<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/7348" mdate="2010-04-27 00:00:00"> <author>螘. Giovanis</author> <title>A Study of Panel Logit Model and Adaptive NeuroFuzzy Inference System in the Prediction of Financial Distress Periods</title> <pages>423 - 429</pages> <year>2010</year> <volume>4</volume> <number>4</number> <journal>International Journal of Economics and Management Engineering</journal> <ee>https://publications.waset.org/pdf/7348</ee> <url>https://publications.waset.org/vol/40</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>The purpose of this paper is to present two different approaches of financial distress prewarning 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 insample and outsample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive NeuroFuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both insample and outofsample 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.</abstract> <index>Open Science Index 40, 2010</index> </article>