi Fathabadi

Articles in Press, Accepted Manuscript, Available Online from 20 February 2023

https://doi.org/10.22067/mfe.2023.77014.1196

Abstract

The government budget is the largest and most important financial document of the country, it is expected every year. Unfortunately, the forecast error in budget expenditures and revenues has caused a budget deficit for the country in consecutive years. Therefore, in the present study, the factors affecting ... Read More

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Original Article Financial monetary economy

The effect of banks' performance on the economic integration of provinces: an approach Spatial econometrics

saeed rahimi; parvaneh salatin; Mahmoud Mahmoudzadeh; Masoud Sufi Majidpour

Articles in Press, Accepted Manuscript, Available Online from 03 May 2023

https://doi.org/10.22067/mfe.2023.78796.1235

Abstract

In this study, the effect of banks' performance on economic convergence in the provinces in the period of 2018-2019 has been investigated using spatial econometrics. The results of the estimation of the models showed that the ratio of facilities to bank deposits as an indicator of banking performance ... Read More

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Original Article Bank

Designing a modle for prioritizing Rial letter of credit applicants: a solution for developing the credit services in Bank Saderat of Iran

MOHAMMAD HOSSEIN Hadavi; Behrooz Ghasemi; SOHEIL SARMAD SAEIDI

Articles in Press, Accepted Manuscript, Available Online from 03 May 2023

https://doi.org/10.22067/mfe.2023.80623.1275

Abstract

In the current situation of the country, realizing macroeconomic policies and achieving the goals of the resistive economy, financing the needs of the real and productive sectors of the economy, especially in the field of indirect provision of funds needed for those active in industrial markets, has ... Read More

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Original Article Financial Economics

Studying the Effect of Financial Friction and Development Shocks on Knowledge Base Index of Economic Sectors in Iran

Sareh Amirmojahedi; Ali Raeispour Rajabali; seied abdolmajed jalaee esfandabadi

Articles in Press, Accepted Manuscript, Available Online from 17 July 2023

https://doi.org/10.22067/mfe.2023.81568.1292

Abstract

Considering that in the knowledge economy , production, distribution and application of knowledge and information is the main factor of development, produce of wealth and employment in all economic activities, therefore, it is important to examine the financial friction and financial development on the ... Read More

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Volume 30 (2023)

Volume 29 (2022)

Volume 28 (2021)

Volume 27 (2020)

Volume 26 (2019)

Volume 25 (2018)

Volume 24 (2017)

Volume 23 (2016)

Volume 22 (2016)

Volume 21 (2015)

Volume 20 (2013)

Volume 19 (2013)

Volume 18 (2012)

Volume 17 (2011)

Volume 16 (2009)

Volume 15 (2008)

Volume 14 (2007)

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