Identification of financial ratios applicable in the construction of a prediction model for bankruptcy of wood industry enterprises

Adamowicz, Krzysztof; Noga, Tomasz

doi:10.2478/ffp-2018-0006

Cited by 3 publications

(6 citation statements)

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“…Financial approach is an important method in bankruptcy prediction, since balance sheets and income statements proffer important information for early warning (Adamowicz & Noga, 2018;Cultrera & Brédart, 2016). Financial analysis is the basis for failure and financial distress prediction, as it can reveal the financial stability and strengths as well as weaknesses of firms (Gregova et al, 2020); thereby, financial ratios (representing solvency, activity, profitability, investment, and leverage) are the most frequently used variables in predictions (Fejér-Király, 2015;Šarlija & Jeger, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Predictions of failure and financial distress: A study on Portuguese high and medium-high technology small and mid-sized enterprises

Tong¹,

Serrasqueiro²

2021

Journal of International Studies

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The main purpose of this paper is to find the differences in the impacts of financial factors on business failure and financial distress. Using the traditional logistic regression method, this paper studies the ability of financial indicators to predict business failure and financial distress of small and mid-sized enterprises in Portuguese high and medium-high technology manufacturing sectors. The research results show that: (1) differences between financially healthy firms and failed firms are more obvious than differences between financially healthy firms and financially distressed firms; (2) the accurate rate of failure prediction decreases with time prolonging (from one year to three years prior to the event), whereas that of financial distress prediction maintains stable at a relatively lower level; (3) profitability is the most important indicator, which is negatively related to the probability of both business failure and financial distress; (4) debt-related and liquidity-related factors (especially indebtedness and general liquidity) are also important in predicting business failure and financial distress. This paper enriches the research literature on the predictions of both business failure and financial distress.

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Section: Literature Reviewmentioning

confidence: 99%

Predictions of failure and financial distress: A study on Portuguese high and medium-high technology small and mid-sized enterprises

Tong¹,

Serrasqueiro²

2021

Journal of International Studies

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“…The previous analyses investigated five financial indicators, which constituted the independent variables; they were the most suitable for the construction of a bankruptcy prediction model for wood industry enterprises. These indicators were: (i) X1 = PRUSAK2_X3 = current assets/current liabilities, (ii) X2 = HOŁDA_X3 = total income/mean assets, (iii) X3 = ALT-MAN_X4 = equity capital/total debt, (iv) X4 = WIERZBA_ X2 = profit from operating activity -depreciation-to-sales ratio; (v) X5 = PRUSAK1_X2 = operating cost/short-term commitment (Adamowicz and Noga 2018). Based on the tolerance indicator it was concluded that the selected variables (indicators) are not closely correlated and can be used to create a bankruptcy prediction model of wood industry enterprises.…”

Section: Resultsmentioning

confidence: 99%

“…Some studies have analyzed the applicability of MBM in predicting the financial situation of wood industry enterprises (Adamowicz and Noga 2017Noga et al 2014). The selection process for appropriate predictors was conducted and described in detail (Adamowicz and Noga 2018). In that process, the authors followed the opinion presented by Jones (2017) indicating that an increase in the number of predictors usually leads to an excessive adjustability, which consequently reduces the general accuracy of the model.…”

Section: Resultsmentioning

confidence: 99%

“…Financial indicators were treated as independent variables in MBM. The detailed process of selecting the variables used to construct FMWE was described in a separate article by Adamowicz and Noga (2018).…”

Section: Methodsmentioning

confidence: 99%

“…It was Adamowicz and Noga (2018) who indicated the need to create a special prediction model based on homogenous (single-branch) financial information. They presented the selection process of appropriate predicators necessary to create a new model of bankruptcy prediction (FMWE).…”

Section: And Many Others)mentioning

confidence: 99%

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Forecasting bankruptcy in the wood industry

Noga

Adamowicz

2020

Eur. J. Wood Prod.

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The assessment of a company’s financial condition is an effective tool, which supports the management system. Nowadays a number of models are available, most often multi-branch ones, which are able to predict the financial situation of an enterprise. Models solely intended for just one line of business are a rarity. As far as the wood sector is concerned, no homogenous model suited to the sector has been created. The article aims to present the final stage of research dealing with predicting bankruptcy in the wood sector. The bankruptcy prediction model presented in this paper, called the model for forecasting bankruptcy of wood enterprises (FMWE), has been developed specifically for the wood sector. The process of model construction was presented and the correctness of forecasts built with the use of FMWE was verified. The predictions were based on 1-, 2- or 3-year periods. Furthermore, the effectiveness of the FMWE projections was compared to the 10 most popular bankruptcy prediction models used in Poland. It was observed that in comparison with other prediction models, FMWE predictions for this particular industry indicate greater credibility, up to 90%, for 1-year and 2-year predictions.

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Untitled

2023

SPSUTOM

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The purpose of the article is to present the results of a PEST analysis of the legal, economic, social and technological determinants of hard coal market development in the European Union from 1990 to 2030. Design/methodology/approach: The research process was carried out with the use of four methods: analysis and synthesis (1) critical review of the literature (2), statistical techniques (3) and an industry case study (4). Findings: Detail regulatory (legal), economic, social (socio-cultural) and technology variables affecting the hard coal market have been identified. All the factors examined exhibited a destimulating effect on the development of the market, from the perspective of the entities operating on the hard coal extraction and utilization market in the European Union. The most pronounced negative effect stems from the social factors. The impact of the legal and economic determinants is of similar magnitude, whereas technological changes show the lowest potency in this regard. Research limitations/implications: Dynamic geopolitical changes and high susceptibility to interventionism can significantly affect the deviations of point forecasts in the pest coal industry in the long run. Practical implications: PEST analysis is used to assess the development of economic sectors regardless of the industry life cycle phase. It can also help determine a given industry's life cycle phase and its future migration trends in practice. Originality/value: The originality of this article lies in the employment of the quantification of macroenvironmental areas significantly affecting the industry, using an authorially modified PEST-based analysis.

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Identification of financial ratios applicable in the construction of a prediction model for bankruptcy of wood industry enterprises

Cited by 3 publications

References 61 publications

Predictions of failure and financial distress: A study on Portuguese high and medium-high technology small and mid-sized enterprises

Predictions of failure and financial distress: A study on Portuguese high and medium-high technology small and mid-sized enterprises

Forecasting bankruptcy in the wood industry

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