Bankruptcy Prediction Model With Zeta (c) Optimal Cut - Off Score to Correct Type I Errors  

Oleh:

Iwan, Mohamad

Jenis: Article from Journal - ilmiah nasional - tidak terakreditasi DIKTI
Dalam koleksi: International Journal of Business vol. 7 no. 1 (Jan. 2005), page 41-68.
Topik: BANKRUPTCY; bankruptcy prediction; legal bankruptcy; stock based insolvency; type I error; type II error; ZETA (c); optimal cut - off score

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II51.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This research examines financial ratios that distinguish between bankrupt and non - bankrupt companies and make use of those distinguishing ratios to build a one - year prior to bankruptcy prediction model. This research also calculates how many times the tupe I error is more costly compared to the type II error. The costs of type I and type II errors (cost of misclassification errors) in conjuction to the calculation of prior probabilities of bankruptcy and non - bankruptcy are used in the calculation of the ZETA (c) optimal cut - off score. The banruptcy prediction result using ZETA (c) optimal cut - off score is compared to the bankruptcy prediction result using a cut - off score which does not consider neither cost of classificaiton errors nor prior probabilities as stated by hair et al. (1998) and for later purposes will be referred to hair et al. optimum cutting score. Comparison between the prediction results of both cut - off scores is purported to determine the better cut - off score between the two, so that the prediction result is more conservative and minimizes expected costs, which mat occur from classification errors. This is the first research in indonesia that incorporates type I and type II errors and prior probabilities of bankruptcy and non - bankruptcy in the computation of the cut - off score used in performing bankruptcy prediction. Earlier researches gave the same weight between type I and II errors and prior probabilities o fbankruptcy and non - bankruptcy, while this research gives a greater weigh on type I error than that on type I error and prior probabilities on non - bankruptcy than that on prior probability of bankruptcy. This research has successfully attained the following results : 1. type I error is in fact 59,83 times more costly comparef to type II error 2. 22 ratios distinguish between bankrupt and non - bankrupt groups 3. 2 financial ratios proved to be effective in predicting bankruptcy 4. prediction using ZETA (c), optimal cut - off score predicts more ocmpanies filling for bankruptcy within one year compared to prediction using hair et at. optimum cutting score 5. although prediction using hair et al. optimum cutting is more accurate, prediction using ZETA (c), optimal cut - off score proved to be able to minimize cost incurred from classification errors.

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