Providing an operational technique for hedging interest rate risk with debt issues in Iran

Document Type : Original Article


1 PhD. Student in Financial Engineering, Department of Financial Management, Faculty of Management and Economy, Science and Research Branch, Islamic Azad University, Tehran-Iran.

2 Prof., Department of Financial Management, Faculty of Management and Economy, Science and Research Branch, Islamic Azad University, Tehran-Iran.

3 Assistant Prof., Department of Financial Management, Tehran North Branch, Islamic Azad University, Tehran-Iran,

4 Assistant Prof. Department of Financial Management, Electronic Campus, Islamic Azad University Tehran-Iran.

5 Associate Prof., Department of Economics, Faculty of Management and Economy, Science and Research Branch, Islamic Azad University, Tehran-Iran.



Interest rate risk is one of the most important financial risks that economic enterprises faced. This risk is actually the probability of a decline in the value from unexpected fluctuations in interest rates in the market. Firms use different analytical models to evaluate the interest rate assessment and the effect of interest rate fluctuations on liabilities and assets and their cash flows. One of the risk hedging strategies is risk management using operational techniques.
In this research, with the aim of proposing an operational technique for hedging interest rate risk, the sensitivity coefficient of firms' stock returns to interest rate fluctuations in the period of 2011 to 2021 and after entering the debt market has been investigated and analyzed. In order to measure the interest rate sensitivity coefficient, a model similar to the model of Flannery and James (1984) and Deleze and Korkeamaki (2018) has been used. In this research, the autoregressive integrated moving average (ARIMA)model has been used to estimate the unexpected part of changes in interest rates, and the rolling window regression and panel data models have been used to estimate the interest rate sensitivity coefficient and analyze and investigate this sensitivity coefficient. The result of the research shows a decrease in the sensitivity coefficient to interest rate changes after the first entry into the debt market and finally the facilitation of interest rate risk management among debt bond issuers.


