scholarly journals Pricing Corporate Bonds with Credit Risk, Liquidity Risk, and Their Correlation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinting Li ◽  
Baochen Yang ◽  
Yunpeng Su ◽  
Yunbi An
Keyword(s):  
Financial Crisis ◽  
Credit Risk ◽  
Liquidity Risk ◽  
Market Risk ◽  
Risk Tolerance ◽  
Corporate Bond ◽  
Bond Pricing ◽  
Pricing Model ◽  
Death Spiral ◽  
Trading Model

This paper proposes a generalized bond pricing model, accounting for all the effects of credit risk, liquidity risk, and their correlation. We use an informed trading model to specify the bond liquidity payoff and analyze the sources of liquidity risk. We show that liquidity risk arises from reduced information accuracy and market risk tolerance, and it is market risk tolerance that links credit and liquidity. Then, we extend the traditional bond pricing model with only credit risk by incorporating liquidity risk into the framework in which the probabilities of the two risk events are estimated by a joint distribution. Using numerical examples, we analyze the role of the correlation between credit and liquidity in bond pricing, especially during a financial crisis. We document that the varying correlation between default and illiquidity explains the phenomenon of bond death spiral observed in a financial crisis. Finally, we take the US corporate bond market as an example to demonstrate our conclusions.

scholarly journals Relationship Between Risk Management Practices and Investment Decisions in Bank of Kigali, Rwanda

2020 ◽  
Vol 1 (1) ◽  
pp. 88-107
Author(s):  
Gedion Alang’o Omwono ◽  
Kayumba Annette
Keyword(s):  
Risk Management ◽  
Credit Risk ◽  
Best Practice ◽  
Management Practices ◽  
Investment Decisions ◽  
Liquidity Risk ◽  
Market Risk ◽  
Risk Tolerance ◽  
Credit Risk Management ◽  
Risk Monitoring

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.

scholarly journals On a New Corporate Bond Pricing Model with Potential Credit Rating Change and Stochastic Interest Rate

2018 ◽  
Vol 11 (4) ◽  
pp. 87 ◽  
Author(s):  
Hong-Ming Yin ◽  
Jin Liang ◽  
Yuan Wu
Keyword(s):  
Interest Rate ◽  
Credit Rating ◽  
Corporate Bond ◽  
Bond Pricing ◽  
Stochastic Interest Rate ◽  
Pricing Model ◽  
New Model ◽  
Stochastic Interest ◽  
The Interest Rate ◽  
Rating Change

In this paper, we consider a new corporate bond-pricing model with credit-rating migration risks and a stochastic interest rate. In the new model, the criterion for rating change is based on a predetermined ratio of the corporation’s total asset and debt. Moreover, the rating changes are allowed to happen a finite number of times during the life-span of the bond. The volatility of a corporate bond price may have a jump when a credit rating for the bond is changed. Moreover, the volatility of the bond is also assumed to depend on the interest rate. This new model improves the previous existing bond models in which the rating change is only allowed to occur once with an interest-dependent volatility or multi-ratings with constant interest rate. By using a Feynman-Kac formula, we obtain a free boundary problem. Global existence and uniqueness are established when the interest rate follows a Vasicek’s stochastic process. Calibration of the model parameters and some numerical calculations are shown.

scholarly journals Pricing Convertible Bonds with Credit Risk under Regime Switching and Numerical Solutions

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Wei-Guo Zhang ◽  
Ping-Kang Liao
Keyword(s):  
Credit Risk ◽  
Regime Switching ◽  
Numerical Solutions ◽  
Dilution Effect ◽  
Convertible Bonds ◽  
Bond Pricing ◽  
Convertible Bond ◽  
Pricing Model ◽  
Black Scholes ◽  
The Impact

This paper discusses the convertible bonds pricing problem with regime switching and credit risk in the convertible bond market. We derive a Black-Scholes-type partial differential equation of convertible bonds and propose a convertible bond pricing model with boundary conditions. We explore the impact of dilution effect and debt leverage on the value of the convertible bond and also give an adjustment method. Furthermore, we present two numerical solutions for the convertible bond pricing model and prove their consistency. Finally, the pricing results by comparing the finite difference method with the trinomial tree show that the strength of the effect of regime switching on the convertible bond depends on the generator matrix or the regime switching strength.

