ORIGINAL_ARTICLE
Measuring the efficiency of firms listed in Tehran Stock Exchange Using Stochastic Frontier Production Function based on accounting data
One of the most important effective elements in economic growth is the efficiency of manufacturing units. Therefore, measuring the efficiency of firms is necessary in order to increase efficiency in future planning courses. In the current research, using Stochastic Frontier Production Function, the efficiency of firms in Tehran Stock Exchange has been measured. In the above method, the efficient frontier is determined by using the Trans log production function, and the efficiency of each firm measured by the efficient frontier. The most important superiority of Stochastic Frontier Production Function is to specify the role of random and environmental elements (out of firm authorities) and inter-organizational elements (in-firm authorities) to assess the inefficiency of firms as compared to other methods. Thus, 105 firms were selected using maximum likelihood method in 2008-2017 to evaluate the research model. Results indicated that the minerals industry and cement industry with the averages of 53% and 90% had the least and most efficiency values, respectively. Separating the inefficiency values showed that the food industry and chemicals industry had the least and most inefficiency resulting from the firm authorities as 33.6% and 95.2%, respectively. According to research results, financial analysts and investors are recommended to rank the efficiency and assess the performance based on the firm authorities. Due to the importance of efficiency measurement in operational auditing, the auditors are recommended to use the current research model to assess the firm’s efficiency. Also, Organization of Industries and Mines is suggested to tackle the obstacles after identifying the elements out of firm authorities which affect the inefficiency in the firms.
https://www.ijfifsa.ir/article_107042_4faff9f5e4b991c4ebcbc4e7526a531e.pdf
2019-07-01
1
18
10.22034/ijf.2020.208163.1085
Efficiency
Stochastic Frontier Production Function
Trans log Production Function
Vahid
Mahmoudi
v.mahmoudi.a@gmail.com
1
Ph.D. Cadidate, Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
AUTHOR
Mohammad Hossein
Ghaemi
ghaemi_d@ikiu.ac.ir
2
Associate Prof., Faculty of Social Sciences, Imam Khomeini International University, Gazvin, Iran.
LEAD_AUTHOR
Hossein
Kazemi
kazemiho@yahoo.com
3
Assistant prof., Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
AUTHOR
Amiri, H., Raissafari, M. (2005). 'The Efficiency of Commercial Banks in Iran', Journal of Iran's Economic Essays, 2(3), pp. 97-142. (in Persian)
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Coelli, T., Prasada Rao, D. and Battese, G.E. (1998). An Introduction to Efficiency and Productivity Analysis, Kluwe Academic Publishers, Boston, 271 PP.
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26
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30
ORIGINAL_ARTICLE
The Impact of Market Inefficiency and Environmental Uncert`ainty on CEO Risk-Taking Incentives
This study investigates the effect of market inefficiency and environmental uncertainty on CEO risk taking. Prior research, however, have struggled to establish this relation empirically; moreover, some evidence points to the possibility that the CEO risk appetite is lower for firms active in inefficient markets. The opportunistic approach of managers leads to decisions about personal interests and imposing costs on shareholders by decreasing risk taking. In order to investigate the issue, data on companies listed in Tehran Stock Exchange, from 2008 to 2018, were extracted and a panel regression model was used to test the research hypotheses. Consistent with expected relation between market inefficiency, environmental uncertainty and CEO risk taking, the managers' risk taking decreases with respect to market inefficiency and environmental uncertainty. Managers may benefit from increased fluctuations in risk orientation, but are more sensitive than shareholders and have less restrictive choice that avoids higher risk.
https://www.ijfifsa.ir/article_107048_aaeb905ead1b705f33594fd53f3a4ae1.pdf
2019-07-01
19
34
10.22034/ijf.2020.204206.1076
Market inefficiency
Environment Uncertainty
CEO risk taking
Mohsen
Rashidi
rashidi.m@lu.ac.ir
1
Assistant Prof., Department of Accounting, Faculty of Economics and Administrative Sciences, Lorestan University, Iran.
