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Financial Simulation Modeling in Excel
book

Financial Simulation Modeling in Excel

by Keith Allman, Josh Laurito, Michael Loh
October 2011
Beginner
216 pages
5h 47m
English
Wiley
Content preview from Financial Simulation Modeling in Excel

RECOVERY ASSUMPTIONS

One major factor that is often glossed over in texts on modeling is where recovery assumptions come from. Recovery assumption can have a tremendous impact on the implied default rate that an analyst may get from the market. An analyst assuming a 60–70 percent recovery may believe that the default likelihood is many times larger than an analyst using a similar model but assuming no recovery.

As defaults and credit events generally end up in court, there is considerable uncertainty as to what an accurate recovery would be if a company defaults. Despite this, practitioners often look to historical defaults in order to get a feel for what an appropriate rate might be. One good source for historical data is provided by www.creditfixings.com, which posts historical CDS credit event auction results. However, due to the wide variance of recoveries (from over 96 percent to less than 1 percent), it is important to understand how similar the debt being modeled is to the debt of the companies that may be used as a comparison.

Generally, four major variables are commonly used in performing a recovery or “loss given default” (LGD) analysis: the seniority of the debt, the industry of the company, the ratio of assets to liabilities, and the state of the overall economy.

The seniority of the debt is generally the most important factor. Whether the bond is senior or subordinate, and how much senior and subordinate debt is outstanding, is crucial to a recovery assumption. Whether ...

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ISBN: 9780470931226Purchase book