Relevant bibliographies by topics / Altman's Z-Score Model

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Academic literature on the topic 'Altman's Z-Score Model'

Author: Grafiati
Published: 3 June 2025
Last updated: 19 July 2025

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Journal articles on the topic "Altman's Z-Score Model"

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Prof., Rohini Sajjan. "PREDICTING BANKRUPTCY OF SELECTED FIRMS BY APPLYING ALTMAN'S Z-SCORE MODEL." International Journal of Research – Granthaalayah 4, no. 4 (2017): 152–58. https://doi.org/10.5281/zenodo.846680.

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Predication of Bankruptcy is critical task. Early stage of identification of likelihood of solvency may avoid evils in the near future & may shelter the firm from Bankruptcy situation. Bankruptcy of organizations can be predicated by using Altman’s Z-Score Model. This study tries to apply the model to understand the likelihood of Bankruptcy of selected firms for past 5 years from 2011 to 2015 which are listed in BSE & NSE. Companies are selected from manufacturing & non-manufacturing sector. The study reveals that none of the companies completely belongs to Safe Zone except for few years. Most of the firms are in Distress Zone which clearly indicates that these firms may go Bankrupt in near future.
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Erizal, Erizal, Margaretha Michella Gunawan, and M. Nasyubun. "Analisis Prediksi Kebangkrutan Perusahaan Asuransi Kerugian Di Indonesia." Journal of Economic, Bussines and Accounting (COSTING) 7, no. 2 (2024): 3245–55. http://dx.doi.org/10.31539/costing.v7i2.8901.

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The application of the bankruptcy model using the Altman Z-score model is carried out to predict financial difficulties by using balance sheet analysis which can reflect the company's financial performance. Insurance companies are needed to minimize risks and uncertainties for futureprotection. Altman's Z-score model is analyzed through the calculation results if it is smaller than <1.1 it is concluded that the company is at high risk, if the calculation results are 1.1-2.6 it is concluded that the company is prone to bankruptcy, and if the calculation result is> 2.6 itcan be said that the company is healthy. So that the probability of bankruptcy can be estimated using the Z- score Altman method. This modeling can be used by insurance companies in making decisions. (MMG) Keywords: Bankruptcy, Financial Performance, Altman's Z-score Method
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Zamzami, Zamzami, Osrita Hapsara, and Yunan Surono. "Kinerja Perusahaan Berdasarkan Pertumbuhan Investasi dan Potensi Kebangkrutan Sub Sektor Perkebunan di Bursa Efek Indonesia Periode 2014 – 2017." J-MAS (Jurnal Manajemen dan Sains) 4, no. 1 (2019): 14. http://dx.doi.org/10.33087/jmas.v4i1.66.

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This research aims to prove the stock sub group of the plantation sector has a positive value of the company (investment growth) if measured using model Tobin's q, and potential bankruptcy if measured using models Altman's Z-score first, Altman's Z-score and the Z-Altman's revision of the score as well as modifications to get the stocks that had the best performance based on the model. The sample in this study using census methods, namely the entire company group issuers shares sub plantation sector during the four-year period, starting from the observation of the year 2014-2017 recorded as many as 16 corporate issuers in Indonesia stock exchange, This form of research is research eksplanatoris. The results showed that the company's performance based on investment growth with model Tobin's q on sub plantation sector was by 20% by the year 2014, by the year 2015 amounting to 13.33% and in the year 2016 amounting to 13.33% and the year 2017 of 26.67%. Group company shares sub plantation sector which has the best performance based on the model of the Altman Z-score First for potential bankruptcy was able to note that in 2014, based on code by issuers SSMS, LSIP and AALI. In the year 2015, 2016 and 2017 which had the most improved performance is SSMS and LSIP. Group company shares sub plantation sector which has the best performance based on the model of the Altman Z-score for potential Revision of bankruptcy, it can be noted that in the year 2014, with code ANJT, LSIP issuers and SSMS. In the year 2015, 2016 and 2017 which had the most improved performance is LSIP. Group company shares sub plantation sector which has the best performance based on the model of the Altman Z-score for potential bankruptcy Modification is the year 2014, with code issuers LSIP, SSMS, ANJT, AALI, SGRO and GOLL. In the year 2015, the stocks that have the most excellent performance namely LSIP, ANJT, AALI and SSMS. In the year 2016, the stocks that have the most excellent performance namely LSIP, AALI, ANJT, PALM, SSMS, SMAR and SIMP and the year 2017 which had the most improved performance is LSIP, AALI, ANJT, SSMS and SMAR.
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Anandasayanan.S and V.A Subramaniam. "PREDICTING BANKRUPTCY OF SELECTED MANUFACTURING COMPANIES LISTED IN COLOMBO STOCK EXCHANGE: APPLYING ALTMAN'S Z-SCORE." International Journal of Research -GRANTHAALAYAH 5, no. 2 (2017): 313–21. https://doi.org/10.5281/zenodo.376051.

