Banks’ Risk Dynamics and Distance to Default

2019 ◽  
Vol 33 (6) ◽  
pp. 2421-2467 ◽  
Author(s):  
Stefan Nagel ◽  
Amiyatosh Purnanandam
Keyword(s):  
Default Risk ◽  
Structural Models ◽  
Return Volatility ◽  
Usual Assumption ◽  
Asset Volatility ◽  
Risk Dynamics ◽  
Asset Values ◽  
Distance To Default ◽  
Bank Equity ◽  
Risky Debt

Abstract We adapt structural models of default risk to take into account the special nature of bank assets. The usual assumption of lognormally distributed asset values is not appropriate for banks. Typical bank assets are risky debt claims with concave payoffs. Because of the payoff nonlinearity, bank asset volatility rises following negative shocks to borrower asset values. As a result, standard structural models with constant asset volatility can severely understate banks’ default risk in good times when asset values are high. Additionally, bank equity return volatility is much more sensitive to negative shocks to asset values than in standard structural models.

Debt Maturity and Asymmetric Information: Evidence from Default Risk Changes

2013 ◽  
Vol 48 (3) ◽  
pp. 789-817 ◽  
Author(s):  
Vidhan K. Goyal ◽  
Wei Wang
Keyword(s):  
Asymmetric Information ◽  
Private Information ◽  
Default Risk ◽  
Important Determinant ◽  
Debt Maturity ◽  
Short Term ◽  
Information Models ◽  
Asset Volatility ◽  
Distance To Default

AbstractAsymmetric information models suggest that a borrower’s choice of debt maturity depends on its private information about its default probabilities, that is, borrowers with favorable information prefer short-term debt while those with unfavorable information prefer long-term debt. We test this implication by tracing the evolution of debt issuers’ default risk following debt issuances. We find that short-term debt issuance leads to a decline inborrowers’ asset volatility and an increase in their distance to default. The opposite is true for long-term debt issues. The results suggest that borrowers’ private information about their default risk is an important determinant of their debt maturity choices.

Executive pensions, compensation leverage, and firm risk

2018 ◽  
Vol 14 (3) ◽  
pp. 342-361 ◽  
Author(s):  
Reilly White
Keyword(s):  
Executive Compensation ◽  
Default Risk ◽  
Risk Shifting ◽  
Firm Risk ◽  
Content Type ◽  
Inside Debt ◽  
Risk Dynamics ◽  
Data Points ◽  
Significant Extension ◽  
Distance To Default

Purpose The purpose of this paper is to investigate how the structure of both CEO and non-CEO executive compensation affects the overall risk of a firm. The author focuses on the interplay between CEO and non-CEO executive compensation structure. Design/methodology/approach The author uses a hand-collected pension-database that employs both OLS and two-stage least squares regressions to determine the effects of inside debt on default risk using the distance-to-default framework. The database consists of 8,965 executive-year data points from 272 firms. Findings This paper accomplishes three major objectives: first, the author presents a significant extension of Sundaram and Yermack (2007) by including non-CEO executives; the author demonstrates how the differences in inside debt between CEO and non-CEO executives are directly related to firm risk; and that funding these pensions via a Rabbi Trust eliminates most of the risk-shifting effects. Firms with the lowest compensation leverage gap between CEO and non-CEO executives were most likely to observe the agency costs associated with high executive leverage. When compensation leverage structures were substantially different, or the pension was pre-funded, these effects are neutralized. Originality/value To the best of the author’s knowledge, the first paper addresses the effects of Rabbi Trusts on risk-shifting behavior between both CEOs and non-CEO executives. Further, the author extends Sundaram and Yermack (2007) using a hand-collected database six times larger than the original paper. By focusing on the “leverage gap” between CEOs and non-CEO executives, the author presents unique evidence that underlines the risk dynamics between CEOs and their boards.

scholarly journals Can Structural Models Price Default Risk? Evidence from Bond and Credit Derivative Markets

2015 ◽  
Vol 05 (03) ◽  
pp. 1550007 ◽  
Author(s):  
Jan Ericsson ◽  
Joel Reneby ◽  
Hao Wang
Keyword(s):  
Default Risk ◽  
Structural Models ◽  
Credit Default Swap ◽  
Corporate Bond ◽  
Credit Default ◽  
Credit Derivative ◽  
Risk Free Rate ◽  
Derivative Markets ◽  
Bond Spreads ◽  
Free Rate

