Principal component regression in GAMLSS applied to Greek–German government bond yield spreads

A solution to the problem of having deal with a large number interrelated explanatory variables within generalized additive model for location, scale and shape (GAMLSS) is given here using as an example Greek–German government bond yield spreads from 25 April 2005 31 March 2010. Those were turbulent financial years, in order capture behaviour, has be able complex nature indicators used predict spreads. Fitting model, principal components regression both main first interaction terms, all parameters assumed distribution response variable seems produce promising results.