LEAD_AUTHOR
Amess, K., Banerji, S., & Lampousis, A. (2015). Corporate cash holdings: Causes and consequences. International Review of Financial Analysis, 42, 421-433.
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2
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3
Balsam S, Gu, Y., and Mao, C. (2018). Creditor Influence and CEO Compensation: Evidence from Debt Covenant Violations. The Accounting Review: September 2018, Vol. 93, No. 5, pp. 23-50.
4
Bhuiyan M.B.U. & Hooks J., (2019). Cash holding and over-investment behavior in firms with problem directors, International Review of Economics and Finance (2019), doi: https:// doi.org/10.1016/j.iref.2019.01.005.
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6
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7
Bushman, R., Z. Dai, and X. Wang. (2010). Risk and CEO turnover, Journal of Financial Economics 96, 381–398.
8
Chen, D., & Zheng, Y. (2014). CEO Tenure and Risk-Taking. Global Business and Finance Review, 19(1): 1-27.
9
Cziraki, P and Xu, M. (2014). CEO job security and risk-taking. FMG disussion papers (DP729). The London School of Economics and Political Science, London, UK.
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12
Ferris, SP, Javakhadze, D, Rajkovic, T. (2019). An international analysis of CEO social capital and corporate risk‐taking. Eur Financ Manag. 25: 3– 37.
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15
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16
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17
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21
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22
Rashidi, M. (2018). The Role of Environmental Uncertainty, Financial Constraints and Accounting Conservatism in Limiting the Performance Outcomes Due to Manager Overconfidence. Accounting and Auditing Review, 25(3), 347-366. (in Persian)
23
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24
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26
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27
ORIGINAL_ARTICLE
Modeling Assets Pricing Using Behavioral Patterns; Fama-French Approach
Behavioral finance is a new issue raised by some financial intellectuals over the past two decades and has been quickly addressed by professors, experts, and students throughout the world. Investigating the factors affecting investment decisions is carried out in the field of behavioral finance; in other words, the focus of behavioral finance is on the specific charac-teristics of human behavior and applying them in asset pricing. Empirically, pricing models rarely include psychological factors, but the noticeable point is that nowadays, researchers have found behavioral factors influencing empirical asset pricing models that can manipulate returns on asset mispricing. Behavioral asset pricing is the result of applying behavioral finance theories within traditional asset pricing theories. Thus, despite the existence of many asset pricing models, due to their weaknesses and lack of comprehensiveness, as well as the necessity of reviewing behavioral factors, this study aims to model asset pricing through behavioral models. Using the data from 141 listed firms in Tehran Stock Exchange over the years 2008 to 2017 and multivariate regression, this study is an attempts to model asset pric-ing through employing behavioral models and Fama-French approach. Using Fama-French approach, the results showed that accounting information risk, investors’ trading behavior, and investors' sentiment have a direct and significant impact on asset pricing.
https://www.ijfifsa.ir/article_107050_7417afe29ae798b1028b928e0dbf7401.pdf
2019-07-01
35
61
10.22034/ijf.2020.189760.1032
Accounting information risk Investors’ trading behavior
Investors' sentiment
Stock Returns
Fama-French approach
Mohammad
Nasiri
nasiri.m2010@yahoo.com
1
Ph.D. Candidate, Department of Accounting, Islamic Azad University, Tehran South Branch, Tehran, Iran.
AUTHOR
Nouroz
Nourollahzadeh
nourollahzadeh2020@yahoo.com
2
Assistant Prof., Department of Accounting, Islamic Azad University, Tehran South Branch, Tehran, Iran.
LEAD_AUTHOR
Fatemeh
Sarraf
aznyobe@yahoo.com
3
Assistant Prof., Department of Accounting, Islamic Azad University, Tehran South Branch, Tehran, Iran.
