ABSTRACT
In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset 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.
Acknowledgements
We are grateful to the Editor and two anonymous referees for useful suggestions that significantly improved the paper. We have benefited from discussions with Richard Luger and Ángel León. Our thanks also go to seminar and conference audiences at the Universidad de Alicante, Universidad Adolfo Ibáñez, the 2016 Econometric Society European meeting at the Université de Genève, and the 3rd Annual Conference of International Association for Applied Econometrics at the University of Milano-Bicocca. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System.