Template-Type: ReDIF-Paper 1.0
Title: Spotting the Danger Zone - Forecasting Financial Crises with Classification Tree Ensembles and Many Predictors
Author-Name: Felix Ward
Author-Email:s3feward@uni-bonn.de
Classification-JEL: C53, E50, G01, N10
Keywords:  

Abstract: 	To improve the detection of the economic ”danger
zones” from which severe banking crises emanate, this
paper introduces classification tree ensembles to the
banking crisis forecasting literature. I show that their
out-of-sample performance in forecasting binary banking
crisis indicators surpasses current best-practice early
warning systems based on logit models by a substantial
margin. I obtain this result on the basis of one long-run-
(1870-2011), as well as two broad post-1970 macroeconomic
panel datasets. I particularly show that two marked
improvements in forecasting performance result from the
combination of many classification trees into an ensemble,
and the use of many predictors.

Note: 
Length: 68
Creation-Date: 2014-10
Revision-Date: 
File-URL: http://www.wiwi.uni-bonn.de/bgsepapers/bonedp/bgse01_2014.pdf
File-Format: application/pdf
Handle: RePEc:bon:bonedp:bgse01_2014