ORIGINAL_ARTICLE
Applying black- Scholes model to breakdown beta: growth options and the risk of beta miscalculation
When evaluating companies and investment plans, most analysts use a discount rate that is derived from CAPM models. The beta in these models usually represent risks and opportunities of the relative industry, with almost no attention to the risks that are already included in the beta. This ignorance in risk measurement could ultimately impair shareholders value. What makes things critical is that by adjusting risks and opportunities in beta, the result of investment plans and company valuation could be much different. In this paper we use 1 to 10 years of monthly return data for all industries of Tehran Stock Exchange and Iran Fara Bourse and suggest an adjusted beta for each industry which is stripped of the dazzling effects of the debts and growth opportunities. We separately account for breaking down beta into beta of growth opportunities and beta of existing assets for each industry in various timelines between 1 to 10 years. Our results showed that the beta of growth opportunities is bigger than the beta of assets for almost all industries. The mentioned betas can make a big difference in cost of capital and we suggest using them when evaluating investment plans, development plans, valuation of companies and even start-ups.
https://www.ijfifsa.ir/article_111726_fef7b736a84d3c08f94a995be6b93bc6.pdf
2019-10-01
1
22
10.22034/ijf.2020.213958.1102
Systematic risk
Growth Opportunities
evaluation
beta
Amin
Babaei Falah
amin.babaeifalah@gmail.com
1
Ph.D. Candidate, Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
AUTHOR
Maryam
Khalili Araghi
m.khaliliaraghi@gmail.com
2
Assistant Prof., Department of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
LEAD_AUTHOR
Hashem
Nikoomaram
nikoomaram@srbiau.ac.ir
3
Prof., Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran.
AUTHOR
Abvali, M., Khalili araghi, M., hasanabadi, h., & yaghoobnezhad, a. (2019). Optional trading pricing with a new analytic method for the Black Scholes equation. Journal of Financial Management Strategy, 7(3), 121-143.
1
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2
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3
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4
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5
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6
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7
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8
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9
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10
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11
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12
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13
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14
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15
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17
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18
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19
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20
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21
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22
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23
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24
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25
ORIGINAL_ARTICLE
Capacity Building of Green Accounting Consequences Based on the Explanation of Strategic Management Accounting Techniques
Strategic management accounting, including systems and processes in the modern era, is characterized by changes in the competitive environment that, Can be achieved through the participation of companies in the management accounting system, Assist financial managers to make decisions in the value chain and develop green accounting functions. Unfortunately, though, over time, strategic management accounting techniques are still unknown to corporate executives, especially in environmental processes, leading to a decline in corporate participation in strategic decision making. The Purpose of this research is Capacity Building Green Accounting Consequences Based on Explanation of Strategic Management Accounting Techniques by analysis of CARD and developed the theory of Rough (ERST). The methodology of this research is developmental, applied and hybrid and two groups of target population participated in this research. In the first part of 15 experts in the field of accounting at the university level an In the second part, 35 executives participated matrix Tehran Stock Exchange through a questionnaire that both the target population, sampling was homogenous. In this research, in the qualitative part, the components and indices related to the research variables were selected based on content analysis and cross-analysis and then based on Delphi analysis and hierarchical analysis in order to achieve theoretical adequacy. Then, in the quantitative section, through the analysis of the Rough Complex analysis, the decision tree determined the most effective green accounting function/outcome and strategic management accounting technique, and finally, the product life cycle costing technique is the most effective strategic management accounting technique for enhancing green accounting functions. In fact, the results showed that product cycle costing technique is a factor for enhancing the cost savings of recycling and waste recycling costs and increasing the competitiveness of the company as a component of green accounting competitive Consequences.
https://www.ijfifsa.ir/article_111728_3cece1c4016588b65d03237c9ea6ea49.pdf
2019-10-01
23
59
10.22034/ijf.2020.226757.1117
Strategic Management Accounting Techniques
Consequences of Green Accounting
Analysis CARD
Developed Theory of Rough
Behjat
Abbasi
behjatsi@yahoo.com
1
Ph.D. Candidate, Department of Accounting, Damavand Branch, Islamic Azad University, Damavand, Iran.
