This study aims to compare two distance-to-default methods, data-transformed maximum likelihood estimation and “naïve”, that are suitable for financial institutions. The links…
Abstract
Purpose
This study aims to compare two distance-to-default methods, data-transformed maximum likelihood estimation and “naïve”, that are suitable for financial institutions. The links between these measures and asset size, Tier 1 and Tier 2 capital ratios, non-performing assets and operating efficiency have been examined and an alternative default risk measure has been introduced. Most of the market-based distance-to-default measures are not appropriate for banks due to their unique debt structure.
Design/methodology/approach
The author has compared two distance-to-default measures and has identified their accounting determinants using Pearson’s correlation and regressions with clustered standard errors. The sample of the US-based systemically important financial institutions covers the period from 2000 to 2010.
Findings
Non-performing assets and operating efficiency are found to be statistically and economically significant determinants of both distance-to-default measures. Tier 1 capital ratio is not a significant indicator of default risk.
Practical implications
The results emphasize the importance of using a combination of market-based default risk measures and accounting ratios in default prediction models for the financial institutions.
Originality/value
This paper identifies accounting determinants of two distance-to-default measures for large financial institutions, before and during the 2008 financial crisis. It introduces a spread between two measures as an alternative default risk indicator.
Details
Keywords
The purpose of this study is to examine the impact of supervisory Leveraged Lending Guidance (LLG) (2013–2014) on risk and structure of syndicated loans arranged by the largest US…
Abstract
Purpose
The purpose of this study is to examine the impact of supervisory Leveraged Lending Guidance (LLG) (2013–2014) on risk and structure of syndicated loans arranged by the largest US banks with participation of nonbank lenders.
Design/methodology/approach
This study uses supervisory shared national credit loan-level data from 2010 to 2015 and DealScan loan origination data and use linear regressions with clustered standard errors.
Findings
This study finds that the impact of the LLG was mixed. Incidence and risk of leveraged lending declined following the Guidance, as reflected in lower nonbank syndicate participation. However, the covenant protections weakened and loan spreads at origination declined. This study also provides evidence that some risky lending originations shifted to nonbank entities outside of the banking regulatory environment.
Originality/value
This study contributes and expands literature on the impact of regulatory guidance on loan risk, terms and structure, focusing on nonbank participation in syndicated commercial loans.