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Bankruptcy is the legal status for an individual or company incapable to pay off outstanding debt. Predication of Bankruptcy is critical task. Early stage of identification of likelihood of solvency may avoid evils in the near future & may shelter the firm from Bankruptcy situation. Bankruptcy of organizations can be predicated by using Altman’s Z-Score Model. This study tries to apply the model to understand the likelihood of Bankruptcy of selected listed manufacturing firms for past 5 years from 2010 to 2014 which are listed in Colombo Stock Exchange. The study reveals that four companies completely belong to Safe Zone for the entire period of study. Three firms are in Distress Zone which clearly indicates that these firms may go Bankrupt in near future.
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Aradhana Sorout and Netra Pal Singh. "Bankruptcy Prediction Using The Altman Z-Score Modification Model in India: A Case Study of Bharti Airtel Limited." Southeast Asian Business Review 3, no. 1 (2025): 12–33. https://doi.org/10.20473/sabr.v3i1.63958.

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Indian telecom sector is facing intense competition since Reliance Jio has entered the telecom market. Furthermore, the COVID-19 pandemic has further strained the sector. Considering these, evaluating a company's financial health is of paramount importance. In spite of various methods available for determining financial stability, Altman's Z-score modification model has been considered a better tool to forecast the possibilities of bankruptcy and determine financial viability of a company. Therefore, this model has been adopted to track Bharti Airtel’s financial health in light of the aforementioned perspective. The purpose of the study is two-fold. Firstly, it focusses on evaluating the financial standing of Bharti Airtel limited & predicting bankruptcy using Altman's Z-score modification model. Secondly, it evaluates the financial standing of Bharti Airtel in context of seven research hypotheses on the performance of the Z’’-Score Model. The exploratory study is based on secondary data acquired from published sources for a period of ten years (2013 to 2022). The analysis on the basis of Altman's Z-score modification model showed that the financial position of Bharti Airtel weakened as the financial scores moved from grey zone to distress zone towards the end of the study period. But as per the other financial parameters considered in the study, the company is financially stable as the net worth is positive, revenue and market capitalization are also increasing, which is contradictory. Thus, the study highlights the need of re-evaluation of the Z’’-Score model and revising the estimation of coefficients in the model to make it viable in the present-day context for the service industry.
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Muhlis, Muhlis. "PENERAPAN MODEL Z-SCORE UNTUK PREDIKSI KEBANGKRUTAN BANK BRI SYARIAH TAHUN 2014-2016." DIKTUM: Jurnal Syariah dan Hukum 16, no. 1 (2018): 81–97. http://dx.doi.org/10.35905/diktum.v16i1.523.

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Abstract: The application of the z-score model is done to find out the early condition possible to avoid the failure of bank management when experiencing financial difficulties that will trigger potential bankruptcy if the score category is below 2.99. The method used is the Altman Z-Score model by analyzing the financial statements of PT Bank BRI Syariah from 2014-2016. Based on the results of the research conducted, the z-score in 2014 was 5.13 and 6.24 in 2015, while in 2016 it was 5.24. Altman's score results indicate that the company is free from potential bankruptcy. The debt ratio has a guarantee of very good assets. Equity is ideal in fulfilling obligations
 Abstrak: Penerapan model z-score ini dilakukan untuk mengetahui kondisi sedini mungkin menghindari kegagalan manajemen bank bila mengalami kesulitan keuangan yang akan memicu potensi kebangkrutan bila kategori skornya dibawah 2,99. Metode yang digunakan adalah model Altman Z-Score dengan menganalisis laporan keuangan PT Bank BRI Syariah dari tahun 2014-2016. Berdasarkan hasil penelitian yang dilakukan, nilai z-score tahun 2014 yaitu 5,13 dan 6,24 pada tahun 2015, sedangkan pada tahun 2016 yaitu 5,24. Hasil score Altman ini menunjukkan bahwa perusahaan bebas dari potensi kebangkrutan. Rasio utang mempunyai jaminan aktiva sangat bagus. Ekuitasnya sangat ideal dalam memenuhi kewajiban
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Masduki, Uki, Adi Rizfal Efriadi, and Ermalina Ermalina. "Kemampuan Model Z- Score dan Model Springate Dalam Memprediksi Financial Distress BPR Multi Artha Sejahtera." Jurnal Manajemen dan Keuangan 8, no. 1 (2019): 68–79. http://dx.doi.org/10.33059/jmk.v8i1.1156.

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The purpose of this study was to test the ability of the model or analytical tool used to predict the bankruptcy of the company, namely the Altman's Z-afternoon model and the Springate model of BPR Multi Artha Sejahtera whose license has been revoked by the Financial Services Authority (OJK) through Commissioner Decree Number 16 / KDK.03 / 2016 with company considerations deteriorating. The data used is secondary data, namely the 2012-2015 BPR Multi Artha Sejahtera financial report data obtained from Bank Indonesia reports. The data is then analyzed using the Altman Z-score (Z-Score) and Springate (S-Score) formulas to detect whether or not there are indications of bankruptcy before BPR Multi Artha Sejahtera is actually declared bankrupt. The results of this study concluded that overall, both Z-core and S-Score were able to predict the bankruptcy rate of BPR Multi Artha Sejahtera during 2011 - 2015. In the case of BPR Multi Artha Sejahtera bankruptcy the use of S-Score to predict bankruptcy is more appropriate in predicting bankruptcy.
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Dr., Vinay Kumar. "Predicting Financial distress of Pharmaceutical Companies in India using Altman Z Score Model." Predicting Financial distress of Pharmaceutical Companies in India using Altman Z Score Model 8, no. 10 (2023): 4. https://doi.org/10.5281/zenodo.10184222.

