Simulated Method of Moments Estimation for Copula-Based Multivariate Models
By D. Oh, Andrew J. Patton. 2013
101 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/17e568daa2dbfe0cde4814bcd24c7489568b991d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- D. Oh
- Andrew J. Patton
- S. J. Koopman
- André Lucas
- Tim Bollerslev
- Kevin Sheppard
- Brendan K. Beare
- Gregor Kastner
In Finance
- D. Oh
- Andrew J. Patton
- S. J. Koopman
- André Lucas
- Tim Bollerslev
- Kevin Sheppard
- Brendan K. Beare
- Gregor Kastner
Citations in the corpus
- Goodness-of-Fit Tests for Copulas of Multivariate Time Series (2017, unknown): “Similar models were proposed by Dias and Embrechts [29], Chen and Fan [10] and Patton [30].”
- Modeling Dependence in High Dimensions With Factor Copulas (2015, methodology): “These simulated rank dependence measures can then be used in the SMM estimation method of Oh and Patton (2013), which is briefly described in Section 3.”
- A review of copula models for economic time series (2012, methodology): “A variety of different standard errors are computed for the estimated parameters, implementation details of which are presented in Patton [122].”
- Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads (2018, methodology): “In contrast, Chen and Fan (2006), Rémillard (2010), and Oh and Patton (2013) allowed for nonparametric estimation of the marginal distributions.”