  • Ahmadi, M and Torghi, S (2016), Evaluation of the relationship between interest rate changes and stock returns in companies listed on the Tehran Stock Exchange, International Conference on New Developments in Management, Economics and Accounting.
  • Akhtaruzzaman, M., Shamsuddin, A., & Easton, S. (2014). Dynamic correlation analysis of spill-over effects of interest rate risk and return on Australian and US financial firms. International Financial Markets and institutions and Money, 31(C), 378-396.
  • Asiyabi Aghdam L, Rahimzadeh A and Rajaei Y, The effect of economic variables on the behavior of stock prices of companies admitted to the stock exchange" Financial Economics Quarterly, Shahrivar 1401, pages 105-126.
  • Asadpour, N (2016), Risk Management System in Banks (Part I), Bank and Economy Monthly, No. 83, Pages 48-51
  • Atanasov, V. (2016). Conditional interest rate risk and the cross-section of excess stock returns. Review of Financial Economics, 30 (C), 23-32
  • Bats,J., & Houben,A. (2017) Bank-based versus market-based financing: Implications for systemic risk. DeNederlandsche Bank,577.
  • Bozorg Asl, M and Razavi, M (2007), The relationship between the returns of companies admitted to the stock market and some macroeconomic variables, scientific research quarterly of financial accounting empirical studies, number 22, Pages 118-97
  • Bhardwaj, G., & Swanson, N, R. (2006). An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series. Journal of Econometrics, 131(1-2), 539-578
  • Bolton, P., Freixas, X. (2000). Equity, bonds, and bank debt: capital structure and financial market equilibrium under asymmetric information Political Economy,108 (2), 324–351
  • Covitz, D., & Sharpe, S.A. (2005). Do Nonfinancial Firms Use Interest Rate Derivatives to Hedge?. Finance and Economics Discussion Series No. 2005-39. The Federal Reserve Board, Washington, D.C.
  • Deleze, F., & Korkeamaki, T.(2018). Interest rate risk management with debt issues: Evidence from Europe. Journal of Financial Stability, 36, 1-11.
  • Dhanani,A., Fifield, , Helliar, C., & Stevenson ,L. (2008). The management of interest rate risk: evidence from UK companies. Applied Accounting Research,9 (1), 52-70
  • Diamond, D. (1991). Monitoring and reputation: the choice between bank loans and privately placed debt. Political Economy,99, 689–721.
  • Entrop, O., Hausse, L., & Wilkens, M. (2017). Looking beyond banks’ average interest rate risk: Determinants of high exposures .The Quarterly Review of Economics and Finance, 63(C), 204-218.
  • Faulkender, M. (2005). Hedging or market timing? Selecting the interest rate exposure of corporate debt. J. Finance 60, 931–962
  • Flannery, M.J.,& James, C.M. (1984). The effect of interest rate changes on the common stock returns of financial institutions. J. Finance 39, 1141–1153
  • Froot A., Scharfstein D. S.,& Stein J. C.(1994). A Framework for Risk Management. Journal of Applied Corporate Finance,63 (3),22-33
  • Graham, J.R.,& Harvey, C.R.(2001). he theory and practice of corporate finance: evidence from the field. J. Financial Econ,60,187-243
  • Guay, W., & Kothari, S.P.(2003). How much do firms hedge with derivatives?. J. Financial Econ, 70, 423–461
  • Korkeamaki, T.(2011). Interest rate sensitivity of the European stock markets before and after the euro introduction. J. Int. Financial Mark. Inst. Money, 21, 811–831.
  • Mallik ,A.,& Mishra,A.(2019). Interest rate forecasting and stress testing in India: a PCA-ARIMA approach. Palgrave Communications, Palgrave Macmillan,5(1),1-17.
  • Man, K.S.(2003). Long memory time series and short-term forecasts. International Journal of Forecasting,19(3), 477-491.
  • MeulBrock,L.K.(2002). A Senior Manager’s Guide to Integrated Risk Management. Journal of Applied Corporate Finance,14(4),56-70
  • Modigliani,F.,& Miller,M .(1958). The Cost of Capital, Corporation Finance and the Theory of Investment. The American Economic Review,48, 261-297
  • Ngalawa, J.,& Ngare, Ph.(2014). Interest Rate Risk Management for Commercial Banks in Kenya. Journal of Economics and Finance,4(1),11-21
  • Oberoi, J.(2017). Interest rate risk management and the mix of fixed and floating rate debt. Journal of Banking and Finance,86(C),70-86
  • Pana, J., & Xiao, Q.(2017). Optimal dynamic asset-liability management with stochastic interest rates and inflation risks. Chaos, Solitons and Fractals,103,460-469.
  • Qayyumzadeh, M and Rahimi Bafqi, H (2017), Investigating the relationship between interest rate risk management and the combination of fixed and floating debt, a case study: companies listed on the Tehran Stock Exchange, the first national conference on management, economics and resistance economics.
  • Rajan, R., &Zingales, L.(2003). "Banks and Markets: The Changing Character of European Finance, NBER Working Papers 9595. National Bureau of Economic Research, Inc.
  • Saunders, A.,& Yourougou, P.(1990). Are banks special? The separation of banking from commerce and interest rate risk. J. Econ. Bus, 42, 171–182.
  • Smith, C. W. & Stulz, R. M. (1985) .The Determinants of Firms' Hedging Policies, J. Financ. Quant. Anal. 20(4), 391–405.
  • Sowell, F.(1992). Maximum Likelihood Test of Stationary Univariate Fractionally Integrated Time Series Models. Journal of Econometrics,53(1),165-188.
  • Stone, B.K.(1974). Systematic interest rate risk in a two-index model of returns. J. Financial Quant. Anal, 9, 709–721.
  • Sweeting ,P. (2011). Financial Enterprise Risk Management. New York: Cambridge University Press