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The present paper aims to measure the financial distress of top five pharmaceutical companies operating in India using Altman's Z score model. This model is widely used throughout the world to identify financial distress in the company. The classical z score model is based on 5 ratios i.e. working capital to total asset ratio, retained earnings to total asset ratio, EBIT to total asset ratio, market value of equity to total liabilities and sales to total asset ratio. The study concluded that four companies fall in the Safe zone according to z score. These companies with average z score of last 5 years are Sun (9.09) pharma, Dr Reddy (7.61), Cipla (9.097) and Zydus (4.31). Thus, these companies are financially sound and may not face the problem of financial distress. Torrent pharma with average z score of 2.52 falls in Grey zone. Management needs to take immediate steps to improve the financial condition to avoid financial distress in the near future.Keywords:- Altman z score, Financial distress, Safe zone, Bankruptcy.
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Pravin, Pratik, and Drashti Anantbhai Dhabaliya. "ANALYSIS OF FINANCIAL DISTRESS USING ALTMAN'S Z-SCORE MODEL IN SELECTED INDIAN PHARMACEUTICAL COMPANIES." Journal of Advanced Research in Economics and Administrative Sciences 4, no. 4 (2023): 1–13. http://dx.doi.org/10.47631/jareas.v4i4.626.

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The necessity for financial analysis is growing as a result of industrialization, trade, and commerce. Predicting financial difficulties has become a key concern for all firms since the financial crisis happened in 2008. For assessing a company's financial health and the likelihood of insolvency, employ Altman’s Z-score model. Early bankruptcy prediction is vital for both the parties involved in the company and society. Based on their sales in the year 2021-2022, the top five pharmaceutical companies listed on the Bombay Stock Exchange were chosen as a sample for this study. The period of the study is five years, from 2017-2018 to 2021-2022. For this study, secondary data is employed. The collected data was examined by using Altman's "Z" score model in Microsoft Excel. The results show that the average Z-score for the pharmaceutical sector over the course of the study was greater than 4.5, which is significantly greater than the threshold value of 1.8 and indicates that the sector's overall financial position is satisfactory.
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Milašinović, Marko, Snežana Knežević, and Aleksandra Mitrović. "Bankruptcy forecasting of hotel companies in the Republic of Serbia using Altman's Z-score model." Menadzment u hotelijerstvu i turizmu 7, no. 2 (2019): 87–95. http://dx.doi.org/10.5937/menhottur1902087m.

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Dissertations / Theses on the topic "Altman's Z-Score Model"

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Almamy, Jeehan. "An evaluation of Altman's Z score using cash flow ratio as analytical tool to predict corporate failure amid the recent financial crisis in the UK." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13735.

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One of the most important threats for many firms today, despite their nature of the operation, size and longevity, is insolvency. Existing empirical evidence has shown that in the past two decades, business failures have occurred at a higher rate than any time since the 1930s. Many business failure studies have been conducted over time using financial ratios as inputs and traditional statistical techniques. Some of these studies examined whether cash flow information improves the prediction of business failure. Most recently, researchers have employed discriminant analysis to perform business failure prediction. The recent changes in the world caused by unstable environments where many firms fail more than ever, there is increasing need to predict business failure. To this date, there have been limited previous studies conducted on failure prediction for UK firms. Even in other countries, there has been a small amount of research done in the field of firm failures. Therefore, this study investigates the extension of Altman’s (1968) original model in predicting the health of UK firms using discriminant analysis and performance ratios to test which ratios are statistically significant in predicting the health of the UK firms .a selected sample containing 90 failed and 1000 non failed on UK industrial firms from 2000 – 2013. The main purpose of this study is to contribute towards Altman’s (1968) original Z-score model by adding new variables (Cash flow ratio). The study found that cash flow, when combined with Altman’s original variables is highly significant in predicting the health of UK general firms. A J-UK model was developed to test the health of UK firms. When compared with the re-estimated the Altman’s original model in the UK context, the predictive power of the model was 82.9%, which is consistent with Taffler’s (1982) UK model. Furthermore, to test the predictive power of the model before, during and after the financial crisis periods; results show that J-UK model had a higher accuracy to predict the health of UK firms than the re-estimated Altman’s original model. Finally, the study proves that liquidity, profitability, leverage and capital turnover ratios are significant ratios in predicting failure. Liquidity and profitability have the highest contribution to the results of both re-estimated Altman’s original model and J-UK model. This study has implications for decision makers. Regulatory bodies and practitioners have to take into account the ratios, which contributed highest to the model in order to serve as early warning signals for corrective action.
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Gega, Ilda <1995&gt. "Bankruptcy Analise of Italian Startups: Altman Z - Score Model." Master's Degree Thesis, Università Ca' Foscari Venezia, 2022. http://hdl.handle.net/10579/21660.

