Implementation of binary logistic regression analysis for financial distress prediction on manufacturing firms listed in Indonesia stock exchange (idx) period 2005-2009

GO, GEORGE HERBERT (2011) Implementation of binary logistic regression analysis for financial distress prediction on manufacturing firms listed in Indonesia stock exchange (idx) period 2005-2009. Masters thesis, Universtitas Pelita Harapan.

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Abstract

In today’s complex and ever changing world, business enviroment keeps changing.Dynamic environment will force firms to adapt with it, or else they are going to suffer. Every change affects the capabilities of firm to survive and grow in the middle of competitions. As a result, financial report is frequently used as a tool to measure firm’s success in operating its business model. In examining the report, financial ratios play important role to make the information to be more useful and easily interpreted, for example to predict financial distress. Financial distress model is very important to be developed. Failures of firms have shocked people across the globe and helped raising awareness that nowadays, not only small and medium enterprises, but also large corporations are not protected from bankruptcy. The causes of bankruptcy can be varied (systematic or unsystematic) and might cause great structural change in the world economy. The sample is composed by 58manufacturing firms that operate in Indonesia and also listed in Indonesia Stock Exchange, from which 29 did not have any financial problems and the other 29 were financially distressed. The method used to analyze is binary logistic regression with help of SPSS 16. The result of this research finds out ratio Retained Earnings / TotalAssets, OperatingIncome / TotalAssets as being the most significant variables in predicting financial distress. Every party who have interest in knowing a firm financial stability should pay more attention on these ratio compared to others

Item Type: Thesis (Masters)
Creators:
CreatorsNIMEmail
GO, GEORGE HERBERTNIM90120080011UNSPECIFIED
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: University Subject > Current > Faculty/School - UPH Surabaya > Business School > Master of Management
Current > Faculty/School - UPH Surabaya > Business School > Master of Management
Depositing User: Rafael Rudy
Date Deposited: 25 Nov 2022 08:50
Last Modified: 25 Nov 2022 08:50
URI: http://repository.uph.edu/id/eprint/51435

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