Review of Corporate Governance Practices and Financial  Distress Prediction

Gillani, Syed Muhammad Ahmad Hassan; Ramakrishnan, Suresh; Raza, Hamad; Ahmad, Humara

doi:10.14419/ijet.v7i4.28.22385

Cited by 6 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…the management) in which the principal evaluates the agent's performance. The theory argues that in conditions of asymmetric information, agency problems are raised (Ahmad et al, 2018). Agency theory has attracted several disciplines: accounting, finance, economics, law, political science, strategy, and organizational psychology.…”

Section: Literature Review Agency Theorymentioning

confidence: 99%

Analysis of Financial Ratios to Predict Financial Distress Conditions of Manufacturing Companies Listed on the Indonesian Stock Exchange

Abdullah¹,

Mirosea²,

Aswati³

et al. 2023

J. Professional Business Review

View full text Add to dashboard Cite

Purpose: This aimsof this study is to identify and analyze the effects of liquidity, profitability, and leverage ratio changes to predict financial distress experienced by manufacturing companies listed on the Indonesian stock exchange. Theoretical framework: The quality of financial reports can improve and enhance a company’s financial performance and confirm the agency theory. The use of financial report quality can help explain relationship conflicts between the principal and the agents and strengthen the explanation of agency theory. Design/Methodology/Approach: The methodology this study used secondary data from the Indonesian stock exchange website. The research population consisted of all manufacturing companies listed on the Indonesian stock exchange. The sample of this study was chosen based on purposive sampling techniques resulting in 15 manufacturing companies meeting the criteria for analysis using logistic regression. The data were analyzed in a quantitative manner using SPSS version 23. Findings: The result of this research confirm the notion of agency theory stating that current ratio (CR) and return on assets (ROA) have negative and significant effects on financial distress. However, the debt-to-asset ratio (DAR) variable does not significantly affect financial distress. These findings indicate that a good current ratio and return on assets of a company will affect the company’s financial conditions while the effect of the debt-to-asset ratio (DAR) is not significant because the company is experiencing financial pressure in settling long-term debts. Research, Practical & Social implications: The study contributes to strengthening previous research findings and helps provide useful information to investors, manufacturing companies, and the business world in general on the Indonesian Stock Exchange in predicting the financial conditions of companies that are experiencing financial distress. Originality/Value: The value of the study contributes ideas to improve the quality of financial information, especially for accounting professional institutions (standard setters) and regulators to improve the quality of financial accounting standards in order to provide quality information to investors, government, stakeholders, and business society in general.

show abstract

Section: Literature Review Agency Theorymentioning

confidence: 99%

Analysis of Financial Ratios to Predict Financial Distress Conditions of Manufacturing Companies Listed on the Indonesian Stock Exchange

Abdullah¹,

Mirosea²,

Aswati³

et al. 2023

J. Professional Business Review

View full text Add to dashboard Cite

show abstract

“…It gives regulators, financial institutions, and politicians the ability to prepare ahead, which helps to safeguard the economy as a whole from the repercussions of firm bankruptcies that cascade through the organization. In the event that a company is experiencing financial problems, it may have consequences that extend beyond the confines of its region (Gillani et al, 2018). This includes workers, suppliers, and any other stakeholders who may be involved (Taj et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Financial Indicators and Corporate Financial Distress Prediction in Context of Pakistan: A Systemic Review.

Muhammad Kamran,

Hassan Mujtaba Nawaz Saleem

2023

ASSAP

View full text Add to dashboard Cite

It is feasible to predict the financial distress that a Pakistani company may experience under the current conditions. This study draws attention to key factors influencing financial forecasting and mitigation by integrating the results of several research studies conducted over the last two decades. The literature places a great deal of emphasis on financial variables such as profitability, solvency, and liquidity as indicators. Other factors that may affect prediction models is an increase in inflation, interest rates, or the gross domestic product. Corporate governance, industry dynamics, market indicators, and legal and regulatory frameworks are among the many factors that impact financial distress prediction. As far as methodologies adopted in existing research are concerned, the machine learning methods are replacing statistical methods and are providing best prediction results. Moreover, this study provides a road map for the future research diretions to be employed for financial prediction related studies.

show abstract

Non-financial variables related to governance and financial distress prediction in SMEs–evidence from Egypt

Ragab

Saleh

2021

JAAR

View full text Add to dashboard Cite

PurposeThis study examines the effect of non-financial variables related to governance on the accuracy of financial distress prediction among Egyptian listed small and medium-sized enterprises (SMEs), by using the logistic regression technique.Design/methodology/approachThis study used a sample of 24 Egyptian-listed SMEs in each year, totaling 120 firm observations, of which 25 were classified distressed and 95 of them non-distressed between 2014 and 2018. The variables for the study included five financial variables and thirteen non-financial variables related to governance. The models were developed using financial variables alone as well as combining financial and non-financial variables related to governance.FindingsThe results showed that the model with financial variables had a prediction accuracy of 91.7% , whereas models with a combination of financial and non-financial variables related to governance predict with comparatively better accuracy of 92.7 and 93.6% .Research limitations/implicationsAlthough the results seem to be conclusive, it could be noted that the non-distressed sample was not paired with the distressed sample. Other studies showed that paired samples increase the financial distress prediction rate. Furthermore, due to the small sample size, this study was unable to create a hold-out sub-sample for the accuracy test.Practical implicationsThe proposed distress prediction model for SMEs is effective for stakeholders, including banks and other financial institutions, in the assessment of the credit risk of SMEs. Using such a model, they could better identify SMEs with a higher risk of failure in their lending decisions. Moreover, SME managers' could be interested in using such models as a tool for planning corrective action, in addition to planning and controlling current operations to avoid financial failure in the future.Originality/valueThis study contributes to financial distress prediction literature in different ways. First, few studies were conducted in the area of financial distress among SMEs. Second, neither of these studies was conducted within the Egyptian context, nor any of them had used non-financial variables related to governance in the prediction of financial distress among SMEs.

show abstract

Review of Corporate Governance Practices and Financial Distress Prediction

Cited by 6 publications

References 31 publications

Analysis of Financial Ratios to Predict Financial Distress Conditions of Manufacturing Companies Listed on the Indonesian Stock Exchange

Analysis of Financial Ratios to Predict Financial Distress Conditions of Manufacturing Companies Listed on the Indonesian Stock Exchange

Financial Indicators and Corporate Financial Distress Prediction in Context of Pakistan: A Systemic Review.

Non-financial variables related to governance and financial distress prediction in SMEs–evidence from Egypt

Contact Info

Product

Resources

About