Processus de Lévy en Finance - Laboratoire de Probabilités et ...
Processus de Lévy en Finance - Laboratoire de Probabilités et ...
Processus de Lévy en Finance - Laboratoire de Probabilités et ...
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118 CHAPTER 3. NUMERICAL IMPLEMENTATION<br />
and formulas (3.28–3.29) yield:<br />
where ψ A k<br />
∂ ˜ζ T (u k )<br />
∂q m<br />
= T eiu krT +T ψ k {<br />
e<br />
x m+iu k x m<br />
− 1 − (1 + iu k )(e xm − 1) }<br />
iu k (1 + iu k )<br />
= T (e xm − 1) eiu krT +T ψ k<br />
+ T e xm eiukrT (e T ψ k<br />
− e T ψA k )<br />
1 + iu k iu k (1 + iu k )<br />
− T e xm eiu krT (e T ψ k<br />
− e T ψA k )<br />
iu k (1 + iu k )<br />
e iu kx m<br />
+ T e xm eiu krT +T ψk A (e iu kx m<br />
− 1)<br />
,<br />
iu k (1 + iu k )<br />
= − A<br />
2 u k(u k − i). Suppose that the grid in strike space is such that x 0 = m 0 d for<br />
some m 0 ∈ Z. Th<strong>en</strong> for every j ∈ {0, . . . , M − 1},<br />
M−1<br />
∑<br />
DFT j [f k e iu M−1−kx m<br />
] = e iu M−1x m<br />
Introducing additional notation:<br />
k=0<br />
e −2πik(j−m−m 0)/M f k<br />
H k = eiu krT +ψ k T<br />
1 + iu k<br />
G k = eiu krT +ψ A k T<br />
iu k (1 + iu k ) ,<br />
we obtain the final formula for computing the gradi<strong>en</strong>t:<br />
∂ˆ˜z T (x j )<br />
∂q m<br />
= ∆ 2π e−ix ju M−1<br />
T (e xm − 1)DFT j<br />
[<br />
w k e −ix 0∆k H M−1−k<br />
]<br />
= e iu M−1x m<br />
DFT (j−m0 −m) mod M [f k ].<br />
+ T e xm (e iu M−1x m ˆ˜z T (x (j−m0 −m) mod M ) − ˆ˜z T (x j ))<br />
+ ∆ ]<br />
2π ei(xm−x j)u M−1<br />
T e xm DFT (j−m0 −m) mod M<br />
[w k e −ix0∆k G M−1−k<br />
− ∆ [<br />
]<br />
2π e−ix ju M−1<br />
T e xm DFT j w k e −ix0∆k G M−1−k . (3.32)<br />
The time values ˆ˜z T have already be<strong>en</strong> computed in all points of the grid wh<strong>en</strong> evaluating option<br />
prices, and the Fourier transforms of G k do not need to be reevaluated at each step of the<br />
algorithm because G k do not <strong>de</strong>p<strong>en</strong>d on q i . Therefore, compared to evaluating the functional<br />
alone, to compute the gradi<strong>en</strong>t of Ĵ α one only needs one additional fast Fourier transform per<br />
maturity date. The complexity of evaluating the gradi<strong>en</strong>t using the above formula is thus only<br />
about 1.5 times higher than that of evaluating the functional itself (because evaluating option<br />
prices requires two Fourier transforms per maturity date). If the gradi<strong>en</strong>t was to be evaluated<br />
numerically, the complexity would typically be M times higher. The analytic formula (3.32)<br />
therefore allows to reduce the overall running time of the calibration algorithm from several<br />
hours to less than a minute on a standard PC.