The Decline in Credit Quality of New-Issue Junk Bonds

1990 ◽  
Vol 46 (5) ◽  
pp. 53-62 ◽  
Author(s):  
Barrie A. Wigmore
Keyword(s):  
Junk Bonds ◽  
Credit Quality

scholarly journals A DYNAMIC MODEL OF CENTRAL COUNTERPARTY RISK

2018 ◽  
Vol 21 (08) ◽  
pp. 1850050
Author(s):  
TOMASZ R. BIELECKI ◽  
IGOR CIALENCO ◽  
SHIBI FENG
Keyword(s):  
Dynamic Model ◽  
Numerical Study ◽  
Risk Measures ◽  
Structure Model ◽  
Counterparty Risk ◽  
Dynamic Risk Measures ◽  
Credit Quality ◽  
Dynamic Risk ◽  
Risk Sensitive

We introduce a dynamic model of the default waterfall of derivatives central counterparties and propose a risk sensitive method for sizing the initial margin, and the default fund and its allocation among clearing members. Using a Markovian structure model of joint credit migrations, our evaluation of the default fund takes into account the joint credit quality of clearing members as they evolve over time. Another important aspect of the proposed methodology is the use of the time consistent dynamic risk measures for computation of the initial margin and the default fund. We carry out a comprehensive numerical study, where, in particular, we analyze the advantages of the proposed methodology and its comparison with the currently prevailing methods used in industry.

Macro Stress Testing of Indian Bank Groups

2017 ◽  
Vol 11 (4) ◽  
pp. 375-403
Author(s):  
Pami Dua ◽  
Hema Kapur
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Private Sector ◽  
Stress Testing ◽  
Inflation Rate ◽  
Output Growth ◽  
Foreign Banks ◽  
Credit Quality ◽  
The Impact

This study examines how various bank groups operating in India have fared macro stress events and conduct macro stress testing (MST) to trace the impact of certain macroeconomic stress scenarios on the credit quality of five Indian bank groups, that is, the State Bank of India (SBI) and its associates (SBGs), nationalised banks (NBs), old private sector banks (OPBs), new private sector banks (NPBs) and foreign banks (FBs), using panel data from 1997 to 2014. Credit quality is modelled as a function of both macroeconomic variables (output growth, interest rate, inflation rate and exchange rate) and idiosyncratic variables (profitability and size indicator of bank business activity). The model is estimated by employing a panel cointegration approach, and the impact of adverse scenarios on the estimated credit quality is computed. Empirical findings show that credit quality is pro-cyclical in nature and rises in the event of a slowdown in the economy. In general, the credit quality of Indian bank groups is found to be inversely and significantly related to the economy’s growth rate, inflation rate, exchange rate and profits of banks and positively and significantly related to the interest rate. Shock analysis also reveals that a downturn in the economy through certain adverse scenarios has a significant adverse impact on the credit quality. The shocks are quickly propagated across banks with substantial heterogeneities present in different bank groups. Thus, macroeconomic policy measures promoting growth with price stability are expected to impact credit quality positively. Further, measures at the bank level can improve credit quality by enhancing their profitability. JEL Classifications: C32, C58, E170, G21

scholarly journals A primer on counterparty valuation adjustments in South Africa

2014 ◽  
Vol 17 (5) ◽  
pp. 584-600
Author(s):  
Gary Wayne Van Vuuren ◽  
Ja'nel Esterhuysen
Keyword(s):  
South Africa ◽  
Financial Crisis ◽  
Credit Risk ◽  
South African ◽  
Credit Spreads ◽  
Basel Iii ◽  
Credit Quality ◽  
Counterparty Credit Risk ◽  
Market Variables

Counterparty valuation adjustment (CVA) risk accounts for losses due to the deterioration in credit quality of derivative counterparties with large credit spreads. Of the losses attributed to counterparty credit risk incurred during the financial crisis of 2008-9 were due to CVA risk; the remaining third were due to actual defaults. Regulatory authorities have acknowledged and included this risk in the new Basel III rules. The capital implications of CVA risk in the South African milieu are explored, as well as the sensitivity of CVA risk components to market variables. Proposed methodologies for calculating changes in CVA are found to be unstable and unreliable at high average spread levels.

