3319539787 by Unknown

Author:Unknown
Language: eng
Format: epub
Published: 2017-08-09T10:29:16+00:00

PV0 = N 0

N–1 Pθ, s .

S

θ, s

s=1, ... , S

where N 0 is the value in 0 of the numeraire.

48

Bibliography

The Adjoint Algorithmic differentiation start from the last step. The derivat-

ives are computed with respect to the underlying parameters M 0 and the model

parameters V

Average There is one sensitivity for each scenario s:

¯ Nθ, s = – N 0 N–2 θP

.

, s

θ, s

and

¯ Pθ, s = N 0 N–1 θ, s

Numeraire and pay-off For each of the dimension m representing the market

and each scenario s we have one sensitivity:

¯ Mθ, s, m = Dmg 2( Mθ, s)¯ Pθ, s + Dmg 3( Mθ, s) ¯ Nθ, s.

Random number The starting parameters and curves are used in each scen-

ario s and for each dimension of the underlying market m:

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