2012 | OriginalPaper | Buchkapitel
Second Extension: Functions of Several Increments
verfasst von : Jean Jacod, Philip Protter
Erschienen in: Discretization of Processes
Verlag: Springer Berlin Heidelberg
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The aim of this chapter is to extend the Laws of Large Numbers to functionals in which each summand depends on several successive increments of the underlying process
X
. This covers two different situations:
1.
The test function
f
is replaced by a function
F
on (ℝ
d
)
k
, where
d
is the dimension of
X
and
k
≥2 is an integer. Then the
i
th summand in the unnormalized functional is
$F(X_{i \varDelta _{n}}-X_{(i-1) \varDelta _{n}},\dots,X_{(i+k-1)\varDelta _{n}},-X_{(i-k-2) \varDelta _{n}})$
, and the same for the normalized functional, upon dividing each increment by
$\sqrt {\varDelta _{n}}$
.
2.
Each summand is a function of
k
n
successive increments (after dividing by
$\sqrt {\varDelta _{n}}$
for the normalized functionals), where
k
n
is a sequence of integers increasing to ∞, but such that
k
n
Δ
n
→0. This poses a formulation problem which is presented in Sect. 8.1, because then the test function must depend on
n
because its argument is
k
n
successive increments, and a form of “compatibility” for different values of
n
has to be assumed.
In Sects. 8.2 and 8.3 the Laws of Large Numbers for the unnormalized functionals are presented, for a fixed number
k
or an increasing number
k
n
of increments, respectively: the methods and results are deeply different in the two cases. In contrast, the results for the normalized functionals, given in Sect. 8.4, are basically the same for a fixed number
k
or an increasing number
k
n
of increments.
Of particular interest is the case of a fixed number
k
of increments, when the test function has a product form, for example when
d
=1 it could be
$f(x_{1},\dots,x_{k})=|x_{1}|^{p_{1}}\cdots|x_{k}|^{p_{k}}$
for positive reals
p
j
. The associated functionals are then called
multipower variations
and have been extensively used for estimating the integrated volatility when the process
X
has jumps. This application is presented from the consistency viewpoint here. The Central Limit Theorem is studied later and is given in Sect. 8.5.