scholarly journals A modelling process of short-term interest rate risk management for the South African commercial banking sector

2011 ◽  
Vol 9 (1) ◽  
pp. 628-637
Author(s):  
Jiaqi Sun ◽  
J.H. Van Rooyen

This study focuses on banking book interest rate risk (IRR) management, more specifically short-term IRR management (SIRR). This type of risk is partly induced by the inflation targeting policy of the South African Reserve Bank (SARB). As a result, inflation leads to an uncertain interest rate cycle and a period of uncertain interest rate levels as it relates to lending and borrowing activities in the South African commercial banking sector. This study highlights what causes short-term interest rate risk and how the banks may forecast and manage the SIRR with reference to the inflation targeting policy. The banking industry manages a high volume of fund transactions and portfolios of investments. The banks are intricately involved in the financial markets and are therefore exposed to a large number of risk factors. A sound banking system is an important prerequisite for a country’s future economic development. One key empirical finding of this research is that 50 per cent of the South African banks agree that loans that cannot undergo immediate rate adjustments are exposed to the repo-rate adjustment after the Monetary Policy Committee (MPC) meeting. Banks surveyed see the need for the development of a short-term interest rate risk (SIRR) management process to better control such repo-rate risk. The next key empirical finding is that interest rate risk is still managed via traditional repricing gap and sensitivity analysis which is not ideal for risk management due to inherent weaknesses (such as not quantifying capital risk exposure). This agrees with the Pricewaterhousecoopers Balance Sheet Management benchmark survey

2018 ◽  
Vol 32 (8) ◽  
pp. 2921-2954 ◽  
Author(s):  
Peter Hoffmann ◽  
Sam Langfield ◽  
Federico Pierobon ◽  
Guillaume Vuillemey

Abstract We study the allocation of interest rate risk within the European banking sector using novel data. Banks’ exposure to interest rate risk is small on aggregate, but heterogeneous in the cross-section. Contrary to conventional wisdom, net worth is increasing in interest rates for approximately half of the institutions in our sample. Cross-sectional variation in banks’ exposures is driven by cross-country differences in loan-rate fixation conventions for mortgages. Banks use derivatives to partially hedge on-balance-sheet exposures. Residual exposures imply that changes in interest rates have redistributive effects within the banking sector. Received October 31, 2017; editorial decision August 30, 2018 by Editor Philip Strahan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.


2017 ◽  
Vol 9 (9) ◽  
pp. 102
Author(s):  
Mohammad Abdel Mohsen Al-Afeef ◽  
Atallah Hassan Al-Ta'ani

Banking sector is one of the most important sectors that support the sustainable economic development in Jordan, therefore this study aimed to test the impact of risks; (Liquidity risk, bank credit risk and interest rate risk) on the safety in the banking sector in the Jordanian commercial banks during the period 2005-2016.The results of the study showed that there is a statistically significant impact for each of liquidity risk and interest rate risk on the safety in the banking sector, and there isn't statistically significant impact for credit risk on the safety in the banking sector during the period of this study, and also find that the explanatory of model was 60.5%, which means that 39.5% due to other factors.


2019 ◽  
Vol 1 (01) ◽  
pp. 57-68
Author(s):  
Constance Henryette Adriana ◽  
Muria Kartika Perdana

The banking sector is the industry most regulated by the government has given the importance of this sector in the country's economy as a bridge for financing the real sector. Stocks in the banking industry are one of the stocks that are highly sought after by investors. Banks that have good health will attract many investors. The purpose of this study is to prove the influence of the bank's health level – risk profile and good corporate governance – on stock price in the banking sector companies on the IDX. The data used in this study are secondary data in the form of financial statements of banking companies. The independent variables in this study are risk profile and GCG, which consist of Non Performing Loans (NPL), Interest Rate Risk (IRR), Loan to Deposit Ratio (LDR), Managerial Ownership, Institutional Ownership, Independent Commissioner, Size of Board of Directors, Committee Audit and dependent variable Share Price. The sampling method in this study was purposive sampling with a sample of 7 banking companies registered on the Indonesia Stock Exchange. Stock price are the closing price on Yahoo Finance. The data analysis technique used is parametric statistical test – multiple linear regression analysis and classical assumption test, including normality test, autocorrelation test, multicollinearity test, and heteroscedasticity test. Test of hypothesis used the R Square test, partial t-test, and F test. The results of the study prove that the Non-Performing Loan (NPL), Independent Commissioner, and Audit Committee variables have no influence on the Stock Price. However, the Interest Rate Risk (IRR), Loan to Deposit Ratio (LDR), Managerial Ownership, Institutional Ownership, and the Size of the Board of Directors have an effect on Stock price.  Keywords: Non-Performing Loan (NPL), Interest Rate Risk (IRR), Loan to Deposit Ratio (LDR), Managerial Ownership, Institutional Ownership, Independent Commissioner, The size of the Board of Directors, the Audit Committee, and stock price.


2021 ◽  
pp. 097215092110394
Author(s):  
Soundariya G. ◽  
Treesa Aleena David ◽  
Suresh G.

This analytical study looks to provide recommendations to the banking sector on different policies and regulations by examining certain aspects of the Basel III accord, which was designed to manage specific operational, capital and market risks of banks. A review of extant literature reveals that only a few papers have been written on simulation-based approaches, using basis and re-pricing risks. We look to connect this as a source while attempting to define and measure the impact of interest rate risk (IRR) on the economic value of equity (EVE) of banks. We propose to use the driver—driven method, wherein interest rate shocks are derived through prime lending rate (PLR) for the period of 2016–2019 in the context of India. Monte Carlo Simulation and OLS regression was performed to predict the IRR; Granger causality was used to examine the cause and effect relationship; the impulse response function (IRF) was used for sensitivity analysis; and the vector error correction model (VECM) technique was used for co-integrating relationships. Notably, the EVE movement caused due to shocks in interest rates had to be traced as it envisages probable EVE losses. Importantly, our study is among the first few to show the relationship between IRR and EVE of banks, especially after the deregulation of Indian banking sector.


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