WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/10000936,
	  title     = {Early Warning System of Financial Distress Based On Credit Cycle Index},
	  author    = {Bi-Huei Tsai},
	  country	= {},
	  institution	= {},
	  abstract     = {Previous studies on financial distress prediction choose
the conventional failing and non-failing dichotomy; however, the
distressed extent differs substantially among different financial
distress events. To solve the problem, “non-distressed”, “slightlydistressed”
and “reorganization and bankruptcy” are used in our article
to approximate the continuum of corporate financial health. This paper
explains different financial distress events using the two-stage method.
First, this investigation adopts firm-specific financial ratios, corporate
governance and market factors to measure the probability of various
financial distress events based on multinomial logit models.
Specifically, the bootstrapping simulation is performed to examine the
difference of estimated misclassifying cost (EMC). Second, this work
further applies macroeconomic factors to establish the credit cycle
index and determines the distressed cut-off indicator of the two-stage
models using such index. Two different models, one-stage and
two-stage prediction models are developed to forecast financial
distress, and the results acquired from different models are compared
with each other, and with the collected data. The findings show that the
one-stage model has the lower misclassification error rate than the
two-stage model. The one-stage model is more accurate than the
two-stage model.
},
	    journal   = {International Journal of Economics and Management Engineering},
	  volume    = {9},
	  number    = {3},
	  year      = {2015},
	  pages     = {949 - 955},
	  ee        = {https://publications.waset.org/pdf/10000936},
	  url   	= {https://publications.waset.org/vol/99},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 99, 2015},
	}