AUTHOR
Mohammadhamed
Khanmohammadi
khanmohamadii@yahoo.com
2
Assistant Prof., Department of Accounting, Damavand Branch, Islamic Azad University, Damavand, Iran.
LEAD_AUTHOR
Zahra
Moradi
za5moradi@gmail.com
3
Assistant Prof., Department of Management, Damavand Branch, Islamic Azad University, Damavand, Iran.
AUTHOR
Tahereh
Mahmoodiyan
mahmodian.mina@yahoo.com
4
Assistant Prof., Department of Psychology, Behshahr Branch, Islamic Azad University, Behshahr, Iran.
AUTHOR
Adams, C. and Larrinaga, C. (2019). Progress: engaging with organizations in pursuit of improved sustainability accounting and performance, Accounting, Auditing & Accountability Journal, 32(8): 2367-2394. https://doi.org/10.1108/AAAJ-03-2018-3399
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62
ORIGINAL_ARTICLE
Analysis of Collective Behavior of Iran Banking Sector by Random Matrix Theory
Banked based financial sector of Iran leads us to focus on the banking industry and its components. One of the important aspects of this industry is its coupling structure. In this paper, we have analyzed the collective behavior of Iran banking sector by Random Matrix Approach (RMT). This technique is useful for splitting the information part of the correlation matrix from the random region. This research confirms good compliance with random matrix predictions. By removing the market mode of the system the average of the banking cross-correlation matrix changes. Then, by calculation of the participation ratio, node participation ratio and relative participation ratios of these banks, it is shown that the collective behavior of the system is so fragile. Also, by applying local and global perturbations on the banking sector, it is shown that this system is very sensitive to the global perturbation and the mean value of cross-correlations decreases rapidly that means some banks have crucial effects in the market.
https://www.ijfifsa.ir/article_111729_076f38c985aefe332a2059b9f8ea5802.pdf
2019-10-01
60
75
10.22034/ijf.2019.111729
Iran banking sector
Random Matrix Theory
Collective Behavior
Perturbation
Reza
Raei
raei@ut.ac.ir
1
Prof., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
AUTHOR
Ali
Namaki
alinamaki@ut.ac.ir
2
Assistant Prof., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
AUTHOR
Hanie
Vahabi
hanie.vahabi@ut.ac.ir
3
MSc., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
LEAD_AUTHOR
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Namaki, A., Raei, R., Asadi, N., & Hajihasani, A. (2019). Analysis of Iran Banking Sector by Multi-Layer Approach. Iranian Journal of Finance, 3(1), 73-89.
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Cattell, R. B. (1943). The description of personality: Basic traits resolved into clusters. The journal of abnormal and social psychology, 38(4), 476.
29
Ward Jr, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American statistical association, 58(301), 236-244.
30
ORIGINAL_ARTICLE
The Relationship between Audit Fees and Stock Price Crash Risk
The purpose of this study is to examine the relationship between audit fees and stock price crash risk. The study period is from 2013 to 2017 and the selected sample consists of 110 companies listed on Tehran Stock Exchange (TSE). To test the hypotheses of the research, the ordinary least squares regression is used. The findings show that there is a positive and significant relationship between audit fees and stock price crash risk. In other words, for companies with higher audit fees, there is a greater risk of falling stock prices.
https://www.ijfifsa.ir/article_111731_3252d93b204ffe28608be19a14b2c5d4.pdf
2019-10-01
76
89
10.22034/ijf.2020.187841.1027
Audit fees
Stock Price Crash Risk
down-to-up volatility
Negative skewness of stock return
Zabihollah
Khani
khanifinance@gmail.com
1
Assistant Prof., Department of Accounting, Fasa Branch, Islamic Azad University, Fasa, Iran.
AUTHOR
Hossein
Rajabdorri
hosrado@gmail.com
2
Ph.D. Candidate, Department of Accounting, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran.
LEAD_AUTHOR
Amani, A., and Davani, G. (2009). Service, Fees and auditor’s ranking, World Economy, No. 1998. (In Persian).
