Factors Affecting Recovery Rates
It is practically impossible to accurately predict the recovery rates. There are various factors that will affect the recovery rates of a defaulted loan:
- Collateral: The higher the value of collateral, the higher will be the recovery rate, as the sale of collateral will be able to payoff more creditors.
- Priority class of the claim: The recovery rates are affected by the priority class of the claim. This is because most bankruptcy procedures settle the claims based on the seniority of the class. The highest recovery rates are observed in the senior secured class and the lowest rates are observed in the junior subordinated debt.
- The bankruptcy procedure used: The backruptcy procedure will also affect the recovery rates. The UK bankruptcy procedures tend to be more favourable towards creditors, while the procedures in USA and France are more friendly towards the obligor. Accordingly, the UK will observe higher recovery rates compared to US and France.
Other Empirical Factors
There are other less observed factors that affect the recovery rates:
- Industry: The types of industry will affect the recovery rates. For example, financial institutions tend of have higher recovery rates than other industries. The more capital intensive the business is, the higher will be the recovery rates.
- The obligor’s rating prior to default: If the obligor was having a poor rating prior to default, then the recovery rates will be less because he may have very few assets to liquidate.
- Business cycle & average rating in the industry: When the economy is in recession, the recoveries will be low. Similarly, when the business is in the downswing of it’s business cycle, the recoveries will be low.
Given all the factors and the uncertainty of recovery rates, banks must be careful about the model they adopt for determining recovery rates.
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $29 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.