Pairing Market Risk and Credit Risk

2011 ◽  
Author(s):  
Isabel Figuerola-Ferretti ◽  
Ioannis G. Paraskevopoulos
Keyword(s):  
Author(s):  
Gleeson Simon

This chapter begins by discussing market risk in the Basel framework. Market risk was a relative latecomer to the Basel framework. Although the original Accord was signed in 1988, it was only in 1996 that the amendment to incorporate market risks was implemented. Market risk in the trading book is comprised of two significant components: position risk, which measures the risk of a change in the value of assets held; and counterparty credit risk, which measures the riskiness of counterparties to derivatives, options, and other trading positions. The remainder of the chapter covers trading book eligibility under Basel 2.5 and Basel 3.


2020 ◽  
Vol 1 (1) ◽  
pp. 88-107
Author(s):  
Gedion Alang’o Omwono ◽  
Kayumba Annette

The purpose of this study was to examine the relationship between risk management practices and investment decisions in Bank of Kigali, Rwanda. This study adopted correlational research design. Descriptive statistics include those of the mean, standard deviation and frequency distribution while inferential statistics involves use of spearman’s coefficient correlations. Linear regression was used where ANOVA was carried on each variable. The study found that there was a correlation between liquidity risk management, default risk management and market risk management with performance of the Banks. The study findings indicated that credit risk management (r=0.096, p<0.01), liquidity risk management (r=0.347, p<0.01), market risk management (r=0.506, p<0.01) and operational risk management (r=0.612, p<0.01) on financial performance. It however found that the Banks do not involve experts and consultants in market risk management thus recommendations were made for the Banks to revise their credit risk management policies, open up and share information with other players on market risk thus involve consultants more in their market risk management and to be more proactive than reactive in risk management. The study concluded that, risk management has a positive influence on the investment decisions and that risk monitoring can be used to make sure that risk management practices are in line with proper best practice risk monitoring policies which also helps bank management to discover exposures at early stages and make corrective actions. The study recommended that, Senior management should develop strategies, policies and practices to manage risk in accordance with the Banks risk tolerance and to ensure that the bank maintains sufficient liquidity risk cover.


2021 ◽  
Vol 6 (2) ◽  
pp. 150-157
Author(s):  
Rini Dwi Astuti ◽  
Dewa Putra Krishna Mahardika

The Covid-19 pandemic began to spread in Indonesia in March 2020. This caused a number of industrial sectors in Indonesia to experience a decrease in financial performance. One of the sectors that experienced a decline in financial performance was the banking sector. This study has purpose to determine the effect of credit risk and market risk on financial performance in commercial banks registered on the Indonesia Stock Exchange in the first until fourth quarters of 2020. The samples in this study is 35 banks. The sample is obtained by purposive sampling method. The method of analysis in this study is multiple linear regression analysis. From the results of the study, simultaneously credit risk and market risk affect financial performance. credit risk negatively affects financial performance. while market risk has a positive effect on financial performance


2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Adi Isa Ansori ◽  
Herizon Herizon

This study tried to determine the effect of liquidity risk measured by LDR and IPR, Credit risk measured by APB and NPL, market risk measured by IRR and PDN, operational risk measured by BOPO, and FBIR both simultaneously or partially. On Core CAR (TIER 1) in Bank group of book 3 and book 4. The sample was selected using purposive sampling technique, consisting of five banks such as PT Bank Negara Indonesia, PT Bank Maybank Indonesia, PT Bank Tabungan Negara, PT Pan Indonesia Bank, and PT Bank Permata. The secondary data were taken from published financial statements starting from first quarter 2010 until second quarter 2015. They were collected by documentation method and analyzed using linear analysis. The result shows that, partially, LDR, IPR, NPL, PDN, BOPO and FBIR have significant effect on Core CAR (TIER 1). Simultaneously, LDR, IPR, APB, NPL, IRR, PDN, BOPO, and FBIR, as represented by liquidity risk, credit risk, market risk, and operational risk partially have significant effect on Core CAR (TIER 1) in Bank group of book 3 and book 4.


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