Russo-Vallois integral
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In mathematical analysis, the Russo-Vallois integral is an extension of the classical Riemann-Stieltjes integral
for suitable functions f and g. The idea is to replace the derivative g' by the difference quotient
and to pull the limit out of the integral. In addition one changes the type of convergence.
Definition: A sequence Hn of processes converges uniformly on compact sets in probability to a process H,
,
if, for every ε > 0 and T > 0,
.
On sets:
,
and
.
Definition: The forward integral is defined as the ucp-limit of
- I − :
.
Definition: The backward integral is defined as the ucp-limit of
- I + :
.
Definition: The generalized bracked is defined as the ucp-limit of
- [f,g]ε:
.
For continuous semimartingales X,Y and a cadlag function H, the Russo-Vallois integral coincidences with the usual Ito integral:
.
In this case the generalised bracket is equal to the classical covariation. In the special case, this means that the process
- [X]: = [X,X]
is equal to the quadratic variation process.
Also for the Russo-Vallios-Integral an Ito formula holds: If X is a continuous semimartingale and
,
then
.
By a duality result of Triebel one can provide optimal classes of Besov spaces, where the Russo-Vallois integral can be defined. The norm in the Besov-space
is given by
with the well known modification for
. Then the following theorem holds:
Theorem: Suppose
,
,- 1 / p + 1 / q = 1 and 1 / p' + 1 / q' = 1.
Then the Russo-Vallois-integral
exists and for some constant c one has
.
Notice that in this case the Russo-Vallois-integral coincides with the Riemann-Stieltjes integral and with the Young integral for functions with finite p-variation.
[edit] References
- Russo, Vallois: Forward, backward and symmetric integrals, Prob. Th. and rel. fields 97 (1993)
- Russo, Vallois: The generalized covariation process and Ito-formula, Stoch. Proc. and Appl. 59 (1995)
- Zähle; Forward Integrals and SDE, Progress in Prob. Vol. 52 (2002)
- Fournier, Adams: Sobolev Spaces, Elsevier, second edition (2003)