AUTHOR
Mohsen
Hamidian
hamidian_2002@yahoo.com
4
Assistant Prof., Department of Accounting, Islamic Azad University, Tehran South Branch, Tehran, Iran.
AUTHOR
Amaya, D., Christoffersen, P., Jacobs, K., Vasquez, A. (2015). Does realized skewness predict the cross-section of equity returns? Journal of Financial Economics, 118(1): 135-167.
1
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2
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3
Baker, M., Wurgler, J., Yuan, Y. (2012). Global, local and contagious investor sentiment. Journal of Financial Economics, 104, 272-287.
4
Barber, B., Odean, T., Zhu, N. (2009). Do retail trades move markets? Review of Financial Studies, 22(1): 151-186.
5
Barberis, N., Huang, M. (2001). Mental accounting, loss aversion and individual stock returns. Journal of Finance, 56, 1247-1292.
6
Brown, G., Cliff, M. (2001).Investor sentiment, the near-term stock market. Journal of Empirical Finance, 11(1): 1-27.
7
Cen, L., Lu, H., Yang, L. (2013). Investor sentiment, disagreement, and the breadth-return relationship. Management Science, 59(5): 1076-1091.
8
Choi, Y., Lee, S. (2017). Realized skewness and future stock returns: The role of information.Economics, 7(3): 359-378.
9
Derakhshande, S., Ali Ahmadi, S. (2017). Evaluating the Role of Investors' Sentiment on Price Orientation and Turnovers in the Capital Market. Financial Knowledge of Securities Analysis, 10(33): 51-63. (in persian).
10
Easley, D., Ohara, M. (2004). Information and the cost of capital. Journal of Finance, 12, 365-372.
11
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13
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14
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16
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18
Han, B., Kumar, A. (2013).Speculative retail trading and asset prices. Journal of Financial and Quantitative Analysis, 48(02): 377-404.
19
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21
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Jorgensen, B., Li, J., Sadka, G. (2012).Earnings Dispersion and Aggregate Stock Returns.Journal of Accounting and Economics, 53, 1-20.
24
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31
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32
Moghadam, A., Ghadr Dan, E., Rashedi, M. (2014).Stock Returns Forecasts Using Market Ratios in Listed Firms in Tehran Stock Exchange.Accounting and Audit Research, 6(24): 117-102. (in Persian).
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38
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Shiller, R. (2014). Speculative asset prices. American EconomicReview, 104(6): 1486-1517.
41
Stambaugh, R., Yu, J., Yuan, Y. (2012).The short of it: investor sentiment and anomalies. Journal of Financial Economics, 104,288-302.
42
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46
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47
Yang, C., Zhou, L. (2015). Investor trading behavior, investor sentiment and asset prices. North American Journal of Economics and Finance, 34, 42-62.
48
Yu, J., Yuan, Y. (2011). Investor sentiment and the mean–variance relation. Journal of Financial Economics, 100(2): 367-381
49
ORIGINAL_ARTICLE
Developing New Financing Instruments for Iran’s Higher Education System (Case Study: Mortgage Securities Model)
Optimizing the financing of Iran's higher education system faces major challenges such as smallness of the private sector, lack of a competitive market in knowledge production, the state's small role in higher education, and also the absence of new financial instruments in the capital market along with the development of the money market. As a result, the most important financing resources and major clients of academic research projects are state-run organizations, which also raise finance through tuition. Apparently, there are a few reasons why the higher education system should change its financing methods to achieve great goals. These reasons include intensified economic sanctions, declined capacity of the state to finance this sector, decreased power of families and firms to cover educational and research expenses through private budgets, and the necessity of making higher education expenses efficient with respect to the need to train the future workforce. The method of this study is a descriptive-qualitative, which was carried out in two stages of the library and the implementation of the Delphi method by referring to 20 experts. Aiming to introduce new instruments to make banking asset-backed securities (of facilities type) to education and research clients (families and firms), this study seeks to prove the hypothesis that the mortgage-backed securities can be employed to achieve the following goals. The first goal is to grant facilities to the students who are financially unable to pay tuition. This relieves the pressure on the Students Welfare Fund. The second goal is to grant business financing facilities to talented students. Finally, the third goal is to finance the firms that have research needs but are unable to cover the expenses through their revenues. Regarding 17 indicators, the research findings indicate that experts reached a consensus (Kendall's W= 0.702).
