Corporate Solvency and Bankruptcy Detection and Predictions

The study aims to examine the impact of liquidity and solvency management on the financial performance of Jordanian manufacturing companies listed on the Amman Stock Exchange, for a period of 10 years from 2010 to 2019. The size of the company was used as a control variable. The study employs Return on Assets (ROA) and Earnings Per Share (EPS) to measure financial performance. Current ratio (CR) and total debts to total assets were used as proxies for liquidity and solvency management, while logarithm of total assets was used to measure the size. Correlation and multi regression analyses have been applied to analyze the data. The results show a statistically significant impact of independent and control variables (liquidity and solvency management and the size of the company) on financial performance, while the detailed results of the hypotheses indicate that liquidity has an insignificant reverse impact on financial performance. With respect to other variables, there is a significa...

Financial insolvency is important for sustainable national growth. This can be resolved through liquidity management, which is very important in any organization in terms of the organization's current assets, current liabilities, shortterm borrowings, and management of shortfall or surplus cash for short-term periods, which affects the company's profitability. Liquidity management should be the company's goal of working capital management. Such idle cash can be used to invest in another company or diversifiable venture that are profitable. Accounting software or accounting information system is a resolution to financial insolvency in which it captures and records the financial effects of transactions. Accounting Information System (AIS) assists managers in four problem-solving stages, which are recognizing the problem, identifying alternatives, assessing the alternatives and taking managerial decision. The methodology employed for this study is Meta-analysis. The sample size employed was 30 literatures. The overall combined relationship had a P-value of .0000 indicating an overall significant level. Insolvency practice and its regulation is critical to economic development. This is especially true in the light of the unintended consequences of globalisation that may result in economic shock and business failures. Nigeria can benefit from reforms in financial insolvency by benchmarking the reform and practice initiatives of the more advanced countries within and outside Africa.

The main objective of this study is to analyze the "pieces" that support the construction of a bankruptcy policy, aiming to identify those that allow building a bankruptcy policy which will help in the recovery from the economic COVID crisis, as well as to build a winning policy in the economic competition between countries. To promote this purpose is observed the impact of bankruptcy policy on the entire economic cycle, allowing to understand that, more than intervening companies at the "end of life", bankruptcy policy impacts on the everyday life of a company, even before its establishment. Subsequently, identifying the characteristics of the ex ante, interim, and ex post efficiencies of a bankruptcy policy, it is analyzed how it can be built one aiming at its maximum efficiency. Finally, the main variables of bankruptcy policy are analyzed, aiming to understand its real implications, sometimes even dual, in the efficiency of this policy.

Bankruptcy prediction studies lack a strong theoretical framework but were driven by empirical testing and exploration of new econometric models to identify potential bankrupt firms. This paper examines this phenomenon by reviewing existing literatures and proposed a theoretical framework to govern the direction and future development of this area of finance. Liquidity, Profitability and Wealth Theory, Cash Flow Theory, Merton Model, &Gambler's Ruin Theory were investigated. Liquidity, Profitability and Wealth theory was discovered to be most popular.

Credit card fraud occurs when user provides their information to the unknown persons or stolen by the unknown persons, that information can be used for unauthorized online purchase and some other situation. Data mining techniques are employed to study the patterns and characteristics of normal and abnormal transactions based on normalized and anomalies data. In order to detect fraud activities and feature patterns associated with financial activities, we are proposing novel fraud detection framework, Codetect. Wide variety of applications is associated with anomaly detection such as fraud detection and network intrusion detection which referees to pattern finding problems in data.

Cartea reflectă rezultatele unor cercetări monofactoriale privind potențialul ratelor financiare în evaluarea riscului de insolvență asociat întreprinderii. Studiul realizat are la bază cel mai mare eșantion utilizat în acest domeniu în România (și unul dintre cele mai mari eșantioane utilizate în cercetările în domeniu la nivel mondial). Rezultatele indică potențialul, dar și limitele fiecărei rate financiare individuale în evaluarea riscului de insolvență cu 2 ani înainte de eventuala producere a evenimentului. Metodologia propusă este aplicabilă întreprinderilor românești. Bazându-se exclusiv pe date disponibile online, aceasta este facil de utilizat. Informațiile prezentate se adresează cu precădere practicienilor în domeniul insolvenței și specialiștilor în domeniul analizei financiare.

