Marco Reale University of Canterbury Universidade Federal do Parana, 27 th November 2006. Break-points detection with atheoretical regression trees. Acknowledgements. The results presented are the outcome of joint work with: Carmela Cappelli and William Rea. Structural Breaks.
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University of Canterbury
Universidade Federal do Parana, 27th November 2006Break-points detection with atheoretical regression trees
The results presented are the outcome of joint work with:
Their detection is important for:
With regard to this point a recent debated issue is fractional integration vs structural breaks.
It exploits the Quandt statistics for a priori unknown break-points.
Node 1 is called root.
Node 5 is called leaf.
The other nodes are called branches.
Regression trees don't provide necessarily optimal partitions
Trees tend to oversplit so the overgrown tree needs a pruning procedure:
All the information criteria robust for non normality, especially BIC.
... and of course you can say you're doing ART