Empirically Effective Bond Pricing Model and Analysis on Term Structures of Implied Interest Rates in Financial Crisis

2011 ◽  
Vol 19 (3) ◽  
pp. 259-292 ◽  
Author(s):  
Takeaki Kariya ◽  
Jingsui Wang ◽  
Zhu Wang ◽  
Eiichi Doi ◽  
Yoshiro Yamamura
Keyword(s):  
Financial Crisis ◽  
Interest Rates ◽  
Bond Pricing ◽  
Pricing Model ◽  
Term Structures

Corporate bond pricing model with stochastically volatile firm value process

2016 ◽  
Vol 148 ◽  
pp. 41-44
Author(s):  
Woon Wook Jang ◽  
Young Ho Eom ◽  
Yong Joo Kang
Keyword(s):  
Firm Value ◽  
Corporate Bond ◽  
Bond Pricing ◽  
Pricing Model

scholarly journals Pengaruh risiko usaha terhadap rasio kecukupan modal inti (TIER 1) pada bank-bank kelompok buku 3 dan buku 4

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Adi Isa Ansori ◽  
Herizon Herizon
Keyword(s):  
Credit Risk ◽  
Liquidity Risk ◽  
Secondary Data ◽  
Operational Risk ◽  
Sampling Technique ◽  
Financial Statements ◽  
Market Risk ◽  
Linear Analysis ◽  
Tier 1 ◽  
Bank Group

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.

scholarly journals Bank liquidity risk management: A South African survey to determine future change

2012 ◽  
Vol 2 (3) ◽  
pp. 33-53 ◽  
Author(s):  
Stephan Claassen ◽  
J.H. Van Rooyen
Keyword(s):  
Risk Management ◽  
Financial Crisis ◽  
South African ◽  
Banking System ◽  
Liquidity Risk ◽  
Risk Tolerance ◽  
Management Tools ◽  
Global Context ◽  
Global Banking ◽  
Global Financial System

In 2008 the global financial system and, more particularly, the world banking system suffered a financial crisis worse than any earlier crises. The financial crunch brought to light that liquidity risk management in banks poses a problem, and that the world’s financial institutions will have to change their current practices as it relates to this risk. Apart from the importance of liquidity and the risk that it may cause, the integrated nature of all risks made banks more aware of the fact that none of these risks can be managed in isolation. For various reasons, South African banks were not as exposed to the problems experienced in the global context. However, SA banks may have learned new lessons from the crisis and may plan to change the way they manage liquidity risk in particular, in the future. In order to determine how SA banks perceive liquidity management and liquidity risk, a survey of all SA banks was carried out. The majority of respondents indicated that the financial crisis reminded them of the importance of liquidity risk management in the South African banking system as well as the global banking system. The majority of banks rate all the liquidity risk management tools as extremely important and rate corporate governance, strategy, policy and risk tolerance, liquidity risk measurement and intra-day liquidity as their number one priority. Basel III is generally perceived as being effective, but 30% of respondents perceived it as neither effective nor ineffective, because South African banks already have similar measures in place.

Corporate governance in relationship with bank risk management

2021 ◽  
pp. 2150034
Author(s):  
Ika Permatasari
Keyword(s):  
Risk Management ◽  
Corporate Governance ◽  
Credit Risk ◽  
Liquidity Risk ◽  
Market Risk ◽  
Data Sources ◽  
Annual Reports ◽  
Bank Risk ◽  
Financial Reports ◽  
The Relationship

The purpose of this research is to examine the relationship between corporate governance and risk management of Indonesian banks. Bank risk managements are measured by market risk, credit risk, and liquidity risk. The samples used in this study were all banks registered in Indonesia during the 2010–2016 period. The data sources were obtained from the annual reports and bank financial reports. The results show that corporate governance implementation in Indonesia was able to affect credit risk and liquidity risk. There were differences in credit risk and liquidity risk in banks with different governance ratings, but not at market risk.

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