scholarly journals Comparative analysis of the impact of variations in total assets of banks on HPR exposure to interest rate risk: Developed financial market vs. financial market of the Republic of Serbia

Skola biznisa ◽  
2013 ◽  
pp. 1-11
Author(s):  
Zeljko Racic
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.


2020 ◽  
Vol 115 ◽  
pp. 105797 ◽  
Author(s):  
Toni Beutler ◽  
Robert Bichsel ◽  
Adrian Bruhin ◽  
Jayson Danton

Author(s):  
Olga Mikhailovna Markova

In modern conditions of the rapid industrial development the banks have to forecast their risks and profitability precisely, to apply information technologies to assess their activities. To evaluate the bank's income, it is necessary to carry out an internal analysis of its assets and liabilities and determine the factors effecting the bank's profitability by managing interest rate risk. The hypothesis of the study is the analysis of the impact on the net interest income and interest rate risk of a commercial bank of factors such as the exchange rate and the key rate of the Bank of Russia (for example, Sberbank, PJSC). There has been studied the impact of the factors (exchange rate and key interest rate of Central Bank of Russia) on the bank's net interest income by using correlation and regression analysis and building a regression model. Many tools are found to be used by the experienced analysts. One of the main tools is GAP analysis of interest rate risk. There have been illustrated the graphs of changes in interest rates of savings and loan associations during the crisis in the United States in the 1950-1960, of realization of interest rate risk with an increase in interest rates, the distribution of assets and liabilities according to the maturity of the balance sheet structure, the impact of changes in the interest rate GAP on net interest income, etc. A matrix of correlations of all variables in the sample (rates of growing values) was constructed. Conclusions are drawn on the need to use hedging instruments (interest rate swaps, interest rate options), as well as of attracting the most reliable data on the state of interest rate risk in the commercial banks.


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.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jie Zhang ◽  
Zhiying Zhang ◽  
Yuehui Liu

The purpose of this study is to propose a methodology that reflects the impact of interest rate risk on firms in supply chain network under bank financing and trade credit and further describe how trade credit improves the impact of interest rate risk on supply chain network through a financial flow equilibrium. A mean-variance framework and a network equilibrium analysis are integrated to provide a modeling framework. The model allows for the investigation of how bank credit financing (BCF) and trade credit financing (TCF) affect the payment strategy and financial flow of interconnected firms in supply chain networks and how they are affected by interest rate risks. The optimal behavior of manufacturers and retailers is described through variational inequality. We construct a supply chain network equilibrium model and derive qualitative properties of the solution and the function that becomes assimilated to the variational inequality problem. Additionally, variational inequality is solved using the modified projection method. This study extends the research on the impact of interest rate risk on the decision in supply chain network of firms. While other studies focus on the game between banks and firms, only a few authors have made attempts to examine the game between one manufacturer and one retailer in supply chain. An effective trade credit strategy is obtained by balancing cash and credit transactions. Through the case study, we learn how to balance the capital flow effectively to improve the negative impact of interest rate risk on supply chain.


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