https://www.ijfifsa.ir/article_107052_a8b0ca8649d5adace933abc4c8abf91b.pdf
2019-07-01
62
88
10.22034/ijf.2020.210772.1095
Higher education system
Banking System
banking securities
Capital Market
development banks
Atiyeh
Dadjoye Tavakoli
ati.dadjoo@yahoo.com
1
PhD. Candidate, Department of Educational Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
AUTHOR
MohammadAli
Hosseini
mahmaimy2020@gmail.com
2
Associate prof., Department of Rehabitation Management, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
LEAD_AUTHOR
Mostafa
Niknami
dr_niknami@yahoo.com
3
Associate prof., Department of Educational Management, Allameh Tabataba'i University ,Tehran, Iran.
AUTHOR
Mohammad Javad
Salehi
javadsaleh@gmail.com
4
Assistant prof., Department of Economics of Higher Education, Institute for Research and Planning in Higher Education, Tehran, Iran.
AUTHOR
Abdo Tabrizi, H. (1997). Mortgage bonds With mortgage backing (MBS Examples of Various Capital Markets). Journal of Accounting. 123: 3-13. (in persian)
1
Amir Hosseini, Z, Ghobadi, M.(2016). Securities Market in Islamic Markets Compared to Securities in Major World Markets, Journal of Research in Knowledge of Investments. 5(18): 1-15. (in persian)
2
Brada, J, Bienkowski, W, Kuboniwa, M. (2015). International Perspectives on Financing Higher Education. PALGRAVE MACMILLAN.
3
Eftekhari, A, Davari, A. (2009). Review of the general policies of the fifth program in higher education. The Office of Social Studies Research Center of the Islamic Consultative Assembly. (in persian)
4
entezari, J, Gharon, M. (2015). Rationality and Performance of the Government in Financing Iran's Higher Education, Journal of Higher Education. 8(29):11-38. (in persian)
5
Fan, G, Sing, T, Ong, S, Sirmans, C.F. (2010). Governance and Optimal Financing for Asset-Backed Securitization, Journal of Property Investment & Finance. 22(5): 414-434.
6
Farsatkhah, M. (2014). Future Studies of Iranian Higher Education: A Study of Trends, Problems and Challenges, with an Emphasis on Future Future People's Strategies. Research project of the Institute for Research and Planning of Higher Education. (in persian)
7
feghhiye Kashani, M. (2006). Becoming Securities of Assets (Loans) in the Banking Industry. Tehran: Monetary and Banking Research Center - Central Bank of the Islamic Republic of Iran. (in persian)
8
Fried, R, Breheny, J. (2009). Tuition Isn't the Only Thing Increasing: The Growth of the Student Loan ABS Market, Journal of Structured Finance. 11(1):40-45.
9
Global Center on Private Financing of Higher Education. (2009). Recent Innovations in the Private Financing of Higher Education. Available on the Internet at www.ihep.org Accessed.
10
Goksu, A, Goksu, G. A. (2011). Comparative Analysis of Higher Education Financing in Different Countries, Procedia Economics and Finance. 26: 1152-1158.
11
Hong, H, Chae, J.(2011). Student Loan Policies in Korea: Evolution, Opportunities and challenges, Educational Research Journal. 26(1):99- 122.