Il saggio si concentra sulla liceità ed efficacia del trust qualora questo sia utilizzato nell’ambito della crisi d'impresa. L’Autore, dopo aver esaminato l’utilità del trust in rapporto ai vari strumenti di composizione negoziale della crisi, fornisce una lettura innovativa del leading case costituito dalla Cass. n. 10105/2014. In particolare, osserva che ai fini della riconoscibilità di tale istituto in ambito concorsuale perda rilevanza la sussistenza dello stato d’insolvenza al momento dell’istituzione del trust, a favore di una sempre maggiore importanza della sua causa in concreto. Quindi, dato il rilievo assunto dalla valutazione del concreto programma di segregazione patrimoniale, l’Autore esamina i possibili indici di elusività del trust, traendo spunto dalla prassi giurisprudenziale. Infine, in chiave di tutela dei creditori, sono analizzate le questioni attinenti l’azione revocatoria e la sorte del trust in caso di sopravvenuto fallimento.

Le disposizioni contenute nel Reg. n. 848 sulle procedure di insolvenza transfrontaliere e, se infine promulgata, nella Direttiva sugli strumenti di allerta, di ristrutturazione preventiva e sulla seconda opportunita` si pongono su una linea di continuita` con l’impostazione del diritto UE nel settore, ma offrono anche novita` di grande rilievo. Prima tra tutte, e` l’estensione dell’ambito di applicazione del Regolamento cit. a procedure escluse dalla previgente disciplina – ed, in particolare, a quelle fondate sulla ‘‘probabilita` di insolvenza – accompagnata da una serie di norme di nuovo conio volte ad esplicitare regole di coordinamento e di cooperazione tra le procedure aperte in piu` Stati membri. Il quadro che ne emerge e` molto complesso e richiede ampie indagini comparate allo scopo di comprenderne appieno la portata. La successiva Proposta di Direttiva interviene su alcune procedure soltanto, ma impone agli Stati membri di affrontare in ottica di mercato interno UE anche il regime delle procedure nazionali. Dalla combinazione dei due strumenti si sviluppera` un approccio senza dubbio piu` sistematico al problema delle insolvenze nel territorio UE, che imporra` ai legislatori nazionali nuove riforme dopo le tante gia` approvate nell’ultimo decennio in molti paesi (Italia, Francia, Spagna, Belgio, ecc.). In Italia, in particolare, le nuove norme UE dovranno costituire elemento di riferimento nell’attuazione della delega contenuta nella L. 19 ottobre 2017, n. 155, che dovrebbe condurre ad un ampio rinnovamento della disciplina concorsuale.

"El volumen se dedica al análisis de la disciplina normativa de los Estados europeos en materia de sobreendeudamiento e insolvencia de las personas naturales, materia ésta relacionada a su vez con el vertiginoso aumento del crédito al consumo; todo ello en un momento en que gradualmente va tomando forma en Europa una especie de “Derecho concursal civil” (?), centrado en la gura del Ciudadano privado.
El ordenamiento jurídico comunitario, tanto desde una perspectiva general como desde la perspectiva singular que aportan las respectivas legislaciones de los Estados miembros, presenta cierto décit regulatorio desde la perspectiva de la mejor tutela de familias y consumidores endeudados en exceso. Esta insuciencia, tanto por sí misma como en combinación con otras disfunciones, sigue inuyendo en el colapso economico-nanciero de una Europa condicionada por una excepcional coyuntura económica cuyas dimensiones aún no son exactamente apreciables.
El volumen se propone contribuir a la identicación de las ineciencias de fondo que subyacen en el actual sistema jurídico comunitario desde la perspectiva que ofrecen los “ajustes” considerados más oportunos."