1
Bedard, J.C., and Johnstone, K.M. (2004). Earnings manipulation risk, corporate governance risk, and auditors’ planning and pricing decisions, The Accounting Review, 79 (2): 277-304.
2
Botosan, C., and Plumlee, M. (2002). A re-examination of disclosure level and the expected cost of equity capital, Journal of Accounting Research, 40 (1): 21-40.
3
Callen, J.L., and Fang, X. (2011). Institutional investors and crash risk: Monitoring or expropriation?, Available At URL: Http://Www.Ssrn.Com.
4
Chen, J., Hong, H., and Stein, J. (2001). Forecasting crashes: Trading volume, past returns, and conditional skewness in Stock Prices, Journal of Financial Economics, 61: 345–381.
5
Diamond, D., and Verrecchia, R. (1991). Disclosure, liquidity and cost of capital, Journal of Finance, 46 (4): 1325-1359.
6
Dimson, E. (1979). Risk measurement when shares are subject to infrequent trading, Journal of Financial Economics. 7: 197-226
7
Ebrahimi, K., Peyvandi, M., and Fakharmanesh, M. (2015). Studying the effect of company ownership structure on audit fee and opinion of independent auditors of companies, Financial Accounting Journal, 6 (24): 59-78. (In Persian)
8
Fallahzadeh Abarghuyi, A., Taftian, A., and Heyrani, F. (2017). An investigation of the interrelationship between discretionary disclosures of information with concurrency and stock price crash risk Using concurrent equation system, Financial Accounting, 9 (36): 53-75. (In Persian).
9
Fama, E., and French, K. R. (1993). Common risk factors in the returns on stocks and bonds, Journal of Financial Economics. 33: 3–56.
10
Hackenbrack, K., Jenkins, N., and Pevzner, M. (2011). Relevant but delayed information in negotiated audit Fees, Auditing: A Journal of Practice and Theory, 33 (4): 95-117.
11
Healy, P., and Palepu, C. (2001). Information asymmetry, corporate disclosure and capital markets, Journal of Accounting and Economics, 31: 405-440.
12
Heflin, F., K. Shaw, and Wild, J. (2005). Disclosure quality and market liquidity: the effect of depth quotes and order sizes, Contemporary Accounting Research, 22 (4): 829- 865.
13
Hong, H., and Stein, J. (2003). Differences of opinion, short-sales constraints, and market crashes, The Review of Financial and Studies, 16 (2): 487-525.
14
Hribar, P., Kravet, T., and Wilson, R. (2010). A new measure of accounting quality, Working Paper. The University of Iowa.
15
Hutton, A., Marcus, A.J., and Tehranian, H. (2009). Opaque financial reports, R2, and crash risk, Journal of Financial Economics, 94: 67-86.
16
Jin, L. and Myers, S.C. (2006). R2 around the world: new theory and new tests, Journal of Financial Economics, 79: 257-292.
17
Khan, M., and Watts, R. L. (2009). Estimation and empirical properties of a firm-Year measure of accounting conservatism, Journal of Accounting and Economics, 48: 150- 132.
18
Kim, J., Li, Y., and Zhang, L. (2010). Corporate tax avoidance and stock price crash risk: firm-level analysis, Journal of Financial Economics, 100 (3): 639- 662.
19
Kim, O., and Verrecchia, R. (1994). Market liquidity and volume around earnings announcements, Journal of Accounting and Economics, 17: 41-67.
20
Kothari, S.P, Shu, S., and Wysocki, P. (2009). Do managers withhold bad news?, Journal of Accounting Research, 47 (1): 241-276.
21
Lambert, R., Leuz, C, and Verrecchia, R. (2007). Accounting information, disclosure, and the cost of capital, Journal of Accounting Research, 45 (2): 385-420.
22
Lang, M., and Lundholm, R. (2000). Voluntary disclosure and equity offerings: reducing information asymmetry or hyping the stock?, Contemporary Accounting Research, 17 (4): 623-662.
23
Mitra, S., Bikki, J., and Al-Hayale, T. (2017). The effect of managerial stock ownership on the relationship between material control weaknesses and audit fees, Review of Accounting and Finance, 16 (2): 239-259.
