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Partial Differential Equations - Modelling and ... - ResearchGate

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Calibration of Lévy Processes with American Options 271<br />

(T i ,x i ); we call ū i =¯p i −x i +S, i ∈ I. The parameters of the Lévy process, i.e.<br />

the volatility σ, the exponent α <strong>and</strong> the function ψ will be found as solutions<br />

of a least square problem, where the functional to be minimized is the sum of<br />

a suitable Tychonoff regularization functional J R (σ, α, ψ) <strong>and</strong>of<br />

J(u) = ∑ ω i (u(T i ,x i ) − ū i ) 2 ,<br />

i∈I<br />

where ω i are positive weights, <strong>and</strong> u = u(σ, α, ψ) is a solution of (VIP), with<br />

T =max i∈I T i .<br />

We aim at finding some necessary optimality conditions satisfied by the<br />

solutions of the least square problem. The main difficulty comes from the fact<br />

that the derivability of the functional J(u) with respect to the parameter<br />

(σ, α, ψ) is not guaranteed. To obtain some necessary optimality conditions,<br />

we shall consider first a least square problem where u is the solution of the<br />

penalized problem (37) rather than (VIP), obtain necessary optimality conditions<br />

for this new problem, then have the penalty parameter ε tend to 0 <strong>and</strong><br />

pass to the limit in the optimality conditions. Such a program has already been<br />

applied in [Ach05] for calibrating the local volatility with American options,<br />

see also [AP05b, AP05a] for a related numerical method <strong>and</strong> results. The idea<br />

originally comes from Hintermüller [Hin01] <strong>and</strong> Ito <strong>and</strong> Künisch [IK00], who<br />

applied a similar program for elliptic variational inequalities. At this point, we<br />

should also mention Mignot <strong>and</strong> Puel [MP84] who applied an elegant method<br />

for finding optimality conditions for a special control problem for a parabolic<br />

variational inequality.<br />

4.2 Preliminary Technical Results<br />

With the aim of finding optimality conditions for the least square problem<br />

(not completely defined yet), we first state some results concerning the adjoint<br />

of B.<br />

Under the assumptions of Proposition 2, it can be checked that the operator<br />

B T defined by<br />

∫ (<br />

B T u(x) = k(z) x(e z − 1) ∂u<br />

)<br />

∂x (x) − e2z u(xe z )+(2e z − 1)u(x) dz (40)<br />

z∈R<br />

is a continuous operator<br />

⎧<br />

⎪⎨ from V s to V s−2α , if α> 1 2 ,<br />

from V<br />

⎪⎩<br />

s to V s−1 , if α< 1 2 ,<br />

from V s to V s−1−ε , for any ε>0, if α = 1 2 .<br />

If α> 1 2 , then for all u, v ∈ V α , 〈B T u, v〉 = 〈Bv,u〉. This identity holds for<br />

all u, v ∈ V s with s> 1 2 if α ≤ 1 2 .

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