A Lei de Recuperação e Falências passa por momento de transição. Se, por um lado, a Lei representou grande avanço em relação ao sistema falimentar anterior, com efeitos positivos sobre o Judiciário e o mercado de crédito, por outro, há novos desafios que precisam ser enfrentados na área da insolvência – questão que gera novo ímpeto reformista.

O presente trabalho, em uma abordagem empírica e interdisciplinar, avalia fatores macro e microeconômicos que impactam a sobrevivência de empresas no Brasil e como essas práticas se coadunam (ou não) com os objetivos e princípios sobre os quais o Direito Falimentar nacional atual foi fundado.

Espera-se que os resultados reportados na presente obra possam contribuir para a tomada de decisão dos agentes envolvidos em reorganizações empresariais, para a discussão jurídica e econômica da efetividade do diploma falimentar nacional e, eventualmente, para informar alterações legislativas que vierem a ser debatidas.

Default by corporate is problem of concern for banking and financial services industry along with economy. Timely prediction of default is imperative for the bankers and regulators to devise and take preventive actions. There has been large numbers of studies across the world and in India too few studies conducted for Indian data. An extensive review of literature reveals that the subject of default prediction has not explored much in India. In India along with rest of the world, the numbers of defaults have been increasing every year. This creates scope for further studies.
A comparative study has been conducted on the data of three countries, namely India, the US and the UK using four methods; MDA, logit, reduced form and structural models. The study for the Indian sample has developed 24 models for three methods; MDA, logit and reduced form model for two sample periods large sample period and small sample period on a sample of 2450 case over ten years from 1st April 2004 to 31st March 2014 and on two years data from 1st April 2014 to 31st March 2016, the developed models have been validated for the forward period as well as for the out of sample firms. Structural model has been tested on Indian data. The study for the American sample has developed three models for the three methods; MDA, logit and reduced form model. Structural model has been tested on American data. The study for the British sample has developed three models for the three methods; MDA, logit and reduced form model. Structural model has been tested on British data. So in this study total 30 models have been developed.
The study uses multiple discriminant analysis and logistic regression analysis to calculate composite scores which are used to predict default. The structural model uses option mathematics to give probability of default with help of market value of assets, book value of debt and asset drift rate. Reduced form model uses Poisson regression to estimate intensity of default which is transformed into probability of default.
The findings of the study for Indian sample suggest that logit model yields the highest classification accuracy of 97.7% and reduced form model yields the lowest classification accuracy of 82.3%. The models for small sample period are robust but classification accuracies for the models for large sample period are higher for different methods. The classification accuracies of 24 developed models for Indian sample has higher than many studies conducted in India and other countries. The findings of the study on American sample suggest that logit model yields the highest classification accuracy of 95% and structural model yields the lowest classification accuracy of 85.9% and classification accuracies of developed models higher than many studies. The findings of the study on British sample suggest that structural model yields the highest classification accuracy of 81.6% and reduced form model yields the lowest classification accuracy of 67.9%.
The findings on variables suggest that all the three types of variables namely accounting, market and economic variables are significant for all the three samples from India, the US and the UK. In case of India, it is observed that all the variables which are significant for large sample period are significant for small sample period indicating the in long run firms tend to follow a certain pattern and default can be predicted with the help of a set of certain variables as far as default predict is concerned. However in short run market variables seem play minor role in default prediction. From the analysis of variables it is evident that total book value of debt with respect to total assets is the most important variable among all the variables with debt component. The biggest limitation of this study is that the models for small sample period are more robust while the models for large sample period have higher classification accuracy. The whole study is facing the problem of sample and selection biases.

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The comparison was carried out on a sample of 90 companies operating in the Slovak Republic over a period of 3 years (2016, 2017, and 2018) with a narrower focus on three sectors: construction, retail, and tourism, using alternative default prediction models, such as CH-index, G-index, Binkert’s Model, HGN2 Model, M-model, Gulka’s Model, Hurtošová’s Model, Model of Delina and Packová, and Binkert’s Model. To verify the reliability of these models, tests of the significance of statistical hypotheses were used, such as type I and type II error. According to research results, the highest reliability and accuracy was achieved by an alternative local Model of Delina and Packová. The least reliable results within the list of models were reported by the most globally disseminated model, Altman’s Z-score. Significant differences between sectors were identified.

