TY - GEN
TI - An Empirical Analysis of Valuation Algorithms for Pricing Callable Snowball Floaters
AB - In this paper we value a callable snowball ﬂoater, a complex interest rate instrument with variable
coupon payments, which depend on the prevailing interest rates in arrears and recursively on
previous coupon payments. The embedded option requires solving an optimal stopping problem
using the dynamic programming principle. A well-known and widely used algorithm to estimate
conditional expectations is a speciﬁc form of least squares Monte Carlo simulation introduced by
Longstaﬀ and Schwartz (2001), which we refer to as the LSM approach. Contrary to the standard
approach, where discounted option values of the subsequent period are regressed on the current
state variables, Longstaﬀ and Schwartz (2001) use the ex post realized payoﬀs of in-the-money
option scenarios from continuation instead. They argue that, in doing so, they get values less than
or equal to the value implied by the optimal stopping rule, which provides an objective convergence
criterion.
We compare the LSM approach with the standard approach and use the price estimate from
an elaborate nested Monte Carlo simulation as a benchmark. We empirically ﬁnd that the LSM
estimate of the embedded option might be considerably downward biased, whereas the standard
estimate is much closer to the benchmark price. Moreover, we ﬁnd that there is no optimal type of
basis function that can generally be recommended for pricing interest rate instruments. Instead,
we suggest using the LSM approach to determine the optimal type of basis function that results
in the largest option value and rely on the standard approach to price the instrument. These
are important issues to consider when pricing complex interest rate instruments, in general, and
callable snowball ﬂoaters, in particular.
UR - http://ssrn.com/abstract=1456343
PY - 2009-09-01
AU - Filipović
AU - , Damir
AU - Friewald, Nils
AU - Pichler, Stefan
ER -