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The Altman Z-score model has been used to predict the bankruptcy of a company since the late 1960s. The formula, developed by Edward I. Altman, was used in this dissertation to speculate the financial distress of companies, using as a sample a certain number of Italian startups. Since the formula has been adapted over the years to different types of companies, this thesis uses the formula for privately owned companies, also called Z'. In essence, the coefficients have different values and in this model the variable X4 with the market value of equity has been replaced by the book value of equity (1983). The startups were selected based on the available data they had published in the Aida (BvD) database. The selected companies have available data to perform an analysis of at least the last five years. The methodology of selecting the companies and the way their data were analyzed are discussed and presented in the different chapters of this dissertation. At the end, conclusions are drawn by examining the figures and the results for each company.
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KITTUR, ASHA HARSHAVARDHAN. "Effectiveness of the Altman Z-Score model : Does the Altman Z-Score model accurately capture the effects of Non-Performing Assets (NPA) in the Indian banking sector?" Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-86144.

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The aim of this study is to measure the effectiveness of Altman’s Z-Score model using Non-performing assets (NPA) as a benchmark stability indicator. To do that, this paper examines if Altman’s Z Score Models capture the decline in financial health of the banks caused by the NPAs, using a two-fold analysis i.e., in advance through prediction and when the distress period is ongoing. The findings of this paper would suggest that: 1. During the distress period: The Z-Scores only marginally capture the distress caused by the NPAs, which is in line the findings of Almamy et al that the predictive ability of the model goes down during the crisis period. 2. For the future: The results of the statistical t-tests indicate that, the Z-Scores do not have the predictive ability to capture the future NPAs. Two different models that are developed by Altman - one for non-manufacturing firms and the other for the emerging markets, are used to test, if one model is more suitable than the other to the Indian banking sector. The findings of this paper suggest that, due to the uniqueness of the Indian banking sector during the NPA crisis, the ‘Emerging market model’, does not produce any significantly better results. Therefore, there is further scope to develop a tailor-made model suitable to the Indian banking sector.
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Coelho, Myles. "Predicting corporate failure: an application of Altman's Z-score and Altman's EMS models to the JSE Alternative Exchange from 2008 to 2012." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/8561.

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Includes bibliographical references.<br>The JSE Alternative Exchange (Alt-X) experienced a dramatic decline in equity values from 2008 to 2009 as part of the global economic crisis of approximately 60, and has subsequently experienced a decline of a further 50 from 2009 to 2012. By way of comparison, the JSE Main Board declined approximately 33 in 2008 and 2009, and has subsequently experienced a 100 increase in equity values from 2009 to 2012. The extent of the decline in equity values of companies listed on the Alt-X has raised the issue as to whether companies listed on the Alt-X have a higher likelihood of corporate failure. This study applies the Altman Z-Score and the Altman Z'EM score in order to identify trends in corporate solvency of Alt-X listed companies. Thereafter bond equivalent ratios are calculated for further analysis.
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Rosário, João David Claro Ferreira do. "Credit risk and banking activities." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/12580.

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Mestrado em Finanças<br>O risco de crédito para o sector bancário é um assunto muito importante. Nesse sentido, é primordial adquirir ferramentas para medir este risco com algum grau de segurança de modo a ser possível tomar as decisões corretas sobre o crédito cedido a clientes. O objetivo deste trabalho é compreender o quão importante é o risco de crédito para as instituições financeiras e apresentar uma forma de o medir associado com o crédito a empresas, analisando um modelo de score para avaliar que o mesmo seja avaliado. Este trabalho também descreve as atividades desenvolvidas nos principais departamentos de uma instituição bancária, de acordo com um estágio que teve lugar no Banco BIC, desenvolvendo desta forma uma revisão da literatura ao risco de crédito, uma descrição sobre a evolução da banca, modelos de avaliação assim como também uma análise a uma empresa, utilizando o modelo Z-Score, comparando o resultado obtido com a classificação fornecida por uma agência de rating. Os resultados provaram que o modelo em análise foi eficaz, proporcionando uma avaliação, dentro das suas limitações, de acordo com a classificação fornecida por esta agência de rating.<br>Credit risk in banking industry is a very important subject. Therefore, it is important to acquire tools to measure it, with some degree of reliability, in order to be possible to take the correct decisions regarding client loans. The objective of this final project is to understand the importance of the credit risk to financial institutions and to present a way of measuring this risk associated with loans to companies, analysing a score model to evaluate this risk. This project also describes the activities developed by the main departments of a banking institution in accordance to an internship which took place in Banco BIC, developing this way a literature review to credit risk, banking evolution and score models as well as analysing a company using the Z-Score model, comparing the results obtained with the rating provided by a rating agency. The results proved that the model under analysis was effective, providing a reliable output within its limitations, correspondingly to the rating provided by this rating agency.
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Metlik, Dan, and Sanna Jakobsson. "Konkurser utan gränser? : En utvärdering av Altmans Z´-scoremodell på företag i Sverige." Thesis, Södertörns högskola, Institutionen för ekonomi och företagande, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-10688.