The study aims to examine the impact of liquidity and solvency management on the financial performance of Jordanian manufacturing companies listed on the Amman Stock Exchange, for a period of 10 years from 2010 to 2019. The size of the company was used as a control variable. The study employs Return on Assets (ROA) and Earnings Per Share (EPS) to measure financial performance. Current ratio (CR) and total debts to total assets were used as proxies for liquidity and solvency management, while logarithm of total assets was used to measure the size. Correlation and multi regression analyses have been applied to analyze the data. The results show a statistically significant impact of independent and control variables (liquidity and solvency management and the size of the company) on financial performance, while the detailed results of the hypotheses indicate that liquidity has an insignificant reverse impact on financial performance. With respect to other variables, there is a significant positive impact of size on performance and a significant negative impact of solvency on performance. The study suggests in light of results, increasing investments in companies' assets by focusing on internal financing, such that large-sized companies with low leverage will have a good performance.

Bankruptcy prediction is very important for all the organization since it affects the economy and rise many social problems with high costs. There are large number of techniques have been developed to predict the bankruptcy, which helps the decision makers such as investors and financial analysts. One of the bankruptcy prediction models is the hybrid model using Fuzzy C-means clustering and MARS, which uses static ratios taken from the bank financial statements for prediction, which has its own theoretical advantages. The performance of existing bankruptcy model can be improved by selecting the best features dynamically depend on the nature of the firm. This dynamic selection can be accomplished by Genetic Algorithm and it improves the performance of prediction model. .

En proclamant le 26 août 1789 que «Les hommes naissent libres et égaux en droit», les signataires de la Déclaration des droits de l'homme et des citoyens, inspirés par la philosophie des Lumières, mettaient un terme à une législation d'Ancien Régime entravant la liberté individuelle. En abolissant les corporations professionnelles et les prescriptions religieuses qui encadraient la liberté contractuelle, les révolutionnaires souhaitaient faire de l'homme et de sa volonté la source du droit contractuel. Le principe de l'autonomie de la volonté, transcrit quinze ans plus tard à l'article 1134 du Code civil, fait de la volonté des parties la source essentielle du droit des conventions. Le contrat, expression de la volonté de l'individu, y est élevé au même rang que la Loi, expression de la volonté collective. L'intervention de l'État dans le domaine économique est cantonnée ; le contenu des contrats n'est plus soumis à son approbation et il ne peut plus intervenir pour en modifier les termes.

To improve credit risk management, there is a lot of interest in bankruptcy predictive models. Academic research has mainly used traditional statistical techniques, but interest in the capability of machine learning methods is growing. This Italian case study pursues the goal of developing a commercial firms insolvency prediction model. In compliance with the Basel II Accords, the major objective of the model is an estimation of the probability of default over a given time horizon, typically one year. The collected dataset consists of absolute values as well as financial ratios collected from the balance sheets of 14.966 Italian micro-small firms, 13,846 ongoing and 1,120 bankrupted, with 82 observed variables. The volume of data processed places the research on a scale like that used by Moody's in the development of its rating model for public and private companies, Riskcalc TM. The study has been conducted using Gradient Boosting, Random Forests, Logistic Regression and some deep learning techniques: Convolutional Neural Networks and Recurrent Neural Networks. The results were compared with respect to the predictive performance on a test set, considering accuracy, sensitivity and AUC. The results obtained show that the choice of the variables was very effective, since all the models show good performances, better than those obtained in previous works. Gradient Boosting was the preferred model, although an increase in observation times would probably favour Recurrent Neural Networks.