Using a set of structural models, we evaluate the price of default protection for a sample of US corporations. In contrast to previous evidence from corporate bond data, credit default swap (CDS) premia are not systematically underestimated. In fact, one of our studied models has little difficulty on average in predicting their level. For robustness, we perform the same exercise for bond spreads by the same issuers on the same trading date. As expected, bond spreads relative to the treasury curve are systematically underestimated. This is not the case when the swap curve is used as a benchmark, suggesting that previously documented underestimation results may be sensitive to the choice of risk-free rate.

scholarly journals THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018

2021 ◽  
Vol 22 (4) ◽  
Author(s):  
VANDERSON A. DELAPEDRA-SILVA
Keyword(s):  
North American ◽  
Default Risk ◽  
Oil And Gas ◽  
Probability Of Default ◽  
Bankruptcy Risk ◽  
The North ◽  
North American Market ◽  
Structural Variables ◽  
Variable Distance ◽  
Distance To Default

ABSTRACT Purpose: This research aims to identify the probability of default of infrastructure companies considering the sector specificities of their activities. In addition, the work seeks to identify the application of structural variables of probability of default in a model in a reduced way in order to identify the significance of its use. For this purpose, we investigated 1,520 North American companies from six different sectors linked to infrastructure. Originality/value: The analyzes carried out to identify the probability of a company going bankrupt hardly consider its sectorial particularity. Although most models bring important inputs for risk assessment, most of them do not consider this sectoral view. Then, this work has as value and originality the contribution to fill this gap and identify the existence of sectorial differences in the analysis of default risk in infrastructure companies in the North American market in the period between 2006 and 2018. Design/methodology/approach: The study performed a logistic regression (logit model) using 11 model variables established in calculating the probability of default. It also used the variable distance to default as an explanatory variable in order to identify its ability to explain the researched phenomenon. Findings: The study identified that, in addition to the size of the companies, the distance to default variable is the only variable that can be applied with significance in all the analyzed sectors. In addition, it was identified that companies in the oil and gas sector have less sensitivity to this variable than companies in the other sectors.

scholarly journals France

2019 ◽  
Vol 19 (263) ◽  
Author(s):  
Keyword(s):  
Default Risk ◽  
Quantitative Method ◽  
Structural Model ◽  
Macroprudential Policy ◽  
Policy Makers ◽  
Actual Performance ◽  
Macroeconomic Variables ◽  
Financial Variables ◽  
Risk Dynamics ◽  
Policy Setting

Macroprudential policy setting faces the challenge of identifying growth of financial and macroeconomic variables above and below potential. The gaps between actual performance and potential are crucial for policy makers but are unobserved. This is especially true for financial variables such as capital and risk of default of borrowers (firms and banks) and lenders (banks and households). Against this backdrop, a macrofinancial structural model is presented that captures (i) sectoral dynamics of firms and banks and feedbacks between them, (ii) capital and default risk dynamics of each sector, (iii) capital and risk gaps i.e., deviations of capital and default risk from potential (the welfare maximizing optimum), and it provides (iv) a quantitative method for measurement.

scholarly journals Impact of Credit Risk on Momentum and Contrarian Strategies: Evidence from South Asian Markets

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 37 ◽  
Author(s):  
Ahmed Imran Hunjra ◽  
Tahar Tayachi ◽  
Rashid Mehmood ◽  
Sidra Malik ◽  
Zoya Malik
Keyword(s):  
Credit Risk ◽  
South Asian ◽  
Default Risk ◽  
Low Risk ◽  
Contrarian Strategies ◽  
Kmv Model ◽  
Distance To Default

We examine the profitability of the momentum and contrarian strategies in three South Asian markets, i.e., Bangladesh, India, and Pakistan. We also analyze, whether credit risk influences momentum and contrarian return for these markets from 2008 to 2014. We use default risk that relates to non-payments of debts by firms as a measure of credit risk. For that purpose, we use distance to default (DD) by Kealhofer, McQuown, and Vasicek (KMV) model as a proxy of credit risk. We calculate the credit risk and form the momentum and contrarian strategies of the firms based on high, medium, and low risk. We find that in all three markets, the momentum and contrarian returns are significant for medium and high credit risk portfolios and no momentum and contrarian returns for low credit risk portfolios.

Bank Risk Dynamics Where Assets are Risky Debt Claims

2016 ◽  
Vol 23 (1) ◽  
pp. 3-31 ◽  
Author(s):  
Sharon Peleg-Lazar ◽  
Alon Raviv
Keyword(s):  
Bank Risk ◽  
Risk Dynamics ◽  
Risky Debt
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