PREDICTION OF CORPORATE FINANCIAL DISTRESS OF PN4 COMPANIES IN MALAYSIA: A LOGISTIC MODEL APPROACH

2005 ◽  
Vol 02 (02) ◽  
pp. 143-155 ◽  
Author(s):  
MOHAMAD ISA HUSSAIN ◽  
ANNUAR MD NASSIR ◽  
SHAMSHER MOHAMAD ◽  
TAUFIQ HASAN
Keyword(s):  
Financial Distress ◽  
Logistic Model ◽  
Model Approach

scholarly journals Financial Distress premium in Pakistan’s Banking Stocks

2020 ◽  
Vol 13 (4) ◽  
pp. 127-146
Author(s):  
Fahim Ullah Khan ◽  
Ahmad Fraz ◽  
Asif Ali
Keyword(s):  
Stock Returns ◽  
Financial Distress ◽  
Banking Sector ◽  
Factor Model ◽  
Covariance Structure ◽  
Additional Risk Factor ◽  
Cross Sectional ◽  
Portfolio Returns ◽  
Fama And French ◽  
Model Approach

This paper examines the role of financial distress premium in explaining the stock returns of banking sector in Pakistan using the sample of twenty listed banks for the period of 2008 to 2018. The study has used two methodologies. Firstly, multifactor model approach of Fama and French (1992) is used to test the financial distress premium (additional risk factor) where portfolio returns are regressed with factor premiums in time series framework. Fama and French (1993) argue that the relationship between the stock return and the selected characteristics occur for that reason these characteristics are proxies for non-diversifiable factor risk. So, the characteristic based model approach of Huang (2009) is used in cross-sectional regression framework where stock returns are regressed with the characteristics. The results indicate that the proposed four factor model is applicable in the banking sector of Pakistan where financial distress premium is priced by the market. The characteristic based model shows insignificant impact of distress proxy of Altman Z score on the banking returns. It suggests that the cross-sectional returns are explained on the covariance structure of returns not the characteristics in the Pakistani banking stocks. The findings of the study suggests that the financial distress is important and consider while forming their portfolios.

Study on Early Warning of Enterprise Financial Distress — Based on Partial Least-squares Logistic Regression

2015 ◽  
Vol 65 (s2) ◽  
pp. 3-16 ◽  
Author(s):  
Kun Xu ◽  
Qilan Zhao ◽  
Xinzhong Bao
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Least Squares ◽  
Partial Least Squares ◽  
Early Warning ◽  
Financial Distress ◽  
Logistic Model ◽  
Logistic Regression Model ◽  
Warning System ◽  
Study Results

Establishment of an effective early warning system can make the company operators make relevant decisions as soon as possible when finding the crisis, improve the operating results and financial condition of enterprise, and can also make investors avoid or reduce investment losses. This paper applies the partial least-squares logistic regression model for the analysis on early warning of enterprise financial distress in consideration of quite sensitive characteristics of common logistic model for the multicollinearity. The data of real estate industry listed companies in China are used to compare and analyze the early warning of financial distress by using the logistic model and the partial least-squares logistic model, respectively. The study results show that compared with the common logistic regression model, the applicability of partial least-squares logistic model is stronger due to its eliminating multicollinearity problem among various early warning indicators.

scholarly journals JAKARTA ISLAMIC INDEX: COVID-19 PANDEMIC AND POTENTIAL FINANCIAL DISTRESS

2021 ◽  
Vol 7 (2) ◽  
pp. 210
Author(s):  
Avianto Nugroho ◽  
Wasiaturrahma Wasiaturrahma ◽  
Putri Anggia
Keyword(s):  
Financial Performance ◽  
Method Of Moments ◽  
Data Model ◽  
Financial Distress ◽  
Positive Impact ◽  
Generalized Method Of Moments ◽  
The Other ◽  
Islamic Companies ◽  
Profitability Ratios ◽  
Model Approach

This research aims to analyze the potential for financial distress of Islamic companies that are included in the Jakarta Islamic Index during pandemic of COVID-19, which is using profitability ratios, liability ratios, and liquidity ratios (Zwesky's Model). The sample is quarterly (2019 to 2020) and it is using the Generalized Method of Moments (GMM) panel data model approach that was developed by Arellano and Bond (1991). The results of this study indicate that the profitability ratio has the most influence on corporate financial distress and from the overall this research occurs in the process of decreasing company financial performance during pandemic of COVID-19. Moreover, there is one company that indicates financial distressed, there are twenty-two companies that experienced a decline in financial performance, but there are 7 companies that experiences better financial performance when the COVID-19 pandemic occurred. In one hand, this shows that COVID-19 has a broad effect on the decline in the financial performance of sharia companies. On the other hand, it has a positive impact on certain companies that works specifically in sectors which is related to information technology.

scholarly journals Assess the Impact of the COVID-19 Pandemic and Propose Solutions for Sustainable Development for Textile Enterprises: An Integrated Data Envelopment Analysis-Binary Logistic Model Approach