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Purpose: To investigate if Altman´s Z´-score model, which calculates financial distress, can be applied on companies established in Sweden and if the financial crisis in 2008 made previously healthy companies go bankrupt. Methodology: Quantitative studies with a positivistic foundation. Empirical data will be collected in order to examine if there is generalizability among the studied objects. Conclusions will be made by comparing the empirical data with the theoretical foundation. Financial distress in firms will be measured. Theoretical perspectives: Altman´s Z´-score model, designed to predict financial distress in private firms. Empirical foundation: A selection of 93 private firms that have gone bankrupt in the years 2008, 2009 or 2010. The firms selected all have a turnover that exceeds 20 million SEK. The years examined will be 2005 to 2009. Conclusion: As this study is carried out, the conclusion is that Altman´s Z´-score model cannot be applied on companies established in Sweden.
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Yee, Hun Leek. "Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/75450.

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The framework used in this study, to predict financial distress amongst the Public Listed Companies (PLCs) in Malaysia, utilizes the 5-variables Altman’s Z-Score Model as the base model and the Auditors’ Opinion on going concern as the 6th variable. Multiple Discriminant Analysis (MDA) and Logistic Regression Analysis (LRA) have been employed, and the revised 6-variables model developed using LRA has the highest accuracy to predict financial distress amongst the PLCs in Malaysia.
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CERRI, ANDREA. "CRISIS, INSOLVENCY AND RESTRUCTURING. AN AMERICAN MODEL IN EUROPE: THE Z-SCORE. A NEW APPROACH AND POSSIBLE EVOLUTIONS." Doctoral thesis, Università Cattolica del Sacro Cuore, 2014. http://hdl.handle.net/10280/2911.

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Dopo una delle peggiori crisi economica e finanziaria mondiale , gli studi sulla previsione delle insolvenze sono diventato uno degli argomenti più dibattuti tra gli studiosi e ricercatori. Al fine di soddisfare le esigenze sia di valutazione interna sia degli investitori professionali , lo studio riscopre il modello "Z - score" di Altman nella sua forma originale , nota per la sua semplicità. Il modello, ancora largamente utilizzato nei mercati statunitensi, è per sua natura poco utilizzato nell’analisi di società europee. La tesi analizza e descrive le caratteristiche dello Z -score, valutandone i risultati come strumento per la previsione di insolvenza nel mercato europeo. Lo studio è condotto su 568 società , prese dagli indici azionari di 7 mercati europei , tra il 2000 e il 2010 . I risultati del test evidenziano una grande variabilità di risultato tra i diversi settori industriali. Il modello risulta semplice ed efficace, ma sostanzialmente incapace di prevedere il rischio di default in Europa, se utilizzato nella sua forma originale . La seconda parte della ricerca studia pertanto come i risultati del modello possano essere valutati da una nuova prospettiva per i mercati europei, concentrandosi su singoli settori industriali. Lo Z score viene testato su un campione di imprese in buona salute ed un altro di aziende insolventi, per 3 gruppi industriali diversi. La ricerca cerca anche di valutare elementi qualitativi accanto a quelli quantitativi, al fine di analizzare in maniera completa il rischio di insolvenza.<br>After one of the worst world economic and financial crisis, the insolvency prediction has become one of the most debatable topics among scholars. In order to satisfy both the professional investors’ needs and the internal evaluation process, the Thesis rediscovers the original Altman “Z-score” model, known for its convenience. This model is still largely used in the US equity markets but, also for its origin, has hardly been applied to the European equity index. The Thesis investigates and describes the operating characteristics of Altman’s Z-score, evaluating its performance as a tool for insolvency prediction in today's European market. The base model capability is tested examining 568 companies, listed in the main stock indexes of 7 European markets, between 2000 and 2010. A large variability among different industries arises from the analysis conducted. The Thesis results prove that the model is user-friendly but a substantial inability to predict the risk of default in Europe if used in its original form. The second research question try to analyse how could the model be useful for the European markets, testing the Z score over good heath and insolvent firms from 3 industrial groups. The research studies how the model’s results could be evaluated from a new perspective, focusing on individual industrial sectors results. The research also tries to evaluate qualitative elements alongside the quantitative ones, in order to give a harmonized and comprehensive estimation of the insolvency risk.
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CERRI, ANDREA. "CRISIS, INSOLVENCY AND RESTRUCTURING. AN AMERICAN MODEL IN EUROPE: THE Z-SCORE. A NEW APPROACH AND POSSIBLE EVOLUTIONS." Doctoral thesis, Università Cattolica del Sacro Cuore, 2014. http://hdl.handle.net/10280/2911.

