eprintid: 1635
rev_number: 11
eprint_status: archive
userid: 6
dir: disk0/00/00/16/35
datestamp: 2013-07-09 14:36:19
lastmod: 2013-07-09 14:36:19
status_changed: 2013-07-09 14:36:19
type: article
metadata_visibility: show
creators_name: Giovanis, Eleftherios
creators_id: eleftherios.giovanis@imtlucca.it
title: A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods
ispublished: pub
subjects: DS
subjects: HD28
divisions: EIC
full_text_status: public
keywords: ANFIS, Binary logistic regression, Financial distress, Panel data
abstract: The purpose of this paper is to present two different
approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a
more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services.
date: 2010-04
date_type: published
publication: World Academy of Science, Engineering and Technology
volume: 40
publisher: World Academy of Science, Engineering and Technology
pagerange: 646-652
refereed: TRUE
issn: 2010-376X
citation:   Giovanis, Eleftherios  A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods.  World Academy of Science, Engineering and Technology, 40.  pp. 646-652.  ISSN 2010-376X      (2010)  
document_url: http://eprints.imtlucca.it/1635/1/World%20Academy%20of%20Science%2C%20Engineering%20and%20Technology_Giovanis_2010.pdf