Investigating the effect of risk on the return of the insurance industry in the Iranian economy using generalized conditional autoregression models, ARIMA-GARCH / TARCH and beta coefficient

الموضوعات :

Abedin Saeidikia ¹ , Dariush Hassanvand ² , Reza Maaboudi ³ , Farhad Tarahomi ⁴

1 - Ph.D. Student, Department of Economics, Aligudarz Branch, Islamic Azad University, Aligudarz, Iran.
2 - Assistant Professor, Department of Economics, Faculty of Management and Economics, Lorestan University, Khorramabad, Iran.
3 - Assistant Professor, Faculty of Humanities, Department of Economics, Ayatollah Ozma Borujerdi University.
4 - Post Doctorate in Economics, Faculty of Social and Economic Sciences, Al-Zahra University, Tehran, Iran.

تاريخ الإرسال : 22 السبت , رمضان, 1443 تاريخ التأكيد : 08 الثلاثاء , ذو القعدة, 1443 تاريخ الإصدار : 11 الإثنين , شوال, 1444

الکلمات المفتاحية: Insurance Industry, beta coefficient, Risk, trend movement of returns,

ملخص المقالة :

Objective: A study of the movement of the insurance industry returns shows that the movement of income returns was less than the movement of the insurance industry. The movements of lower income returns than the movements of paid losses of the insurance industry in the economy are due to various variables, including the management of the insurance industry, part of which is due to risk recognition. Which helps managers in the insurance industry, to the extent of tolerable and intolerable risks in the acceptance or non-acceptance of various swimming risks, and by managing them play an important role in marketing and increasing the demand for insurance and in general, In line with the optimal growth of the insurance industry.Methodology: This study, using generalized conditional autoregression models, ARIMA-GARCH / TARCH and beta coefficient, has evaluated the impact of risk on the return of the insurance industry in the Iranian economy during the period 1350-1398.Results: The results showed that there is a significant relationship between the study of the impact of risk on the return of Basma industry. Also in this research, systematic risk has been investigated using the beta coefficient method. Since the result of the impact of risk on the return on income of the insurance industry is 67%. Because the obtained beta coefficient is less than one and greater than zero. This result indicates that the income of the insurance industry is smaller than the general trend of market movement and risk aversion

المصادر:

 Asays, H., and Jalili Kamjoo, S. P., Study of the effect of political, economic and financial risk regimes on life insurance demand, Scientific Journal of Insurance Research, Serial Number 141-Spring 2021, 36(1).

 Doi: 10.22056/JIR.2021.168010.2459

 

Peykarjoo, K., and Hosseinpour, Badrieh Measurin, g value at risk in insurance companies using the GARCH model, Insurance Industry Quarterly, Winter 2010, 100(4), P. 58-33. Doi: 10.22056/JIR.2010.246129.2780.

 

Jalali, S. A., Jafari, M., and Jafari, S., Study of financial development on the process of globalization of the economy in Iran,Scientific Quarterly, Research on Applied Economic Studies in Iran, 2014, 3(9), P. 92-75.

Doi: 10.22048/JIR.2014.246129.1857.

 

  Hassanzadeh, A., and Kazemnejad, M., A Review of the Role of   the Insurance Industry in the Economy and Capital Market of Iran and Some Developing Countries Developed, Insurance Research Institute Publications, Insurance Industry Quarterly 2008. Doi: 10.22021/JIR.2008.246129.2416.

 

 Dehghani, A., and Sheikh Rezaei, N., National Risk Index on Commercial Insurance Demand (Case Study of Countries Mena), Journal of Economics and Business, Eighth Year, Issue Sixteen, Fall 2017, P.15-31.

 Doi: 10.22056/JIR.2017.246129.2714.

 

 Raghfar, H., Safarzadeh, I., and Ghafouri Boroujerdi, M., The Impact of Inflation on the Financial Wealth of Insurance Companies in Iran, Model Quarterly Economic Construction (Twelfth Year, No. 2 "Consecutive 42" Summer 2015, P. 47-23. Doi: 10.22017/JIR.2015.246129.2780.

 

 Suri, A., Econometrics (Advanced) Volumes I and II with the use of stata & views8, Seventh Edition (Volume 2) and Eighth (Volume 1) Tehran; Farhangology Publishing 2018.

 

Shahbazi, K., God-worship, R.B., And Ehterami, M., The relationship between the development of life and non-life insurance on economic growth in Iran, Boundary Test Approach, Insurance Research Journal, 2013, 28(3), P. 47-21. Doi: 10.22056/JIR.2013.246129.2729.

 

 Shahbazi, K., Saleki, J., Nonlinear effect of life and non-life insurance penetration on economic growth in Iran, Quarterly Economic Research (Sustainable Growth and Development), 18(4), Winter 2018, P. 63-21. Doi: 10.22084/JIR.2018.246129.2735.

 

Shahriar, B., Vahamdi, S. M. M., Calculation of the optimal reliance in insurance companies with a value-risk approach Economic, Spring 2008, 8-1(28), P. 243-223. Doi: 10.22041/JIR.2008.246129.2713.

 

 Safdarian, S., Yahyaabadi, A., Hertamani, A., Analysis of the relationship between employed population and life insurance demand in Iran (2009-2010), Scientific-Specialized Quarterly of Development Economics and Planning, First Year, Second Issue, 2012, P. 70-53. Doi: 10.22041/JIR.2012.246129.2591.

