| Estimating
Credit Risk Premia
-- Lim Kian Guan
This
paper investigates the nature of the credit risk premium adjustments in the Jarrow-Lando-Turnbull
model of credit risk spreads. The adjustments relate the equivalent martingale
measures to the empirical measures of unconditional transition probabilities.
The author provides a modified version of the risk adjustment that allows a linear
partition of the credit spread into an unconditional default component, a recovery
component, and the risk premium adjustment. The risk adjustments are related to
conditional default risk, illiquidity risk, and other factors not related to recovery
effects. The log-transform of these risk adjustments can be specified as linear
regressions on a set of macroeconomic variables. Some new insights are gained
pertaining to these conditional risks such as a typical upward sloping term structure
and sensitivity to short-term treasury rates and increasing forward rates. The
conditional risks appear to be insensitive to market returns. ©
2006 The IUP . All Rights Reserved.
Quantifying
Operational Risk Guided by Kernel Smoothing and Continuous Credibility
--
Jim Gustafsson, Jens P Nielsen,
Paul Pritchard and Dix Roberts
The
challenge of assessing the capital, necessary to protect an organization against
exposure to operational risk losses is discussed in this paper (operational risk
itself is defined as the risk of loss arising from inadequate or failed internal
processes, people and systems or from external events). The evolutionary nature
of operational risk modelling to establish capital charges is recognized emphasizing
the importance of capturing tail behavior. Challenges surrounding the quantification
of operational risk particularly those associated to sparse data are addressed
with modern statistical methodology including nonparametric smoothing techniques
with a particular view to comparison with Extreme Value Theory (EVT). The credibility
approach employed supports analysis from pooled data across business lines on
a dataset from an internationally active insurance company. The approach has the
potential to be applied more generally, for example where data might be pooled
across risk types or where a combination of internal company losses and publicly
reported (external) data is used. ©
2006 The IUP . All Rights Reserved.
Hunting
the Living Dead: A "Peso Problem" in Corporate Liabilities Data
-- Umberto Cherubini and Matteo Manera
Recent
literature has pointed out that information asymmetries may be the reason of the
poor performance of structural credit risk models to fit corporate bond data.
In fact it is well known that these models lead to a strong understatement of
the credit spread terms structure, particularly on the short maturity end. Possible
explanations stem from strategic debt service behavior and, as discovered more
recently, the problem of accounting transparency. This raises the possibility
that some of these flaws could be reconducted to a sort of "peso problem",
i.e., the market may ask for a premium in order to allow for a small probability
that accounting data may actually be biased (Baglioni and Cherubini, 2005). In
this paper the authors propose a modified version of the Duan (1994, 2000) MLE
approach to structural models estimation in order to allow for this "peso
problem" effect. The model is estimated for the Parmalat case, one of the
most famous cases of accounting opacity, using both equity and Catalogue Data
Services (CDS) data. ©
2006 The IUP . All Rights Reserved.
Controlling
CFaR with Real Options A Univariate Case Study
--
Giuseppe Alesii
Cash
Flow at Risk (CFaR) can be controlled using real options. In this normative paper,
we derive numerically a univariate discrete time model, extension of (Kulatilaka,
1988), the expanded Net Present Value (NPV) of an industrial investment and simultaneously
state variable thresholds to optimally exercise real options for the whole life
of the project. In this framework, we model total variability in expanded NPV
using a Markov chain Monte Carlo method. A number of original results are derived
for an all equity financed firm. Cash flow distribution and CFaR is used for each
epoch in the life of the project. A VaR for the expanded NPV at time 0 is derived.
These new methods have been applied to two case studies in shipping finance, namely
a Very Large Crude Carrier and a Panamax. ©
2006 The IUP . All Rights Reserved. | 
