Copulas and Long Memory

Author:

Ibragimov Rustam,Lentzas George

Publisher

Elsevier BV

Reference40 articles.

1. Representation (49) implies that the joint distribution of Y t and Y t?h is normal with the correlation coefficient ? h and, thus, the copula of the r.v.'s X t and X t?;where ? t has a normal distribution: ? t ? N (0, 1 ? ? 2 )

2. Long memory processes and fractional integration in econometrics;R T Baillie;Journal of Econometrics,1996

3. ARCHIMEDEAN COPULAS AND TEMPORAL DEPENDENCE

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1. Elimination of long term memory in volatility in portfolio optimization: A study via some bivariate copulas (frank and BB6 copula);FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & DATA ANALYTICS: Incorporating the 1st South-East Asia Workshop on Computational Physics and Data Analytics (CPDAS 2021);2023

2. Goodness-of-fit test of copula functions for semi-parametric univariate time series models;Statistical Papers;2020-01-03

3. Remarks on the speed of convergence of mixing coefficients and applications;Statistics & Probability Letters;2013-10

4. How Can Long Memory in Volatility Be Eliminated in Portfolio Optimization: An Empirical Evidence Using Copulas;SSRN Electronic Journal;2013

5. Some aspects of modeling dependence in copula-based Markov chains;Journal of Multivariate Analysis;2012-10

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