Financial ratios as a powerful instrument to predict insolvency; a study using boosting algorithms in Colombian firms

Mejía, Diego Andrés Correa; Lopera-Castaño, Mauricio

doi:10.18046/j.estger.2020.155.3588

Cited by 6 publications

(5 citation statements)

References 42 publications

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“…Due to financial debts are less expensive than equity, especially for the interest tax shields. On the other hand, it has been demonstrated that high debt increases the likelihood of insolvency [14]. The comparison of the accuracy of various prediction models and the decision which model has SHS Web of Conferences 9 2, 0 (2021) Globalization and its Socio-Economic Consequences 2020 [16].…”

Section: Financial-economics Analysismentioning

confidence: 99%

“…(1 -short-term receivables) (5); Adjusted current assets = financial accounts + adjusted inventory + adjusted short-term receivables (6); Adjusted short-term liabilities = short-term liabilities. (1 -short-term commitments) (7); Available liquidity = financial accounts / short-term external capital (8); Current liquidity = (financial accounts + short-term receivables) / short-term external resources (9); Total liquidity = (inventories + financial accounts + short-term receivables) / short-term external capital (10); Operating liquidity = financial accounts / short-term liabilities (11); Current operating liquidity = (financial accounts + short-term receivables) / short-term liabilities (12); Total operating liquidity = (stocks + financial accounts + shortterm receivables) / short-term liabilities (13); Adjusted available liquidity = financial accounts / adjusted short-term liabilities (14); Adjusted current liquidity = (financial accounts + adjusted balance of receivables) / adjusted balance of short-term liabilities (15); Adjusted total liquidity = adjusted balance of current assets / adjusted balance of current liabilities (16). 3 Results…”

Section: Ex Post Financial Analysismentioning

confidence: 99%

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Financial Analysis as a Basis for Creation of the Financial Plan of the Selected Business Entity – Case Study

Skocdopole

2021

SHS Web of Conf.

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Research background: Authors mentioned in the Research describe a financial analysis as first step of a financial planning process. It is an effective tool in the evaluation of a company’s financial efficiency on the basis of data from financial reports, where the individual data are sorted, aggregated and measured. The analysis usually consists liquidity, activity, profitability indicators and debt ratios. The result of the analysis should evaluate financial health and subsequently predict future of the focused company. Purpose of the article: The scope of this article is a practical application of financial analysis of the company. The main sources of information include financial statements balance sheet and income statement over the period of the last 3 years. Other sources are information obtained from employees of the company and information gained by studying a literature. Methods: The analysis process begins by identifying the main objectives and targets, continues by the methodical procedure, analysis of indicators and an interpretation of the analysis results. The main objective of the analysis is to evaluate the assets, the sources and the overall economic situation of the company. The key indicators that are the status and development of current and non-current assets, the status and development of equity and liabilities and a profit development. Findings & Value added: The financial analysis of a focused company was applied for the last 3-year time period. The worst status of the indicators occurred in the second year and after the subsequent intervention of the company management the result improved to sustainable status.

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Section: Financial-economics Analysismentioning

confidence: 99%

Section: Ex Post Financial Analysismentioning

confidence: 99%

Financial Analysis as a Basis for Creation of the Financial Plan of the Selected Business Entity – Case Study

Skocdopole

2021

SHS Web of Conf.

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“…Looking at previous research contributions, we find that financial analysis as an input to forecast was employed partially, as a large group of researchers used financial analysis to predict the future financial conditions of companies, and we mention from that: the study (Jiang & Lee, 2012), which confirmed the possibility of using financial ratios to predict basic returns For stocks, and a study (Yang & Dimitrov, 2017) that found that using processed data is useful in predicting companies' default. Indeed, some studies have determined the accuracy of using financial analysis in forecasting, such as the study (Correa-Mejía & Lopera-Castaño, 2020), which concluded that the financial ratio analysis could be used to predict the failure of companies for a period of three years with an accuracy rate of 70%, this percentage increased to 80% According to the results of the study (Alireza & others, 2021).also, (Slimi, 2012) studied the effect of business cycles in certain countries in the Middle East and North Africa on the profitability of banks. The study concluded that the effect of recession is not certain on the profitability of banks and it varies by country and a study of (Ibrahim, et al, 2017) discussed several macro and partial indicators including financial indicators for banks-that can be used as an early system to monitor financial crises before they occur.…”

