Predicting Financial Distress for Listed MENA Firms

El-Ansary, Osama; Bassam, Lina

doi:10.5296/ijafr.v9i2.14542

Cited by 6 publications

(22 citation statements)

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“…The performance of a DMBs could be used as yard stick to measure another DMBs in the same category in terms of size, capitalization and staff strength who operate in the same industry (Abdolazim, 2014). Basically, the financial performance of a DMBs could be a reflection of the trends in the banks return on assets, profitability, economic value added, return on equity, liquidity, solvency, riskiness of the bank and many others like how fast it concludes a loan facility request and ability to manage the loan facilities, the low level of non-performing loans (Arroyave, 2018;Faith & Agnes, 2015;El-Ansary, 2019;Fan & Yijun, 2014). The study by Makokha, Mukanzi and Maniagi (2016) and that of Shrivastave, Kumar and Kumar (2018) posited that financial performance is the measure of how well a firm uses its assets to generate revenues.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial Risk and Financial Performance Of Deposit Money Banks Listed In Nigeria

2020

IJBMR

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This study examined the effect of financial risks on performance of Deposit Money Banks DMBs) using the identified explanatory variables of financial risks, viz: Credit risks, Insolvency risks, Liquidity risks and Market risks covering a period of 12 years (2007-2018). The methodology of the study makes use of ex-post facto research design. While the population of the study were nineteen deposit money banks, the study sample comprised ten (10) DMBs. The panel regression models estimated using Unobserved Effects Model (UEM), while the result of the Hausman test indicated between fixed effect model and random effect model at 5% inference. The study findings showed that Credit Risk was negative and statistically significant to deposit money banks' performance [β =-13.0495; Pval = 0.013]. The result also shows that Liquidity Risk is inversely and insignificantly related to banks' profitability [β =-0.156; Pval = 0.6703] and Insolvency Risk (INSRK) have negative signs that are statistically insignificant to banks profitability [β =-0.016; Pval = 0.745]. Market Risk has insignificant and positive effect on Profitability (NPBIT) [β = 0.038; Pval = 0.5720] at 0.05 level. Also, Credit Risk (CR) was found to be negative and statistically significant at Economic Value Added [β =-7.0789; Pval = 0.006]. On the contrary, the result also shows that Liquidity Risk (LIQR) [β = 0.0264; Pval = 0.961] and Market Risk [β = 0.0369; Pval = 0.747] have positive signs that are statistically insignificant to Economic Value Added. On its part, Credit Risk (CR) established a negative and significant effect on Return on Assets [β =-0.9647; Pval = 0.0421]. Liquidity Risk [β =-0.0018; Pval = 0.8471] and Insolvency Risk [β = 0.0008; Pval = 0.7719] have negative and positive signs that are statistically insignificant to Return on Assets. In relation to the findings of the study, the study recommended amongst others that it is fundamental for DMBs in Nigeria to practice scientific credit risk management, improve their efficacy in credit analysis and loan management to secure as much as possible their assets, and minimize the high incidence of non-performing loans and their negative effects on financial performance. KEYWORD: credit risk, economic value added, financial risk, insolvency risk, market risk, profitability.

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Section: Literature Reviewmentioning

confidence: 99%

Financial Risk and Financial Performance Of Deposit Money Banks Listed In Nigeria

2020

IJBMR

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“…Various studies have been conducted to predict financial distress, including Altman's Z-score model. The relationship between cash flow and financial distress has been extensively researched (Bui & Thach, 2023;Bernardin & Tifani, 2019;El-Ansary & Bassam, 2019;Phan et al, 2022). If a business experiences financial distress, it will face cash flow difficulties.…”

Section: Introductionmentioning

confidence: 99%

Financial Distress, What Factors Affect It?

Anggraeni,

Hady,

Nalurita

2024

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Every company, small or large, can experience financial distress, to anticipate it, company need to know the factors that lead to financial distress. This study aimed to examine the relationship between operation cash flow, leverage, size of the company, retained earnings, director size, and audit committee on financial distress. This study used 114 manufacturing companies listed on the Indonesian stock market from the year 2018 until 2022. This research added director size and audit committee. The research uses quantitative data, and the data type used is secondary data collected from the financial reports of the companies under study listed on the Indonesia Stock Exchange. The result showed that operation cash flow, size of company, retained earnings, and director size have negative relationships with financial distress. However, leverage and audit committees have positive relationships. Management needs to manage operating cash flow, minimize leverage, manage the size of the company and retained earnings also manage the size of the director and audit committee according to the size of the company.

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“…Such an approach is based on time series forecasting. Financial ratios can be actively changed with fundamental changes in corporate finances and changes in the global economic environment (Osama and Bassam, 2019). It is essential to develop a revolutionary approach in the face of dynamic financial environments in the future.…”

Section: Introductionmentioning

confidence: 99%

Predicting financial distress using the worst-practice-frontier data envelopment analysis model and artificial neural network

Fathi

Rahimi

Minouei

2022

NBRI

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Purpose The main purpose of this paper is to predicate financial distress using the worst-practice-frontier data envelopment analysis (WPF-DEA) model and artificial neural network. Design/methodology/approach In this study, a neural network technique was used to forecast inputs and outputs in the future time-period. Using a WPF-DEA model, financially distressed companies were identified based on the worst performance, and an improvement solution was provided for those decision-making units. Findings This study’s findings show that dynamic WPF-DEA has high predictability in corporate financial distress, and it can be used with high confidence. Based on the future time-period results, JOUSH & OXYGEN was predicted to be a financially distressed company in the two future time-periods. Originality/value In recent decades, globalization, technological changes and a competitive space have increased uncertainty in the economic environment. In such circumstances, economic growth certainly depends on correct decision-making and optimal allocation of resources. It can be done by introducing appropriate tools and models for assessing corporate financial conditions, including financial distress and bankruptcy.

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Predicting Financial Distress for Listed MENA Firms

Cited by 6 publications

References 0 publications

Financial Risk and Financial Performance Of Deposit Money Banks Listed In Nigeria

Financial Risk and Financial Performance Of Deposit Money Banks Listed In Nigeria

Financial Distress, What Factors Affect It?

Predicting financial distress using the worst-practice-frontier data envelopment analysis model and artificial neural network

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