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Dopo una delle peggiori crisi economica e finanziaria mondiale , gli studi sulla previsione delle insolvenze sono diventato uno degli argomenti più dibattuti tra gli studiosi e ricercatori. Al fine di soddisfare le esigenze sia di valutazione interna sia degli investitori professionali , lo studio riscopre il modello "Z - score" di Altman nella sua forma originale , nota per la sua semplicità. Il modello, ancora largamente utilizzato nei mercati statunitensi, è per sua natura poco utilizzato nell’analisi di società europee. La tesi analizza e descrive le caratteristiche dello Z -score, valutandone i risultati come strumento per la previsione di insolvenza nel mercato europeo. Lo studio è condotto su 568 società , prese dagli indici azionari di 7 mercati europei , tra il 2000 e il 2010 . I risultati del test evidenziano una grande variabilità di risultato tra i diversi settori industriali. Il modello risulta semplice ed efficace, ma sostanzialmente incapace di prevedere il rischio di default in Europa, se utilizzato nella sua forma originale . La seconda parte della ricerca studia pertanto come i risultati del modello possano essere valutati da una nuova prospettiva per i mercati europei, concentrandosi su singoli settori industriali. Lo Z score viene testato su un campione di imprese in buona salute ed un altro di aziende insolventi, per 3 gruppi industriali diversi. La ricerca cerca anche di valutare elementi qualitativi accanto a quelli quantitativi, al fine di analizzare in maniera completa il rischio di insolvenza.<br>After one of the worst world economic and financial crisis, the insolvency prediction has become one of the most debatable topics among scholars. In order to satisfy both the professional investors’ needs and the internal evaluation process, the Thesis rediscovers the original Altman “Z-score” model, known for its convenience. This model is still largely used in the US equity markets but, also for its origin, has hardly been applied to the European equity index. The Thesis investigates and describes the operating characteristics of Altman’s Z-score, evaluating its performance as a tool for insolvency prediction in today's European market. The base model capability is tested examining 568 companies, listed in the main stock indexes of 7 European markets, between 2000 and 2010. A large variability among different industries arises from the analysis conducted. The Thesis results prove that the model is user-friendly but a substantial inability to predict the risk of default in Europe if used in its original form. The second research question try to analyse how could the model be useful for the European markets, testing the Z score over good heath and insolvent firms from 3 industrial groups. The research studies how the model’s results could be evaluated from a new perspective, focusing on individual industrial sectors results. The research also tries to evaluate qualitative elements alongside the quantitative ones, in order to give a harmonized and comprehensive estimation of the insolvency risk.
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Protivová, Irma. "Hodnocení finanční situace podniku a návrhy na její zlepšení." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2010. http://www.nusl.cz/ntk/nusl-222416.

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The master’s thesis analyses financial health of the company Veletrhy Brno, a. s. in the years 2005 to 2008 at the basis of selected methods of the financial analysis. It comprises proposal of possible of identified problem which should result in the improvement of financial situation of the company.
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Books on the topic "Altman's Z-Score Model"

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Mutter, J. How reliable is Altman's Z score model and what are the merits of alternative approaches to corporate failure prediction?. Oxford Brookes University, 1996.

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Financial Performance of Companies Listed on the Kuwait Stock Exchange. an Exploration Using Altman's Z-Score Model. Anchor Academic Publishing. ein Imprint der Diplomica Verlag GmbH, 2016.

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Book chapters on the topic "Altman's Z-Score Model"

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Nurasik, Fitiyan Izza Noor Abidin, Eka Hasanah, and Agus Rizal. "Financial Distress Prediction Models: Altman Z-Score Approach." In Proceedings of the International Conference on Intellectuals’ Global Responsibility (ICIGR 2022). Atlantis Press SARL, 2023. http://dx.doi.org/10.2991/978-2-38476-052-7_44.

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Pérez-Pons, María E., Javier Parra, Guillermo Hernández, Jorge González, and Juan M. Corchado. "Machine Learning and Financial Ratios as an Alternative to Altman’s Z-Score Bankruptcy Model in Spanish Companies." In Decision Economics: Minds, Machines, and their Society. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75583-6_13.

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Shree, Nithya, and Durai Selvam. "Prediction of bankruptcy of Indian manufacturing companies (construction) using Zmijewski model and Altman Z score." In Advances in Management Research. Routledge, 2022. http://dx.doi.org/10.4324/9781003366638-9.

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Xu, Xinyi. "Application of Altman Z-score Model in Credit Risk Assessment of Light Industry in China." In Proceedings of the 2022 2nd International Conference on Financial Management and Economic Transition (FMET 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-054-1_12.

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Priyanto. "Financial Distress Analysis by Using Altman Z-Score Methods: A Case Study of Selected Fertilizer Company in Indonesia Year 2016–2020." In Proceedings of the 19th International Symposium on Management (INSYMA 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-008-4_6.

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AbstractThis study aims to analyze financial distress conditions in PT XYZ. This private company produces chemicals and fertilizers in Indonesia and sells them in Indonesia and globally. PT XYZ is chosen because it is Indonesia's biggest and most complete fertilizer industry. This study used secondary data taken from the business enterprise’s economic statements on the company’s official website from 2016 to 2020. The Altman Z-Score model for production non-public corporations is set as the method used. The study used many ratios to calculate financial distress, working capital ratio (ratio between working/operational capital and total/overall assets), retained earnings ratio (retained earnings divided by total assets), EBIT (ratio between earnings before interest and tax and total assets), and also ratio between the book value of the equity and total liabilities.
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Thabit, Mohsen Younis, and Bushra Najem Aubdullah Al-Mashhadani. "Forecasting the Financial Failure of Iraqi Banks Listed on the Stock Exchange Using Altman Z''-Score Model." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-84628-1_18.

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Padmaja, R., and R. S. Ch Murthy Chodisetty. "Role of financial soundness of banking industry in India by using Altman Z-score model with special reference to Canara Bank — Empirical evidence." In Digital Transformation and Sustainability of Business. CRC Press, 2025. https://doi.org/10.1201/9781003606185-183.

