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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 2 m -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 pro posed method.
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