While the focus in the popular press has been on whether and by how much
the GSE are undercapitalized, whether or not the US government should nationalize the GSE
and the steep decline in stock prices of the GSE, everything stems from perceived credit risk
in agency mortgages and mortgage-backed securities and consequently the potential losses
the GSE face.
The US mortgage loans can broadly be categorized as “agency”, “Alt-A” and “subprime”.
Of all US mortgages outstanding, about 12% is subprime, about 50% is agency and the rest
is Alt-A. Of the originations in the 2003–07 timeframe, the proportion of agency mortgages
is significantly lower than 50% while after August 2007, agency mortgages are the dominant
category being originated.
Increasing delinquency and foreclosure in subprime mortgages catalyzed the near demise
of the mortgage securitization markets in 2007 and huge marked-to-market losses in CDO
books of many banks in the United States and elsewhere in 2007 and 2008. Yet subprime
constituted a small fraction of all US mortgages. In fact, the delinquency rates for US subprime
mortgages may have reached a plateau, although it is too soon to be conclusive.
Investors now fear increasing delinquencies in Alt-A and possibly agency mortgages. Since
the size of agency market is much bigger than the subprime market and the originally expected
losses are relatively small, any small change in projected delinquencies and losses can have
a big effect on the percentage increase in economic capital required to support the GSE
portfolios as well as on the mortgage market as a whole.
Investors extrapolated downgrades and losses in mezzanine RMBS and CDO of RMBS
tranches observed in mid-2007 to the much larger-sized, super-senior tranches without
explicit computation of their relative (credit) risks. Similarly, investors are extrapolating
losses in subprime to the much larger sized mortgage markets of Alt-A and agency mortgages
without necessarily assessing relative credit risks in securities backed by sub-prime
mortgages and by agency mortgages. This coupled with the uncertainty of any government
action on matters of restructuring mortgages to prevent foreclosure and of nationalizing the
GSE has left the mortgage market in a sorry state, postponing the possibility of a comeback
of mortgage-related securitizations.
In this issue, we present two full-length research papers and two technical reports.
The first paper “Break on through to the single side” is by Madan and Schoutens. In this
paper, the authors consider a structural form model for a firm’s asset value process, with
default occurring when, for the first time, asset value breaches a low barrier. They assume
that a firm’s value follows a Lévy process with negative jumps and derive the distribution of a
firm’s default time. They also calculate the corresponding CDS spread. After that the authors
study the calibration quality of their model in the context of a portfolio of 125 representative
credits contained in the iTraxx and CDX indexes.
The second paper “Valuing loan credit default swap cancellability” by Benzschawel et al
presents a general framework for calculating the additional premium required by protection
sellers as compensation for potential cancellation of loan credit default swaps (LCDS). They
assume that when high-yield credit becomes investment-grade the issuer firm will repay its
loans and contractually the LCDS will be terminated. The method requires as inputs both
a probability of default and likelihood of cancellation. While risk-neutral probabilities of
default may be inferred from market spreads, the actual probabilities of cancellation are unobservable.
Because of this, the authors use historical ratings transitions to estimate likelihoods
of cancellation for credits of various ratings and calculate their corresponding cancellation
premiums. The authors also provide an approximate formula for LCDS cancellability as the
ratio of fee legs for cancellable and noncancellable LCDS.
This issue has two technical reports. A technical report describes a particular practical
technique and enumerates situations in which it works well and others in which it does not.
Such reports provide extremely useful information to practitioners in terms of saved time
and duplication of efforts. The contents of technical reports complement rigorous conceptual
and model developments presented in the research papers and provide a lot of value to
practitioners.
The first technical report “Development and validation of credit scoring models” is by
Glennon et al. The authors develop a suite of credit scoring models using the same data but
with three modeling techniques widely adopted in the banking industry, including logistic
regression, rank ordering and CHAID. The authors use three approaches in variable selection:
stepwise, resampling and the intersection between the two. The performance of the models
is then evaluated with two types of measures: discriminatory power (K-S Statistic) and
predictive accuracy (Hosmer–Lemeshow Goodness of Fit Test). The statistical validations
are performed on both in-time and out-of-time samples, as well as multiple segments of the
samples. The conclusions are: 1) the models have discriminative powers; 2) the differences
across the models are small and 3) the out-of-time validation shows a substantial loss of
accuracy for all models – the loss is mainly from the large changes in the default rates of the
high risk components of the population. Practitioners will find this article highly useful in
developing industry-standard scorecards. This paper reads like a credit scoring primer and
its principles and techniques are accessible to even beginner readers.
The second technical report “Maturity adjustments under asymptotic single risk factor
models: a comparative analysis” by McCoy compares three approaches for calculating maturity
adjustment for credit exposures of maturity greater than one year within the scope of
asymptotic single risk factor (ASRF) model. These approaches are: (i) multi-period probability
of default based on the basic Merton framework as derived in Gurtler and Heithecker
(2005); (ii) “annualized” probability of default based on the basic survival analysis – a relationship
that has been in existence in credit literature for a long time; and (iii) default
probability term structure derived from market credit spreads. Actually there is a fourth one
lurking in the background: the Basel II maturity adjustment formulation. Maturity adjustment
in this context is the adjustment needed on the default-mode economic capital calculated with
a one-year horizon and some prespecified level of confidence. The overall contents of the
article provide a good survey of most things associated with maturity adjustment in economic
capital calculations. To the not-so-sophisticated practitioner, it provides a wealth of simple
knowledge about maturity adjustment. Maturity adjustment is an area that has not received
much attention in credit risk literature as evidenced by the rarity of papers with coverage of
maturity adjustment specifically. |