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Thomas, Dany, Ria Mammen, Vimal George Kurian, and S. P. Asha. "Dynamics of Financial Risk on the Effect of Sustainable Practices on Financial Performance." In Advances in Logistics, Operations, and Management Science. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3880-3.ch011.

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The study examine the influence of financial risk on the nature of the relationship between ESG and the financial performance of Indian banks. In India, loans are key financial products of banks that are exposed to carbon-intensive sectors, which hinder their efforts to mitigate against transition risks and global ESG standards, amid the growing pressure from international investors. The study uses ROA to measure financial performance. The independent variable ESG was measured using the ESG scores Indian banks indexed in the NIFTY 100 ESG Index. Altman's Z-score model which predicts the financial risk of Indian banks was considered as the mediating variable to assess its influence on the nature of the relationship between ESG and financial performance. The evidence from the study would be useful to identify the changes in the financial performance of Indian banks resulting from their sustainable performance.
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Gidiş, İnan. "Financial Stability and Credit Risk in Turkish Participation Banks: A Comparative Analysis." In Finansal Piyasaların Evrimi IV. Özgür Yayınları, 2023. http://dx.doi.org/10.58830/ozgur.pub395.c1723.

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This paper delves into the evolving landscape of Islamic finance in Türkiye, where Participation Banks (PBs) adhere to Islamic law and ethical principles, setting them apart from Conventional Banks (CBs). The unique nature of PBs demands tailored assessments of their financial health. The primary objective is to evaluate the financial stability and credit risk of Türkiye's PBs through a comparative analysis with CBs. The study employs the Non-Performing Loans (NPL) ratio in conjunction with the Emerging Market (EM) Score model—a modified version of Altman's Z-Score which is widely used in predicting the bankruptcy of firms including banks. The combination provides a comprehensive evaluation and a deeper understanding of financial stability.&#x0D; Focused on six major PBs—Kuveyt Türk, Albaraka Türk, Türkiye Finans, Ziraat, Vakıf, and Türkiye Emlak—the methodology entails collecting and analyzing financial data from official sources, including the Participant Banks Association of Turkey (TKBB) and the Banking Regulation and Supervision Agency (BRSA).&#x0D; Anticipated outcomes include enhanced decision-making and the development of robust risk management strategies for Turkish PBs, reinforcing their financial stability. The comparative analysis with CBs aims to unveil competitive advantages and unique challenges, offering valuable insights for policymakers, regulators, and stakeholders in the Turkish banking sector.
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Holpus, Hardo, Ahmad Alqatan, and Muhammad Arslan. "Investigating the Viability of Applying a Lower Bound Risk Metric for Altman’s z-Score." In 21st Century Approaches to Management and Accounting Research [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97433.

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The study aimed to build a risk metric for finding the lower boundary limits for Altman’s z-score bankruptcy model. The new metric included a volatility of Altman’s variables and predicted the riskiness of a firm bankrupting in adverse situations. The research examined whether the new risk metric is feasible and whether it provides satisfying outcomes compared to Altman’s z-score values during the same period. The methods to conduct the analysis were based on Value at Risk methodology. The main tools used in constructing the model were Monte Carlo simulation, Lehmer random number generator, normal and t-distribution, matrices and Cholesky decomposition. The sample firms were selected from FTSE 250 index. The important variables used in the analysis were all Altman’s z-score variables, and the period under observation was 2001–2007. The selected risk horizon was the first quarter of 2008. The first results were promising and showed that the model does work to the specified extent. The research demonstrated that Altman’s z-score does not provide a full and accurate overview. Therefore, the lower bound risk metric developed in this research, produces valuable supplementary information for a well-informed decision making. To verify the model, it must be back- and forward tested, neither of which was carried out in this research. Furthermore, the research elaborated on limitations and suggested further improvement options for the model.
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Conference papers on the topic "Altman's Z-Score Model"

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Almamy, Jeehan. "An Extension of Altman's z-Score Model as an Analytical Tool to Predict the Financial Health of UK Companies." In Eighth Saudi Students Conference in the UK. IMPERIAL COLLEGE PRESS, 2015. http://dx.doi.org/10.1142/9781783269150_0012.

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Pelloneová, Natalie, and Vladimíra Hovorková Valentová. "Financial Health of Cluster Organisations: A Case Study from the Czech and Slovak ICT Industry." In Liberec Economic Forum 2023. Technical University of Liberec, 2023. http://dx.doi.org/10.15240/tul/009/lef-2023-55.

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This paper analyses the financial health of firms that are members of selected cluster organizations operating in the Czech and Slovak Republics. The research includes two research samples, which are member firms of cluster organizations IT Cluster and Košice IT Valley. Both of the above-mentioned cluster organizations were established as a result of a cluster initiative and associated entities from the ITC sector. The firms that form the cores of the above-mentioned cluster organizations are mostly active in the sectors with the following statistical classification: NACE 620100, 620200, and 620900. The main objective of the present research is to analyze selected financial health indicators of member firms of both cluster organizations and to determine whether or not there are significant differences in the development of selected financial indicators between individual firms. To achieve the objective, the profitability ratios and Altman's Z´´score model were used. The research results are discussed in the conclusion of the paper.
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Prasetiyo, Yudhi, Etik Ipda Riyani, Yeni Widiastuti, and Putri Agustina. "Altman Z-Score Models and Financial Distress." In Proceedings of the 5th International Public Sector Conference, IPSC 2023, October 10th-11th 2023, Bali, Indonesia. EAI, 2023. http://dx.doi.org/10.4108/eai.10-10-2023.2342214.

