A Mathematical Method for Deriving the Relative Effect of Serviceability on Default Risk

Economy – Quantitative Finance – Risk Management

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

16 pages

Scientific paper

The writers propose a mathematical Method for deriving risk weights which describe how a borrower's income, relative to their debt service obligations (serviceability) affects the probability of default of the loan. The Method considers the borrower's income not simply as a known quantity at the time the loan is made, but as an uncertain quantity following a statistical distribution at some later point in the life of the loan. This allows a probability to be associated with an income level leading to default, so that the relative risk associated with different serviceability levels can be quantified. In a sense, the Method can be thought of as an extension of the Merton Model to quantities that fail to satisfy Merton's 'critical' assumptions relating to the efficient markets hypothesis. A set of numerical examples of risk weights derived using the Method suggest that serviceability may be under-represented as a risk factor in many mortgage credit risk models.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Mathematical Method for Deriving the Relative Effect of Serviceability on Default Risk does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Mathematical Method for Deriving the Relative Effect of Serviceability on Default Risk, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Mathematical Method for Deriving the Relative Effect of Serviceability on Default Risk will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-376652

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.