Requierements for Determining Technical Interest Rate in Iranian Life insurance Industry

Subject Areas : Journal of Investment Knowledge

Aziz  Ahmadzadeh ¹ (Ph.D. in Financial Economics, Assistant Professor-Insurance Research Center-Iran.)
Mojtaba  Abed ² (Ph.D. Candidate in Actuarial Science- Expert of Actuary in Central insurance of I.R. Iran.)

Received: 2021-01-02 Accepted : 2021-04-17 Published : 2024-03-20

Keywords: Technical interest rate, Life insurance, discount rate, financial supervision, Guaranteed interest rate,

Abstract :

Thus, the analysis of the roots of technical interest rates, types of models for determining technical interest rates and identification of variables that should be considered in determining it and how and quality of monitoring it, has been done using the documentary method to the governing frameworks. Then, based on the results, a questionnaire was designed to confirm and complete the framework and sent to relevant experts. The results of the study show that based on the reviewed studies, the use of time series models is the main method of determining the technical interest rate in insurance companies, but in some cases, structural models have also been used.But in Iran, the use of time series models for determination of technical interest rates are not mentioned by experts and the majority of experts support structural models that taking into account the economic variables including inflation, interest rates, exchange rates and gold respectively (in order of importance) to determine technical interest rates. In the field of supervision, although there are different patterns, but the use of interest rates on long-term bonds with the highest credit rating, has been the common denominator of all countries to determine the maximum technical interest rate. It seems that the high weighting of experts on the variables of inflation, exchange rate and gold in Iran is due to the sharp fluctuations in the value of the national currency, which is the outstanding difference between Iran and other countries under study. Finally,

References:

• احمدزاده, ع.، قنبرزاده، م.، علی‌محمدی، م.، حیدری، ح.، افشاری، س.، صیدی مرادی، ج.، ۱۳۹۷، انواع بیمه‌های زندگی و چالش‌های توسعه آن در ایران با رویکرد بیمه‌های زندگی غیرپس‌اندازی، پژوهشکده بیمه.


• اسلاملوییان, ک. و استادزاد, ع., 1393. برآورد نرخ رجحان زمانی در ایران با استفاده از الگوریتم بازگشتی. پژوهشات اقتصادی، شماره ۴۹، صفحه ۲۶۷-۲۹۴.


• پرومیسلو, ا. د., ۱۳۹۲. مبانی ریاضیات اکچوئرال. تهران: پژوهشکده بیمه.


• تقوی, م., ۱۳۷۷. مبانی علم اقتصاد. تهران: انتشارات صنایع ایران.


• دلالی اصفهانی, ر. و محمدی, ا., ۱۳۹۳. تعامل نرخ بهره پولی و رشد اقتصادی. معرفت اقتصاد اسلامی, ۶(۱), صفحه ۵-۲۸.


• کینز, ج. م., 1936. نظریه عمومی اشتغال، بهره و پول. ترجمه منوچهر فرهنگ؛ تهران: نشر نی.


• شیردل, ر., صادقی, ح., عصاری آرائی, ع. و عبدلی, ق., 1396. برآورد نرخ تنزیل اجتماعی ایران با رویکرد رجحان زمانی جامعه. بخشنامه سیاست‌های مالی و اقتصادی، شماره ۱۸، صفحه ۷-۲۴.


• عبدلی, ق., 1388. تخمین نرخ تنزیل اجتماعی برای ایران. پژوهشنامه اقتصادی، شماره ۳.


• میرآخور، ع.، عصمت پاشا، ع. 1394. بازارهای سرمایه اسلامی رویکرد مقایسه‌ای، ترجمه احمدزاده، ع.، عریانی، ب.و معظمی گودرزی، م. مؤسسه عالی آموزش بانکداری ایران.


• Ait-Sahalia, Y. (1996a). “Nonparametric Pricing of Interest Rate Derivative Securities”, Econometrica, vol. 64, No.3, 527-560.


• Ait-Sahalia, Y. (1996b). “Testing Continuous-Time Models of the Spot Interest Rate”, The Review of Financial Studies, Vol.9, No.2, 385-426.


• Berument H., N.D. Ceylan and H. Olgun 2007, “Inflation Uncertainty and Interest Rates: Is the Fisher Relation Universal?”, Applied Economics, Vol. 39, 53-68.


• Black, F. and Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities”, Journal of Political Economy, 81, 637-659.


• Bowers, N. L. et al., 1997. Actuarial Mathematics. USA: Society of Actuaries.


• Brace, A., Gatarek, D., and Musiela, M. (1997). The Market Model of Interest Rate Dynamics. Mathematical Finance, 7(2):127{155.


• Brennan, M. J. and Schwartz E. S. (1980). “Analyzing Convertible Bonds”, Journal of Financial and Quantitative Analysis 15: 907-929.


• Chan, K. C.س, Karolyi, A., Longstaff, F. A. and Sanders B. S. (1992). ”An Empirical Comparison of Alternative Models of Short-Term Interest Rate”, Journal of Finance, 47, 1209-1227


• .Charpentier, A., 2016. Computational Actuarial Science with R. Boca Raton, Florida: Chapman & Hall/CRC The R Series.


• Cherubini, U., Luciano, E. & Vecchiato, W., 2004. Copula Methods in Finance. New York: Wiley.


• Cox, J. R., Ingersoll, J. & Ross, S., 1985. A theory of the term structure of interest rates. Econometrica, Volume 53, pp. 385-407.


• Cox, J. and Ross, S. (1976). “The Valuation of Options for Alternative Stochastic Processes”, Journal of Financial Economics.


• Cox, J. C., Ingersoll, J. E. and Ross, S. A. (1985). “An Interemporal General Equilibrium Model of Asset Prices”, Econometrica, 53, 363-384.


• Cox, J. C., Ingersoll, J. E. and Ross, S. A. (1980). “An Analysis of Variable Rate Contracts”. Journal of Finance, 35, 389-403.


• Doll, D.C. (1990) “A Brief History of Universal Life”. Product Development News, Society of Actuaries, Issue 26, 8-9


• Dothan, L. (1978). “On the Term Structure of Interest Rates”, Journal of Financial Economics 6, 59-69.


• Duffie, D. & Kan, R., 1996. A yield-factor model of interest rates. Mathematical Finance, Volume 6, pp. 379-406.


• Eling, M., Holder, S. (2013). Maximum Technical Interest Rates in Life Insurance in Europe and the United States: An Overview and Comparison" ;Geneva Papers on Risk and Insurance - Issues and Practice 38(2) · April 2013.


• Engle, R. and Patton, A. (2001). “What good is a Volatility Model?” Quantivative Finance, Volume 1, 237-245.


• Engle, R. (1982). “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models”, Journal of Business & Economic Statistics, Vol. 20, No. 3, 339-350.


• Evans, C., and Marshall, D., (2001). “Economic determinants of the nominal treasury yield curve.” Working Paper, Federal Reserve Bank of Chicago.


• Fang, H., Fang, K. and Kotz, S. (2002). “The Meta-elliptical Distributions with Given Marginals”, Journal of Multivariate Analysis 82, 1-26.


• Fisher, I., 1930. The Theory of Interest. New York: The MacMillan Company.


• Lindstone, H. A., On Discounting the Future, Technological Forecasting and Social Change, 5, (1972), pp. 335-38.


• Merton, R. C. (1973). “Theory of rational option pricing”, Bell Journal of Economics and Management Science, 4 (1), 141-183.


• Payne J.E. and B.T. Ewing, 1997, “Evidence from Lesser Developed Countries on the Fisher Hypothesis: A Cointegration Analysis”, Applied Economics Letters, Vol. 4, 683-687.


• Wilkie, A.D. (1995) \More on a stochastic asset model for actuarial use (with discussion)," British Actuarial Journal 1, 777-964.


• Yakoubov, Y., Teeger, M., and Duval, D. (1999) \A stochastic investment model for asset and liability management," In Proceedings of the 30th International ASTIN Colloquium and 9th International AFIR Colloquium, August, 1999, J: 237-266.


• Vasicek, O., 1977. An equilibrium characterization of the term structure.Journal of Financial Economics, Volume 5, pp. 177-188.


• Willis Towers Watson (2018). 2018 valuation for interest rates and annuity.


• willistowerswatson.com . 2018/10


• Willis Towers Watson (2018). 2018 valuation for interest rates and annuity. willistowerswatson.com . 2018/10


• Willis Towers Watson (2017). 2017 valuation for interest rates and annuity. Avilable at: willistowerswatson.com . 2019/9