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Jagannathan, Sharath Kumar, Gulhan Bizel, and Hulya Alpagu. "Predicting Bankruptcy of Companies in the Pharmacy and Technology Sectors Using Altman’s Z-score model." In 2023 6th International Conference on Recent Trends in Advance Computing (ICRTAC). IEEE, 2023. http://dx.doi.org/10.1109/icrtac59277.2023.10480832.

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Kiaupaite-Grushniene, Vaiva. "Altman Z-Score Model for Bankruptcy Forecasting of the Listed Lithuanian Agricultural Companies." In 5th International Conference on Accounting, Auditing, and Taxation (ICAAT 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/icaat-16.2016.23.

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Damayanti, Santi. "Does the Analysis of Altman Z-Score Model, Zmijewski Model, and Springate Model Impact the Financial Distress?" In 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020). Atlantis Press, 2021. http://dx.doi.org/10.2991/aebmr.k.210831.015.

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Liodorova, Julija, and Irina Voronova. "Z-score and P-score for bankruptcy fraud detection: a case of the construction sector in Latvia." In Contemporary Issues in Business, Management and Economics Engineering. Vilnius Gediminas Technical University, 2019. http://dx.doi.org/10.3846/cibmee.2019.029.

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To protect investment and ensure repayment of payables, recent studies have focused on identifying the relationships between company bankruptcy and internal fraud. The P-score model that is based on the most popular Altman Z-score model has been developed to indicate the manipulation of financial statements. Purpose of the study is to determinate the accuracy and the feasibility of P-score and Z-score models to detect fraudulent bankruptcy in regional conditions, based on reports of the Latvian construction companies that failed due to fraud, and during the verification of other known data. Research methodology is based on the background studies of P-score testifying, applying this approach to the Latvian condition. The present study analyzes the behaviour of the two models in identifying distress and fraud. To testify the results of the study, the authors use the financial analysis methods, comparison, statistical and quantitative research methods. Findings have shown the possibility of using the P-score and Z-score technique for bankruptcy fraud detection at the Latvian companies, based on the construction sector samples. The accuracy of the method is above 80%. Research limitations – acquisition a large amount of data on companies that are in the process of analytical studies on the recognition of their insolvency and having signs of fraud is not possible due to the confidentiality of information. Practical implications – the results of the study may be applicable to the audit of the company, investment reliability assessment, partnership evaluation and economic examination to detect fraud. Originality/Value of the study is the first test of practical implication of P-score model in Latvia and the Baltic countries on the samples of small and medium-sized construction companies. The authors propose improving the coefficients of the P-score model taking into account the requirements for financial statements in Latvia
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Mugozhi, Farirepi, and Anyway Ngirazi. "AN ASSESSMENT OF THE APPLICATION AND THE CORPORATE FAILURE PREDICTIVE VALUE OF ALTMAN’S Z-SCORE MODEL IN ZIMBABWE." In Annual International Conference on Accounting and Finance (AF 2016). Global Science & Technology Forum ( GSTF ), 2016. http://dx.doi.org/10.5176/2251-1997_af16.79.

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Barbullushi, Erjole, and Blerta Dragusha. "ALTMAN Z-SCORE REVISED MODELS AS EARLY WARNING SYSTEMS FOR BANKRUPTCY EVALUATION OF ECONOMIC ENTITIES ​." In 4th International Scientific Conference: Knowledge based sustainable economic development. Association of Economists and Managers of the Balkans, Belgrade, Serbia et all, 2018. http://dx.doi.org/10.31410/eraz.2018.873.

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Hundal, Shab, and Anne Eskola. "Financial accounting manipulations and bankruptcy likelihood: A study of Nordic banks." In Corporate governance: Fundamental and challenging issues in scholarly research. Virtus Interpress, 2021. http://dx.doi.org/10.22495/cgfcisrp13.

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The phenomena of accounting manipulations and bankruptcy likelihood have always been a topic of interest among researchers. The key objective of the current study is to examine the impact of fraudulent accounting practices on the likelihood of bankruptcy, and the performance of firms. Beneish M-score model and Jones model have been applied to evaluate earnings quality, whereas the Altman Z-score model has been used to analyze the level of financial distress. Based on the analysis of secondary data collected from 33 Nordic banks for the period 2011–2018, the findings disclose that Z-score of most of the sample banks has been found to be relatively high thus representing their high level of financial health. The study does not rule out potential earnings management measures applied by the sample banks. Furthermore, earnings manipulations increase the bankruptcy likelihood, especially in case of larger banks. The financial data manipulation practices artificially enhance the financial performance of banks, however, in a broad perspective; such manipulations can trigger potential financial distress
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