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Working papers:
 "Separating the Components of
Default Risk: A DerivativeBased Approach," Working Paper, New York University, October, 2006,
pdf
In this paper, I propose a general pricing framework that allows
the riskneutral dynamics of loss given default (QLGD) and
default probabilities (QPD) to be separately and
sequentially discovered. The key is to exploit the differentials
in QLGD exhibited by different securities on the same
underlying firm. By using equity and option data, I show that one
can efficiently extract pure measures of QPD that are
not contaminated by recovery information. Equipped with this
knowledge of pure default dynamics, prices of any defaultable
security on the same firm with nonzero recovery can be inverted
to compute the associated QLGD corresponding to that
particular security. Using data on credit default swap premiums, I
show that, crosssectionally, QPD and QLGD are
positively correlated. In particular, this positive correlation is
strongly driven by firms' characteristics, including leverage,
volatility, profitability and qratios. For example, 1 percent increase
in leverage leads to .14 percent increase in QPD and .60 percent
increase in QLGD. These findings raise serious doubts about
the current practice, by both researchers and practitioners, of
setting QLGD to a constant across firms.
 "DiscreteTime Dynamic Term Structure Models with Generalized Market
Prices of Risk," Working Paper, Stanford University and New York University, March, 2006, (with Qiang Dai and Ken Singleton), under revision for resubmission to the Review of Financial Studies,
pdf
This paper develops a rich class of discretetime, nonlinear dynamic term structure
models. Under the riskneutral measure, the distribution of the state vector
Xt resides within a family of discretetime affine processes that nests the exact discrete
time counterparts of the entire class of continuoustime models in Duffie and Kan (1996)
and Dai and Singleton (2000). Moreover, we allow the market price of risk, linking
the riskneutral and historical distributions of Xt, to depend generally on the state Xt.
The conditional likelihood functions for coupon bond yields for the resulting nonlinear
models under the historical measure are known exactly in closed form. As an illustration
of our approach, we estimate a three factor model with a cubic term in the drift of the
stochastic volatility factor and compare it to a model with a linear drift. Our results show
that inclusion of a cubic term in the drift signifficantly improves the models statistical
fit as well as its outofsample forecasting performance.
 "Riskneutral Dynamics of Interest Rates," 2006, (with Ken Singleton) (pdf available soon)
A critical assumption underlying many term structure models in the
literature is that the state variables are affine or exponentially
affine under the riskneutral measures. This assumption is mainly
for convenience since it allows for analytical pricing of bond
prices. This paper develops a simulation technique that can
compute bond prices efficiently, allowing for general nonlinearity
and interdependence of the state variables under the risk neutral
measures. We show that this technique can be used to investigate
whether US interest rates data exhibit any nonlinearity under the
risk neutral measures while making no prior assumptions on the
physical distribution of the state variables. A better
understanding of the riskneutral dynamics of interest rates will
ultimately enhance our knowledge of the dynamics of premiums
required by investors to bear interest rate risks.