 

 Kadkhodai, H., Bank and Stock Insurance: Financial Development Triangle, 2001, Insurance Industry Quarterly 4, P.131-44. Doi: 10.22056/JIR.2001.246129.2178.

 

 Kendrick, Tom, Project Risk Identification and Management, Translated by Morteza Kashfian Reyhani, Tehran, Jihad Daneshgahi Publications 2009.

 

Lotfi, A. A., Study of the effect of macroeconomic variables on the insurance demand of individuals, 2016, Bimonthly Monetary Economics.

 

Mirzakhani, H., and Nouri, A., Identifying the most important factors to increase investment risk in Iran's industrial sector and providing solutionsIn order to get rid of their negative effects, Economic November and December 2013, 9,10. P.48-23. Doi: 10.22058/JIR.2013.246129.2748.

 

 Mirzaei, A., Hassani, M., and Noureddini, S., The effect of important insurance indicators on economic growth in OPEC member countries, Quarterly Insurance Industry, 2014, 1, P.22-1.

 Doi: 10.22016/JIR.2014.246129.2764.

 

 Mirzaei, H., Mirzakhani, A., The need and importance of monitoring the financial wealth of insurance companies in the conditions of liberalization. Insurance, 2000, 59(15), P.73-82. Doi: 10.22056/JIR.2000.246129.2167.

 

 Nobahar, E., Pourabadollah Kooj, M., and Bohloli, R., Study of the risk of skewness in the health insurance industry in Iran, Scientific Journal of Insurance Research, 2017, 35(3). Doi: 10.22056/JIR.2017.246129.2748.

 

 Feyen, E., Rodney, L., Rocha, R., What Drives the Development of the Insurance Secto? An Empiricial Analysis Based on a Panel of Developed and Countries.The World Bank Police Research Working paper.5572,2011. Doi: 10.22056/JIR.2011.246129.2717.

 

[20] Abbasian-Naghneh, S., Tehrani, R., Tamimi, M. The Effect of JCPOA on the Network Behavior Analysis of Tehran Stock Exchange Indexes. Advances in Mathematical Finance and Applications, 2021, 6(3), P. 465-477, Doi: 10.22034/amfa.2019.1873319.1258

[21] Zanjirdar, M. Overview of Portfolio Optimization Models. Advances in Mathematical Finance and Applications, 2020, 5(4), P. 419-435. Doi: 10.22034/amfa.2020.674941

[22] Zangenehmehr, P., Farajzadeh, A. On Solutions of Generalized Implicit Equilibrium Problems with Application in Game Theory. Advances in Mathematical Finance and Applications, 2022, 7(2), P. 391-404. Doi: 10.22034/amfa.2021.1935453.1617

[23] Izadikhah, M. Financial Assessment of Banks and Financial Institutes in Stock Exchange by Means of an Enhanced Two stage DEA Model. Advances in Mathematical Finance and Applications, 2021, 6(2), P. 207-232. Doi: 10.22034/amfa.2020.1910507.1491

[24] Izadikhah, M. DEA Approaches for Financial Evaluation - A Literature Review, Advances in Mathematical Finance and Applications, 2022, 7(1), P. 1-36, Doi: 10.22034/amfa.2021.1942092.1639

[25] Salehi, A., Mohammadi, S., Afshari, M., Impact of Institutional Ownership and Board Independence on the Relationship Between Excess Free Cash Flow and Earnings Management. Advances in Mathematical Finance and Applications, 2017, 2(3), P. 91-105. Doi: 10.22034/amfa.2017.533104

 

[26] Parsa, B., Sarraf, F., Financial Statement Comparability and the Expected Crash Risk of Stock Prices. Advances in Mathematical Finance and Applications, 2018, 3(3), P. 77-93. Doi: 10.22034/amfa.2018.544951

 

[27] Jokar, H., Shamsaddini, K., Daneshi, V., Investigating the Effect of Investors' Behavior and Management on the Stock Returns: Evidence from Iran. Advances in Mathematical Finance and Applications, 2018, 3(3), P. 41-52. Doi: 10.22034/amfa.2018.544948

 

[28] Rezaei, N., Elmi, Z., Behavioral Finance Models and Behavioral Biases in Stock Price Forecasting. Advances in Mathematical Finance and Applications, 2018, 3(4), P. 67-82. Doi: 10.22034/amfa.2019.576127.1118

 

[29] Agah, M., Malekpoor, H., Bagheri, A., Investigating the Effect of Financial Constraints and Different Levels of Agency Cost on Investment Efficiency. Advances in Mathematical Finance and Applications, 2017, 2(4), P. 31-47. Doi: 10.22034/amfa.2017.536264

 

[30] Karbasi Yazdi, H., Mohammadian, M., Effect of Profitability Indices on the Capital Structure of Listed Companies in Tehran Stock Exchange. Advances in Mathematical Finance and Applications, 2017, 2(3), P. 1-11. Doi: 10.22034/amfa.2017.533085

 

[31] Ahmadi, R., Kordloei, H., The Effect of Financial Distress on the Investment Behavior of Companies Listed on Tehran Stock Exchange. Advances in Mathematical Finance and Applications, 2018, 3(4), P. 17-28. Doi: 10.22034/amfa.2019.565459.1108