12
Hosseini, A, Hekmat, H. (2013). The Role of Sukuk Rental and Participation Bonds in Corporate Finance, Quarterly Journal of Accounting Research. 2(8):1-26. (in persian)
13
Ismail, Sh, Bakri, M, Rosalan, A, Noor, A. (2014). Developing a Framework of Islamic Student Loan-backed Securitization, Procedia-Social and Behavioral Sciences. 129:380-387.
14
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32
ORIGINAL_ARTICLE
The Design of Relationship Model between (IRAN) Economic Markets Return and Capital Market Return Exploiting Comonotonicity in Probability Theory
This paper investigates the design of an efficient model so as to anticipate the basic economic market rate of returns. To do so, accepting the relationships, interactions and effectiveness of these markets and exploiting Comonotonic Functions under Probability Function Framework as well as using weekly data for ten years’ period of time(2008-2017) in Iran’s economy we design optimum model and test its capability and estimation power. The results illustrate the efficiency of the achieved model. Furthermore, taking the practical nature of this paper into account, we come up with optimum lag of time and the period of time required to achieve equilibrium in any market and the entire economy as a prototype in the frame of Stock Exchange.
https://www.ijfifsa.ir/article_107054_f141f5e13402c1fd5b1f38abe9a130bd.pdf
2019-07-01
89
106
10.22034/ijf.2020.214153.1101
Behavioral Finance
Economic equilibriums
Comonotonic
Rate of return
Systematic risk
Mohammad Esmaeil
Fadaeinezad
m-fadaei@sbu.ac.ir
1
Prof., Department of Financial Management, Faculty of Management and Accounting, University Of Shahid Beheshti, Tehran, Iran.
AUTHOR
Hamid
Banaeian
h.banaeian@ut.ac.ir
2
PhD, Department of Financial Management, Faculty of Management, University of Tehran, Tehran, Iran.
LEAD_AUTHOR
Abasinejad, Hosein. Mohamadi, Shapur (2005). Analysis of Iranian commercial cycles using Wavelet theories. Economic Research Journal/number/75
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26
ORIGINAL_ARTICLE
Modeling and Rating Financial Soundness Indicators of Commercial Banks Using Confirmatory Factor Analysis and TOPSIS method
Several financial soundness frameworks, such as CAMELS, are currently present in the banking industry, but some evidence suggests that the present frameworks have inefficiencies in an Islamic banking environment. This study is aimed at identifying and prioritizing the adjusted financial soundness indicators in Iranian banks. In this paper, the factors affecting financial soundness in banking industry were investigated and rated based on the viewpoints of 382 banking experts. Data gathering is done by designing a questionnaire. The research method is descriptive-correlation. For data analysis and the testing of the hypotheses, R-test software and confirmatory factor analysis have been used. TOPSIS method is used to rate the indicators from the points of view of senior banking managers. The findings showed capital adequacy, asset quality, profitability, liquidity, management quality, sensitivity to market risk, Islamic banking, corporate governance, and facilities with technical and economic backing affect the financial soundness of banks, while the liquidity and profitability indexes have the most impact.
https://www.ijfifsa.ir/article_107056_dd80c3fe17d9025270402df61e78b07e.pdf
2019-07-01
107
136
10.22034/ijf.2020.182468.1068
Financial Soundness
financial stability
banking industry
Islamic Banking
TOPSIS
Seyed Ahmad
Seyedi
seyedi.acc@gmail.com
1
Assistant Prof., Department of Accounting, Shandiz Institute of Higher Education, Mashhad, Iran.
LEAD_AUTHOR
Mohammad Reza
Abdoli
mrab830@yahoo.com
2
Associate Prof., Department of Accounting, Shahrood Branch, Islamic Azad University, Shahrood, Iran.
AUTHOR
Abdul Karim, N., Al habshi, S., Kassim, S., & Haron, R. (2019). A Critical Review of Bank Stability Measures in Selected Countries with Dual Banking System. Revista Publicando, 6(19), 118-131
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