Impact of Unfunded Pension Obligations on Credit Quality of State Governments

2013 ◽  
Vol 33 (3) ◽  
pp. 24-54 ◽  
Author(s):  
CHRISTINE R. MARTELL ◽  
SHARON N. KIOKO ◽  
TIMA MOLDOGAZIEV
Keyword(s):  
State Governments ◽  
Credit Quality

Financing environmentally-sustainable projects with green bonds

2019 ◽  
Vol 24 (6) ◽  
pp. 608-623 ◽  
Author(s):  
Elettra Agliardi ◽  
Rossella Agliardi
Keyword(s):  
Structural Model ◽  
Environmental Concern ◽  
Policy Implications ◽  
Environmentally Sustainable ◽  
Credit Quality ◽  
Bond Issuers ◽  
The Difference ◽  
Sustainable Investments ◽  
Sustainable Projects

AbstractA structural model for green bonds is developed to explain the formation and dynamics of green bond prices and to address the issue of the so-called ‘greenium’, that is, the difference between the yields on a conventional bond and a green bond with the same characteristics. We provide answers to the following questions: What are the determinants of the green bond value? Do green bonds enhance the credit quality of the issuer? Are green bonds a relatively cheap tool to fund sustainable investments? We also study the effect of investors' environmental concern on portfolio allocation. Our results have direct policy implications and suggest that an improvement in credit quality could ultimately lead to a lower cost of capital for green bond issuers and that governmental tax-based incentives and an increase in investors' green awareness play a significant role in scaling up the green bonds market.

scholarly journals Application of Credit Risk Scoring Methods in Corporate Borrower Monitoring

2021 ◽  
Vol 24 (4) ◽  
pp. 689-709
Author(s):  
Olga Andreevna Tazenkova
Keyword(s):  
Development Strategy ◽  
Predictive Ability ◽  
Initial Assessment ◽  
Scoring Methods ◽  
Periodic Review ◽  
Credit Quality ◽  
Credit Risks ◽  
Monitoring Process ◽  
Decision Making System

A method for assessing the risk of default of a corporate borrower at the monitoring stage based on a scoring assessment is proposed. This paper provides proof of the hypothesis that scoring methods for assessing credit risks can be used not only at the stage of initial assessment of a potential borrower when making a decision on lending, but also at the stage of its monitoring when accompanying a transaction. Monitoring is a periodic review of the credit quality of the corporate borrower with whom the loan agreement is concluded. This is done for the purpose of timely detection of negative signals, as well as timely response to threatening trends in the borrower's activities. Some credit institutions save on monitoring by relying on the decision-making system, considering it flawless. However, this saving can be a fatal mistake, since many things change over time during the "life" of the enterprise. This is facilitated by both external factors (political, economic) and internal (incorrect development strategy of the organization, inability to assess its own credit capabilities, unscrupulous counterparties). The proposed method is a system of automatic risk signals that have been tested for predictive ability, excluding manual procedures. The proposed solution includes markers (risk signals) that have a predictive ability above average, which can lead to a default of the corporate borrower. In addition, color marking is applied – red, yellow, green, which allows you to visualize the criticality of the identified risk signal depending on the predictive ability - a visual representation of the borrower's risks in order to facilitate interpretation. The analysis of the developed method showed how much it is possible to speed up the monitoring process, which will allow for a prompt response to the identified risk signals, as well as to predict the likely deterioration of the borrower's credit quality in the loan or guarantee portfolio without compromising the quality of risk assessment.

An Analysis of Debt and Equity Market Reaction to Pension Risk Transfer Announcements: What Investors Need to Know

2018 ◽  
Keyword(s):  
Pension Fund ◽  
Market Reaction ◽  
Equity Market ◽  
Risk Transfer ◽  
Credit Quality ◽  
Stock Market Reaction ◽  
Funded Status ◽  
The Impact ◽  
Gathering Data

The pension annuity buyout market continues to experience very strong growth, with record deal volumes being reported. Cantor, Hood, and Power (2017) document a large variation in stock market reaction to annuity buyout announcements. The fundamental question remains however: Does the equity market care about these transactions? In Cantor, Hood, and Power (2018), we hope to further understand the market’s view of pension annuity buyout transactions. We argue that the funded status of the pension fund and the motivation for the buyout could drive the market’s reaction. By expanding our sample and gathering data on funded status, we can test the market’s reaction based on the funded status of the plan prior to the announcement. In addition, we examine the credit market’s reaction to the buyouts. We argue that the equity and debt markets may have a different reaction to the news, conditional on the funded status and credit quality of the company. Our research has important implications for plan sponsors considering whether a pension annuity buyout is an effective transaction. Moreover, our research is relevant for investors who are trying to interpret the impact of these transactions on a company’s value.

Kazakh government realistic on oil and COVID-19 shocks

2020 ◽  
Keyword(s):  
Foreign Investment ◽  
Fiscal Consolidation ◽  
Content Type ◽  
Profit Margins ◽  
Credit Quality ◽  
The Government

Significance In response to the new macroeconomic realities, the government put on hold the fiscal consolidation plans it announced earlier and allocated 4.4 trillion tenge (10.1 billion dollars) to fight the spread of COVID-19 and its economic fallout. Impacts The COVID-19 crisis is a test for the new president; he has previously been somewhat overshadowed by his predecessor Nursultan Nazarbayev. The deteriorating credit quality of corporate and individual borrowers will raise levels of non-performing loans in the banks. A weak tenge will improve exporters' profit margins but could deter future foreign investment.

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