2021 ◽  
Vol 14 (10) ◽  
pp. 465
Author(s):  
Han-Khanh Nguyen ◽  
Mai-Nam Vu
Keyword(s):  
Data Envelopment Analysis ◽  
Textile Industry ◽  
Logistic Model ◽  
Business Performance ◽  
Data Envelopment ◽  
Factors Affecting ◽  
Dea Models ◽  
Binary Logistic Model ◽  
The Impact ◽  
Model Approach

The COVID-19 pandemic impacted many socio-economic areas of countries around the world. It has made the production and business situations of enterprises face substantial difficulties. In this study, the authors used data envelopment analysis (DEA) models to assess the impact of the COVID-19 pandemic on Vietnam’s textile and garment enterprises. The authors have used the binary logistic model to determine the factors affecting employees’ decision to change jobs in the textile industry. The research results showed that the COVID-19 pandemic greatly affected the business performance of the textile and garment enterprises in Vietnam. Moreover, the results helped identify the factors affecting employee turnover and proposed solutions to help businesses stabilize their personnel situation and develop sustainable businesses in the post-COVID-19 era.

scholarly journals Bivariate Response Logistic Regression for Categorical Data

2019 ◽  
Vol 1 ◽  
pp. 193-199
Author(s):  
V Adah ◽  
S C Nwaosu ◽  
M E Nja
Keyword(s):  
Logistic Regression ◽  
Categorical Data ◽  
Malaria Infection ◽  
Logistic Model ◽  
Joint Infection ◽  
New Approach ◽  
Explanatory Variables ◽  
Joint Infections ◽  
Bivariate Logistic Regression ◽  
Model Approach

The bivariate logistic regression model can be used to obtain the probability of joint events as well as individual events where there are two response variables and several explanatory variables. The existing bivariate logistic model approach appears intractable. This paper provides a modeling procedure that addresses this problem. This approach compares favourably with the existing procedure. The new approach is used to model the probability of malaria and typhoid infections, using age, sex and location of the patients as associated factors. The marginal probabilities showed a decrease in malaria infection with age. Sex and location showed a significant impact on the probability of malaria infection. Typhoid fever infection on the other hand indicates an increase with age. Sex has no significant impact on the probability of typhoid infection. The joint model shows that all variables are statistically significant with odds value greater than 1 indicating higher likelihood of joint infection and odds value that are less than one indicating lower likelihood of joint infections, χ2:12.02828 (0.00729)

scholarly journals Estimates Model of Factors Affecting Financial Distress: Evidence from Indonesian State-owned Enterprises

2019 ◽  
pp. 1-19 ◽  
Author(s):  
Aminullah Assagaf ◽  
Etty Murwaningsari ◽  
Juniati Gunawan ◽  
Sekar Mayangsari
Keyword(s):  
Financial Distress ◽  
Logistic Model ◽  
Operating Performance ◽  
Accounting Standards ◽  
Secondary Data ◽  
Financial Statements ◽  
Model Estimation ◽  
Corporate Planning ◽  
Factors Affecting ◽  
The Future

This study as a model estimation of factors that influence the financial distress of State-Owned Enterprises. This study contributes to the gap in an earlier study using a logistic model which classifies companies with indicators one for companies experiencing financial distress and a zero for the company is not experiencing financial distress, so it is not possible to do research specifically on one group of firms, for example, companies that experience financial distress. This study uses a marginal approach in measuring financial distress that is proxy with a marginal score with a more realistic and proven mathematics and accounting calculations. For the company's management with state, companies can use these results as a reference in evaluating the achievements of past operating performance, or to formulate strategies and policies in the future of corporate planning in order to achieve the level of marginally better scores or financial distress. This study needs to be continued by using secondary data corresponding realization of audited financial statements, so the result is more realistic and relevant because it uses the data of financial statements that meet the accounting standards.

scholarly journals LOGISTIC MODEL DEVELOPMENT FOR PREDICTION OF COVID-19 INFECTED INDIVIDUALS: CASE STUDY IN CENTRAL JAVA PROVINCE, INDONESIA

2021 ◽  
Vol 4 (1) ◽  
pp. 96-103
Author(s):  
Okky Widya Arditya ◽  
Widowati Widowati ◽  
Sutimin Sutimin ◽  
R. Heru Tjahjana ◽  
Priyo Sidik Sasongko
Keyword(s):  
Logistic Model ◽  
Model Development ◽  
Dynamical Behaviour ◽  
Central Java ◽  
Contact Patterns ◽  
High Death ◽  
The Mathematical Model ◽  
Central Java Province ◽  
Model Approach

In early 2020, covid-19 spread fast in the worldwide and cause the high death. The disease started from the Asian region which resulted in a viral pandemic in 2020. In order to anticipate the increasing of the cases, a strategy is needed to inhibit its transmission.  The mathematical model approach is important tool for predicting of covid-19 spread in populations. In this paper we propose and analyze the dynamical behaviour of a developed logistic model by considering the effect of the contact patterns in reducing the covid-19 spread process.  To verify the developed logistic model, numerical simulation was given with case study of covid-19 spread for patients under supervision in Central Java Province, Indonesia.  Based on simulation results, it was found that physical distancing can reduce the growth of the covid-19 spread for patient under supervision. It can be seen from the number of covid-19 spread for patients under supervision with physical distancing intervention smaller compared to without physical distancing intervention.

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