From Surf Wiki (app.surf) — the open knowledge base
Russo–Vallois integral
In mathematical analysis, the Russo–Vallois integral is an extension to stochastic processes of the classical Riemann–Stieltjes integral
:\int f , dg=\int fg' , ds
for suitable functions f and g. The idea is to replace the derivative g' by the difference quotient
:g(s+\varepsilon)-g(s)\over\varepsilon and to pull the limit out of the integral. In addition one changes the type of convergence.
Definitions
Definition: A sequence H_n of stochastic processes converges uniformly on compact sets in probability to a process H,
:H=\text{ucp-}\lim_{n\rightarrow\infty}H_n,
if, for every \varepsilon0 and T0,
:\lim_{n\rightarrow\infty}\mathbb{P}(\sup_{0\leq t\leq T}|H_n(t)-H(t)|\varepsilon)=0.
One sets:
:I^-(\varepsilon,t,f,dg)={1\over\varepsilon}\int_0^tf(s)(g(s+\varepsilon)-g(s)),ds :I^+(\varepsilon,t,f,dg)={1\over\varepsilon}\int_0^t f(s)(g(s)-g(s-\varepsilon)) , ds
and
:[f,g]_\varepsilon (t)={1\over \varepsilon}\int_0^t(f(s+\varepsilon)-f(s))(g(s+\varepsilon)-g(s)),ds.
Definition: The forward integral is defined as the ucp-limit of
:I^-: \int_0^t fd^-g=\text{ucp-}\lim_{\varepsilon\rightarrow\infty (0?)}I^-(\varepsilon,t,f,dg).
Definition: The backward integral is defined as the ucp-limit of
:I^+: \int_0^t f , d^+g = \text{ucp-}\lim_{\varepsilon\rightarrow\infty (0?)}I^+(\varepsilon,t,f,dg).
Definition: The generalized bracket is defined as the ucp-limit of
:[f,g]\varepsilon: [f,g]\varepsilon=\text{ucp-}\lim_{\varepsilon\rightarrow\infty}[f,g]_\varepsilon (t).
For continuous semimartingales X,Y and a càdlàg function H, the Russo–Vallois integral coincidences with the usual Itô integral:
:\int_0^t H_s , dX_s=\int_0^t H , d^-X.
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-Vallois Integral an Ito formula holds: If X is a continuous semimartingale and
:f\in C_2(\mathbb{R}),
then
:f(X_t)=f(X_0)+\int_0^t f'(X_s) , dX_s + {1\over 2}\int_0^t f''(X_s) , d[X]_s.
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
:B_{p,q}^\lambda(\mathbb{R}^N)
is given by
:||f||{p,q}^\lambda=||f||{L_p} + \left(\int_0^\infty {1\over |h|^{1+\lambda q}}(||f(x+h)-f(x)||_{L_p})^q , dh\right)^{1/q}
with the well known modification for q=\infty. Then the following theorem holds:
Theorem: Suppose
:f\in B_{p,q}^\lambda, :g\in B_{p',q'}^{1-\lambda}, :1/p+1/p'=1\text{ and }1/q+1/q'=1.
Then the Russo–Vallois integral
:\int f , dg
exists and for some constant c one has
:\left| \int f , dg \right| \leq c ||f||{p,q}^\alpha ||g||{p',q'}^{1-\alpha}.
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.
References
This article was imported from Wikipedia and is available under the Creative Commons Attribution-ShareAlike 4.0 License. Content has been adapted to SurfDoc format. Original contributors can be found on the article history page.
Ask Mako anything about Russo–Vallois integral — get instant answers, deeper analysis, and related topics.
Research with MakoFree with your Surf account
Create a free account to save articles, ask Mako questions, and organize your research.
Sign up freeThis content may have been generated or modified by AI. CloudSurf Software LLC is not responsible for the accuracy, completeness, or reliability of AI-generated content. Always verify important information from primary sources.
Report