Nonparametric inference for Lévy-driven Ornstein-Uhlenbeck processes

By Geurt Jongbloed, F. Meulen, A. van der Vaart. 2005

111 citations recorded by the source corpus.

Subfields: Finance, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/970bc56115d695e78d73b9e52e903692314c983e

How researchers see this paper

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

In Finance

1. Peter J. Brockwell
2. Valentine Genon-Catalot
3. V. Todorov
4. Fabienne Comte
5. Richard A. Davis
6. Yu Yang
7. Hiroki Masuda
8. Markus Reiß

In Mathematical Physics

1. Fabienne Comte
2. Valentine Genon-Catalot
3. Michael H. Neumann
4. Richard A. Davis
5. Peter J. Brockwell
6. Wim Schoutens
7. Johanna Kappus
8. Markus Reiß

Citations in the corpus

• Recent results in the theory and applications of CARMA processes (2014, background): “Inference for such processes has also been investigated by Jongbloed et al. (2005).”
• Approximate self-weighted LAD estimation of discretely observed ergodic Ornstein-Uhlenbeck processes (2010, methodology): “[16] considered a nonparametric estimation of the Lévy density of Z together with a simple consistent estimator of λ; Jongbloed and van der Meulen [15] studied a parametric estimation based on the “cumulant M -estimator”, which is a kind of weighted minimum L(2)distance contrast functions; Brockwell”
• Ergodicity and exponential β-mixing bounds for multidimensional diffusions with jumps (2007, background): “[10] already proved the β-mixing property under stationarity.”
• Estimation for Nonnegative Lévy-Driven Ornstein-Uhlenbeck Processes (2007, background): “(The weak consistency of this estimator was shown by Jongbloed et al. (2005).)”
• Maximum likelihood estimation in processes of Ornstein-Uhlenbeck type (2009, background): “From a non-parametric point of view, the estimation of λ and the Lévy measure of the BDLP Z has been considered in Jongbloed et al. (2005).”
• Nonparametric estimation for L\'evy processes from low-frequency observations (2007, background): “A related low-frequency problem for the canonical function in L evy-Ornstein-Uhlenbeck processes has been considered by Jongbloed, van der Meulen, and van der Vaart (2005) , where a consistent estimator has been constructed.”
• Estimation for L\'{e}vy processes from high frequency data within a long time interval (2011, methodology): “As n(ˆhm) = k ˆhmk2, we deduce from ( 19 ) that, for all m 2 Mn,”
• Estimation of the characteristics of a Lévy process observed at arbitrary frequency (2010, methodology): “A very similar structure occurs in the estimation for Lévy-Ornstein-Uhlenbeck processes [5] and in the calibration of financial derivatives (European options) to Lévy models [1].”
• Nonparametric estimation for pure jump Lévy processes based on high frequency data. (2009, unknown): “Illustrations of this approach can be found in Watteel and Kulperger (2003), Jongbloed and van der Meulen (2006), Neumann and Reiss (2007), Jongbloed et al. (2005) for the related problem of L´evy-driven Ornstein-Uhlenbeck processes or Comte and Genon-Catalot (2008).”