24
O’Keefe, T., Simunic, D. and Stein, M. (1994). The production of audit services: evidence from a major public accounting firm, Journal of Accounting Research, 32 (2): 241-261.
25
Picconi, M., and Reynolds, J.K. (2010). Do auditors know more than the market?, Working paper, College of William and Mary.
26
Rasekhi, M., and Arad, H. (2017). Investigating the relationship between auditor's fees and delays in submitting audit report in Tehran Stock Exchange, New Research in Management and Accounting, 20: 169- 185. (In Persian).
27
Razmian, Z., Fallah Shams, M., Khodaei Valahzaghard, M., Hasani, M. Forecasting Crash risk using Business Strategy, Equity Overvaluation and Conditional Skewness in Stock Price, International Journal of Finance and Managerial Accounting, 2020; 4(16): 13-25.
28
Riahi-Belkaoui, A. (2003). Intellectual capital and firm performance of US multinational firms, Journal of Intellectual Capital, 4: 215-226.
29
Sukrisno, A. (2012). Auditing (Petunjuk Praktis Pemeriksaan Akuntan oleh Akuntan Publik). Edisi Keempat. Salemba Empat: Jakarta.
30
Tulus Suryanto (2014). Determinants of audit fee based on client attribute, auditor attribute, and engagement attribute to control risks and prevent fraud: A study on public accounting firms in Sumatra-Indonesia, International Journal of Economics and Business Administration, 2 (3): 27-39
31
ORIGINAL_ARTICLE
Evaluating and Comparing Systemic Risk and Market Risk of Mutual Funds in Iran Capital Market
Mutual funds are one of the most paramount investment mechanisms in financial markets. By playing a financial intermediary role, they give nonprofessionals access to professionally managed portfolios of securities and provide numerous benefits for both the capital market and investors simultaneously. This study evaluated and investigated the systemic risk of mutual funds in the Iran capital market by adopting a Conditional Value at Risk (CoVaR) approach and employing quantile regression. In the finance literature, systemic risk is the probability of a downfall in the financial system when a segment or an individual component gets in distress. This risk can trigger instability or shock in financial markets and the real part of the economy. The results revealed that stock (equity) mutual funds were systemically more important than other funds, including fixed-income and balanced mutual funds, due to the high volatility in their return, which makes them riskier. To compare systemic risk and market risk among mutual funds, funds classified into five different groups based on their systemic risk. According to this categorization, analysis of variance illuminated that the market risk of mutual funds had a direct relationship with their systemic risk, such that a higher systemic risk of a fund stood for higher market risk.
https://www.ijfifsa.ir/article_111732_5f8e19983f7831d351d4c0d8ea391b10.pdf
2019-10-01
90
112
10.22034/ijf.2020.231342.1127
Conditional value at risk
Mutual Funds
quantile regression
systemic risk
Fereshteh
Shahbazin
f_shahbazin@yahoo.com
1
Ph.D. Candidate of Department of Financial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AUTHOR
Hasan
Ghalibaf Asl
h.ghalibafasl@alzahra.ac.ir
2
Prof., Department of Finance and Insurance, Faculty of Management, Alzahra University, Tehran, Iran.
LEAD_AUTHOR
Mohen
Seighali
seighali@ut.ac.ir
3
Assistant Prof., Faculty of Accounting and Management, Islamic Azad University, Qazvin, Iran.
AUTHOR
Moslem
Peymani Foroushani
m.peymani@atu.ac.ir
4
Assistant Prof., Faculty of Finance and Banking, Allameh Tabatabaei University, Tehran, Iran.
AUTHOR
Abergel, F., Chakrabarti, B., Chakraborti, A., & Ghosh, A. (2012). Econophysics of systemic risk and network dynamics. Springer Science & Business Media.
1
Abrishami, H., Mehrara, M., & Rahmani, M. (2019). Measuring and Analysis of Systemic Risk in Iranian Banking Sector and Investigating Its Determinants. Econometric Modeling, 11-36.
2
Adrian, T., & Brunnermeier, M. (2016). CoVaR: Dataset. American Economic Review.
