Multivariate return decomposition: theory and implications
Stanislav Anatolyev () and
Nikolay Gospodinov ()
No 2015-7, FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta
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 (search for similar items in EconPapers)
JEL-codes: C13 C32 C51 G12 (search for similar items in EconPapers)
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Journal Article: Multivariate Return Decomposition: Theory and Implications (2019)
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