Wiener integrals, Malliavin calculus and covariance measure structure
By Ida Kruk, Francesco Russo, Ciprian A. Tudor. 2006
87 citations recorded by the source corpus.
We introduce the notion of covariance measure structure for square integrable stochastic processes. We define Wiener integral, we develop a suitable formalism for stochastic calculus of variations and we make Gaussian assumptions only when necessary. Our main examples are finite quadratic variation processes with stationary increments and the bifractional Brownian motion.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/de017aabe64947011ea777d75dba00ed5ad9d921
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Citations in the corpus
- The Jain–Monrad criterion for rough paths and applications to random Fourier series and non-Markovian Hörmander theory (2013, background): “Russo for the references [35, 36] which led to Example 2.”
- Stochastic Calculus with Respect to Gaussian Processes (2014, methodology): “To overcome this deficiency one then might consider [27, 28, 36, 41, 51].”