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Modelling Dependence in High Dimensions with Factor Copulas
his paper presents flexible new models for the dependence structure, or copula, of economic variables based on a latent factor structure. The proposed models are particularly attractive for relatively high dimensional applications, involving fifty or more variables, and can be combined with semiparametric marginal distributions to obtain flexible multivariate distributions. Factor copulas generally lack a closed-form density, but we obtain analytical results for the implied tail dependence using extreme value theory, and we verify that simulation-based estimation using rank statistics is ...
Multivariate return decomposition: theory and implications
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 ...
All Fluctuations Are Not Created Equal: The Differential Roles of Transitory versus Persistent Changes in Driving Historical Monetary Policy
The historical analysis of FOMC behavior using estimated simple policy rules requires the specification of either an estimated natural rate of unemployment or an output gap. But in the 1970s, neither output gap nor natural rate estimates appear to guide FOMC deliberations. This paper uses the data to identify the particular implicit unemployment rate gap (if any) that is consistent with FOMC behavior. While its ability appears to have improved over time, our results indicate that, both before the Volcker period and through the Bernanke period, the FOMC distinguished persistent movements in ...