3
Adrian, T., & Brunnermeier, M. K. (2011). CoVaR. . CoVaR (No. w17454). National Bureau of Economic Research.
4
Ahmadi, Z., & Farhanian, M. (2015). Systemic Risk Measuring in Tehran Stock Exchange with CoVaR and MES Approaches. Journal of Securities Exchange, 7(26), 3.
5
Azari Gharelar, A., & Rastegar, M. (2015). Master thesis on A Comparision Among Systemic Risk Measures in Tehran Stock Exchange. Tehran, Iran: Kharazmi University.
6
Ebadi, J., Elahi, N., & Houshmand Gohar, S. (2019). Effect of Exchange Rate Change Shocks on Systemic Risk Index Among Mutual Funds. Economic Research and Policies, 27(89), 373-398.
7
Farzinvash, A., Elahi, N., Gilanipour, J., & Mahdavi, G. (2018). The evaluation of Systemic Risk in the Iran Banking System by Delta Conditional Value at Risk (CoVaR) Criterion. Financial Engineering and Portfolio Management, 8(33), 265-281.
8
Giglio, S., Kelly, B., & Pruitt, S. (2016). Systemic risk and the macroeconomy: An empirical evaluation. Journal of Financial Economics, 119(3), 457-471.
9
Girardi, G., & Ergün, T. (2013). Systemic risk measurement: Multivariate GARCH estimation of CoVaR. Journal of Banking & Finance 37.8, 3169-3180.
10
Hamid Abrishami, M. M. (2019). Measuring and Analysis of Systemic Risk in Iranian Banking Sector and Investigating Its Determinants. Econometric Modeling, 11-36.
11
Hekmatifarid, S., Rezazadeh, A., & Malek, A. (2018). The Estimation of Systematic Risk in Iranian Financial Sectors (ΔCoVaR Approach). Quarterly Journal of Economic Modelling, 12(3), 99-122.
12
Jin, X., & Simone, F. (2014). Banking systemic vulnerabilities: A tail-risk dynamic CIMDO approach. Journal of Financial Stability(14), 81-101.
13
Klaus, B., & Rzepkowski, B. (2009). Risk spillover among hedge funds: The role of redemptions and fund failures. European Central Bank.
14
Kleinow, J., Moreira, F., & Strobl, S. (2017). Measuring systemic risk: A comparison of alternative market-based approaches. Finance Research Letters 21, 40-46.
15
Mohammadiaghdam, S., Ghavam, M., & Fallahshams, M. (2017). Assessment of the Systemic Risk Originated from the Currency Shocks in the Financial Markets of Iran. Financial Research, 19(47), 475-504.
16
Moradmand Jalali, M., & Hasanlou, K. (2016). The Assessment of Share of Banks, Insurance and Investment Companies in Systemic Risk. Quarterly Journal of Islamic Finance and Banking Studies, 67-92.
17
Noralidokht, S., & Dadashi Arani, H. (2015). Master thesis on Contagion Robustness in Financial Networks. Zanjan, Iran: Institute for Advanced Studies in Basic Sciences (IASBS).
18
Pellegrini, C., Meoli, M., & Urga, G. (2017). Money market funds, shadow banking and systemic risk in the United Kingdom. Finance Research Letters 21, 163-171.
19
Rahimi Baghi, A., Arabsalehi, M., & Vaez Barzani, M. (2019). Assessing the Systemic Risk in the Financial System of Iran using Granger Causality Network Method. Financial Research, 21(53), 121-142.
20
Sadeghi, M. (2012). Systemic risk management in Iran financial institutions. Research, Development and Islamic Studies Department of Iran Securities and Exchanges Organization.
21
Shirmohammadi, F., Chavoshi, S., & Feshari, M. (2015). Master thesis on systemic risk in Iran financial market. Tehran: Iran University of Economic Science.
22
White, H., Kim, T.-H., & Manganelli, S. (2015). VAR for VaR: Measuring tail dependence using multivariate regression quantiles. Journal of Econometrics 187.1, 169-188.
