High-Dimensional Copula-Based Distributions with Mixed Frequency Data
FEDS Working Paper No. 2015-050
http://dx.doi.org/10.17016/FEDS.2015.050
54 Pages Posted: 26 Jul 2015
There are 2 versions of this paper
High-Dimensional Copula-Based Distributions with Mixed Frequency Data
High-Dimensional Copula-Based Distributions with Mixed Frequency Data
Date Written: May 19, 2015
Abstract
This paper proposes a new model for high-dimensional distributions of asset returns that utilizes mixed frequency data and copulas. The dependence between returns is decomposed into linear and nonlinear components, enabling the use of high frequency data to accurately forecast linear dependence, and a new class of copulas designed to capture nonlinear dependence among the resulting uncorrelated, low frequency, residuals. Estimation of the new class of copulas is conducted using composite likelihood, facilitating applications involving hundreds of variables. In- and out-of-sample tests confirm the superiority of the proposed models applied to daily returns on constituents of the S&P 100 index.
Keywords: composite likelihood, forecasting, high frequency data, nonlinear dependence
JEL Classification: C32, C51, C58
Suggested Citation: Suggested Citation