On conditional covariance modelling: An approach using state space models-Reference-Cited by-同舟云学术

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On conditional covariance modelling: An approach using state space models

Published:2016-08 Issue: Volume:100 Page:304-317
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Hendrych R.,Cipra T.

Funder

Czech Science Foundation

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference20 articles.

1. Aielli, G.P., 2011. Dynamic conditional correlation: on properties and estimation. Working Paper 1507743, July, SSRN. URL: http://ssrn.com/abstract=1507743.

2. Joint forecasts of Dow Jones stocks under general multivariate loss function;Alp;Comput. Statist. Data Anal.,2010

3. Optimal Filtering;Anderson,1979

4. Multivariate GARCH models: a survey;Bauwens;J. Appl. Econometrics,2006

5. Modelling the coherence in short-run nominal exchange rates: a multivariate generalized ARCH model;Bollerslev;Rev. Econ. Stat.,1990

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1. Multivariate Volatility Modeling;Time Series in Economics and Finance;2020

2. MGARCH models: Trade-off between feasibility and flexibility;International Journal of Forecasting;2018-01

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