23
ORIGINAL_ARTICLE
Analyzing Shareholder Network in the Tehran Stock Exchange
The stock market plays an important role in the economic development of countries. Network analysis is one of the latest methods in analyzing the stock market. It is a new concept for a macro view of the whole market in quantitative science literature. Therefore, this research analyzes the available Shareholder network in the Tehran Stock Exchange from 2013 to 2017. This research is based on a type of data collected and analyzed is quantitative research. And, its’ type is network analysis. The research results indicate that many of shareholders are connected to each other, although a class structure governs their relations. Some of the shareholders, in comparison with others, have a better position. Having a better position caused them to encounter fewer mediators in gaining access to other shareholders, and also easier access to available resources. The shareholders’ ability in gaining access to information through the cluster of network members enhances too. Therefore, it is claimed that these shareholders can play the role of key actors in the governing structure. Also, the results of the Pareto distribution indicate that the distribution of power among the Shareholders is approximately 25/75, that is, 75 per cent of the strength in the hands of 25 per cent of the Shareholders.
https://www.ijfifsa.ir/article_111733_d4d4bff5651fd01b7d886b38046d4af6.pdf
2019-10-01
113
134
10.22034/ijf.2020.207802.1084
Shareholder
Network analysis
Tehran Stock Exchange
Reza
Taghizadeh
rezataghizadeh@yazd.ac.ir
1
Assistant Prof., Faculty of Economic, Management and Accounting, Yazd University, Yazd, Iran.
LEAD_AUTHOR
Amin
Nazemi
anazemi@rose.shirazu.ac.ir
2
Assistant Prof., Department of Acounting, School of Economics Management and Social Sciences, Shiraz University, Shiraz, Iran.
AUTHOR
Mohammad
SadeghzadehMaharluie
s.msadeghzadeh@rose.shirazu.ac.ir
3
Ph.D. Candidate, Department of Accounting, Faculty of Economic and Management Sciences, Shiraz University, Shiraz, Iran.
AUTHOR
Abbasi, A., Hossain, L., Leydesdorff, L. (2012). Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks. Journal of Informetrics, 6(3), 403-412.
1
Abedini, M.A., Senobar, N., and A. fazlzadeh (1395). Investigation the corporate governance mechanisms and boards bonus of listed companies in Tehran Stock Exchange, Stock Exchange journal. 33, 93-114. (in Persian)
2
Babu Roy, R and Kumar Sarkar, U. (2011). A Network approach to capture co-movements of global stock returns" Indian institute of management Calcutta. Working Paper. WPS NO.676.
3
Boginski, V., Butenko, S., Pardalos, P.M. (2005). Statistical analysis of financial networks. Computational Statistics & Data Analysis, 48, 431-443.
4
Borgatti, S. P. (2005). Centrality and network flow, Social Networks, 27 (1), 55–71.
5
Dastkhan, H.N., Gharneh, Sh. (2018). How the ownership structures cause epidemics in financial markets: A network-based simulation model, Statistical Mechanics and its Applications, 492, 324-342.
6
De Nooy, W., Mrvar, A., Batagelj, V. (2005). Exploratory social network analysis with pajek, structural analysis in the social sciences. Cambridge: Cambridge University Press, 1th Ed.
7
Deylami, S., and Safari M. (2016). The relation between corporate governance quality and stock return volatility, journal of empirical research in accounting, 21, 115-136. (in Persian)
8
Edwards, G. (2010). Mixed-method approaches to social network analysis. National Centre for Research Methods, ESRC National Centre for Research Methods Review Paper.
9
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10
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11
Hashemi, A., and Bakrani, K., (2011). An overview of the influential literature of capital decisions on ownership structure and corporate governance mechanisms, Journal of Accounting and Financial Management, 2, 111-128. (In Persian)
12
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13
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14
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15
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16
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17
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19
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20
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21
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22
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23
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24
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25
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27
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28
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29
Taghizadeh. R., Nazemi, A. (2019). Network analysis of stock prices case study: listed pharmaceutical companies in the OTC and stock market of Iran. Journal of Investment Knowledge, 8 (29), 171-188. (in Persian)
30
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33
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34