Multivariate Return Decomposition: Theory and Implications

31 Pages Posted: 7 Sep 2017

See all articles by Stanislav Anatolyev

Stanislav Anatolyev

New Economic School; CERGE-EI

Nikolay Gospodinov

Federal Reserve Bank of Atlanta

Date Written: 2015-08-01


In this paper, we propose a model based on multivariate decomposition of multiplicative—absolute values and signs—components of several returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.

Keywords: multivariate decomposition, multiplicative components, volatility and direction models, copula, dependence

JEL Classification: C13, C32, C51, G12

Suggested Citation

Anatolyev, Stanislav and Gospodinov, Nikolay, Multivariate Return Decomposition: Theory and Implications (2015-08-01). FRB Atlanta Working Paper No. 2015-7, Available at SSRN:

Stanislav Anatolyev (Contact Author)

New Economic School ( email )

Skolkovskoe shosse, 45
Moscow, 121353

CERGE-EI ( email )

P.O. Box 882
7 Politickych veznu
Prague 1, 111 21
Czech Republic

Nikolay Gospodinov

Federal Reserve Bank of Atlanta ( email )

Atlanta, GA 30309
United States


Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics