Local asymptotic mixed normality property for elliptic diffusion: a Malliavin calculus approach

By Emmanuel Gobet. 2001

96 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Finance, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/91bc5f31733302752ef0ee88f3c81697943ef286

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Jia Li
2. V. Todorov
3. Michael SØrensen
4. A. Lindner
5. Mathieu Kessler
6. George Tauchen
7. Masayuki Uchida

In Finance

1. V. Todorov
2. George Tauchen
3. Jia Li
4. Tim Bollerslev
5. A. Lindner
6. Mathieu Kessler
7. Michael SØrensen
8. Peter J. Brockwell

In Modeling and Simulation

1. Michael SØrensen
2. Jia Li
3. V. Todorov
4. George Tauchen
5. Bo Martin Bibby

Citations in the corpus

• Adaptive estimation of continuous-time regression models using high-frequency data (2017, methodology): “1 We leave for future work the analysis of the problem of efficient continuoustime regression estimation in the case when the data is contaminated by noise and the elements of X are asynchronously observed; see, for example, Hayashi and Yoshida (2011) and Bibinger et al.”
• Statistical Methods for Stochastic Differential Equations (2012, background): “Gobet (2001) showed, under regularity conditions, that for the high-frequency asymptotics in a fixed time-interval considered in this section, the diffusion model is locally asymptotically mixed normal (LAMN) with rate √ n and conditional variance given by W (β); see e.”