August 2013
Beginner to intermediate
672 pages
22h 30m
English
Content preview from Handbook of Economic Forecasting
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Chapter 16
Copula Methods for Forecasting Multivariate Time Series
Andrew Patton, Duke University, NC, USA
Abstract
Copula-based models provide a great deal of flexibility in modeling multivariate distributions, allowing the researcher to specify the models for the marginal distributions separately from the dependence structure (copula) that links them to form a joint distribution. In addition to flexibility, this often also facilitates estimation of the model in stages, reducing the computational burden. This chapter reviews the growing literature on copula-based models for economic and financial time series data, and discusses in detail methods for estimation, inference, goodness-of-fit testing, and model selection that are useful when ...
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