Section: Previous Studiesmentioning

confidence: 99%

Using the Financial Analysis Approach to Forecast Industrial Production: A Guide from Jordan

Banikhalid¹,

Al-Oshaibat²

2021

IJBM

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This study aims to derive the function that can be used to predict the growth rate in the added value of industrial production in Jordan, depending on the financial ratios of industrial companies listed on the Amman Stock Exchange. To achieve the objectives of the study, the descriptive and analytical approach and multiple regression analysis were used using the SPSS program. The study population was represented by the public joint-stock companies listed on the Amman Stock Exchange in the industrial sector from 1994 to 2018. Results show that the financial ratios influencing the growth rate in industrial production value added the most (Industry t + 1) are earnings per share (EPS), net profit margin (NPM), and return on equity (ROE). Moreover, the effect is non-linear expressed by a function that can be used to predict the industrial production in Jordan. The study recommends paying attention to the partial input to predict macroeconomic variables, especially with the development of systems for storing and processing big data, as this method provides appropriate and sufficient data to make accurate decisions and enhances the right track.

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“…That way, based on information obtained from a set of financial reports, the management would be able to recognize early signals of business failure. Forecasting the business failure of companies, according to previous research, can be done using a traditional model (based on selected indicators) [15][16][17], but also by using existing, modern models (Altman Z"model, Springate model, Zmijewski model, Kralicek's model, BEX model, logit model) [18][19][20][21][22] to recognize early signals of business failure, i.e. determine whether the analyzed company will go bankrupt or not.…”

Section: Introductionmentioning

confidence: 99%

Modern models for predicting bankruptcy to detect early signals of business failure: Evidence from Montenegro

Vukčević,

Lakićević,

Melović

et al. 2024

PLoS ONE

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This paper explores predicting early signals of business failure using modern models for bankruptcy prediction. It reviews how continuous operations enhance market value, strengthening competitiveness and reputation among stakeholders. The study involves medium and large companies in the Montenegrin market from 2015 to 2020, comprising 30 bankrupt and 70 financially stable firms. Logistic regression is also employed to create a logit model for early detection of bankruptcy signals in companies. This research establishes the empirical validity of modern models in predicting business failure in the Montenegrin market, particularly through logistic regression. Significant indicators, such as the Degree of Indebtedness (DI) and turnover ratio of business assets (TR), exhibit strong predictive power with a p-value less than 0.001 according to Likelihood ratio tests. The paper underscores the potential benefits of bankruptcy prediction for both internal and external stakeholders, especially investors, in enhancing the competitiveness of Montenegro’s large and medium-sized companies. Notably, the research contributes by bridging the gap between theory and practice in Montenegro, as bankruptcy prediction models have not been extensively applied in the market. The authors suggest the possible applicability of the created logit model to neighboring countries with similar economic development levels. In that sense, the concept of predicting bankruptcy is positioned as integral to corporate strategy, impacting the overall reduction of bankruptcies. The paper concludes by highlighting its role as a foundation for future research, addressing the literature gap in the application of bankruptcy prediction models in Montenegro. The created logit model, tailored to the specific needs of Montenegrin companies, is presented as an original contribution, emphasizing its potential to strengthen the competitiveness of companies in the market.

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Financial ratios as a powerful instrument to predict insolvency; a study using boosting algorithms in Colombian firms

Cited by 6 publications

References 42 publications

Financial Analysis as a Basis for Creation of the Financial Plan of the Selected Business Entity – Case Study

Financial Analysis as a Basis for Creation of the Financial Plan of the Selected Business Entity – Case Study

Using the Financial Analysis Approach to Forecast Industrial Production: A Guide from Jordan

Modern models for predicting bankruptcy to detect early signals of business failure: Evidence from Montenegro

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