In IPC is a situation which trader or company is not able pay its dept. and can't fulfill the Business Commitment. Gitman believes that, bankruptcy happens in situations when the dept. of a company is more than the assets value. So one of the critical factors for Investors who decide to invest is predicting the bankruptcy. Prediction of bankruptcy can be done using many methods that among them ratio analysis method and the analysis of market risk method are the most validated methods. In analysis of market risk method, the probability of bankruptcy is estimated through the changes in market risk. In ratio analysis method the probability of bankruptcy is estimated through a group of financial report that are combined by scholars. In recent years Academic research communities have been trying to predict bankruptcy more exact that these different models for predicting bankruptcy arr including: (William, Altman, D.kin, spin gate ...)

Recent literature tried to explain the Indian growth miracle in different ways, ranging from trade liberalization to industrial reforms. Using data on Indian manufacturing firms, this paper analyzes the relationship between firm's productivity and export market participation during 1991–2004. While it provides evidence of the self-selection hypothesis by showing that more productive firms become exporters, the results do not show that entry into export markets enhances productivity. The paper examines the explanation of self selection hypothesis for total factor productivity differences across 33,510 exporting and non-exporting firms. It uses propensity score matching to test the learning-by-exporting hypothesis. In line with the prediction of recent heterogeneous firm models of international trade, the main finding of the paper is: more productive firms become exporters but it is not the case that learning by exporting is a channel fuelling growth in Indian manufacturing.

In practice, one chosen method is generally used to solve classification tasks. Although the most modern procedures yield excellent accuracy rates, international research findings show that a concurrent (ensemble) application of methods with weaker classification performance achieves comparable rates of high accuracy. This article’s main objective is to compare the predictive power of the two ensemble methods (Adaboost and Bagging) most commonly used in bankruptcy prediction, using a sample consisting of 976 Hungarian corporations. The article’s other objective is to compare the accuracy rates of bankruptcy models built on the deviations in specific financial ratios from industry averages to those of models built on financial ratios and variables factoring in their dynamics.

This study assesses the classification accuracies of two statistical methods namely, multiple discriminant analysis and logistic regression approach in default prediction. It uses a small sample of 32 India firms listed on Bombay Stock Exchange for the sample period of six years over 2010-11 to 2015-16. Two models have been built using the two statistical methods. Results of the study clearly indicate that there are no significant differences in the classification accuracies because of change in statistical methods. Different statistical measures clearly suggest that the two developed models have comparative classification accuracies in default prediction. However, the specification and robustness of logit model is found to be on lower side than that of the discriminant model contrary to large numbers of studies. The weaker model specification of logistic model may be result of small sample size.

The article attempts to synthesize the historical development tendencies of theoretical approaches, methodologies and empirical researches of corporate survival and bankruptcy prediction, laying emphasis on the 30-year development history of Hungarian empirical bankruptcy prediction models. Based on the historical development of Hungarian bankruptcy prediction it can be argued that it has already caught up to the level of international best practice regarding the examined research problems, applied methods and empirical results. Throughout the development history of Hungarian bankruptcy prediction it can be tracked, how the initial, small, cross-sectional sample and classical methodology based bankruptcy prediction has evolved to today's corporate rating systems meeting the requirements of the dynamic, through-the-cycle economic capital calculation models. Contemporary methodological development is characterized by the domination of artificial intelligence, data mining, machine learning and hybrid modelling. The article reveals that Hungarian bankruptcy models are necessary to accomplish efficient bankruptcy prediction in Hungary. Throughout model development, it is essential to consider the sampling problems, the definition of target variable, the proper accomplishment of data preparation and data transformation steps, the dynamization of variables and the inclusion of behavioural variables. In addition the article draws several normative proposals how to select the right bankruptcy prediction method(s).

Il Tribunale Torino, sez. fall., 25 gennaio 2017 interviene in materia di obblighi informativi volti a correggere l’asimmetria informativa dei creditori e ad evitare possibili abusi dello strumento concordatario. Il provvedimento è particolarmente interessante in quanto prevede che decorsi trenta giorni dalla comunicazione dello stesso e ogni trenta giorni successivi, il debitore depositi in cancelleria una situazione finanziaria aggiornata dell’impresa, che la cancelleria dovrà pubblicare sul registro delle imprese entro il giorno successivo, trasmettendone una copia informativa ed esplicativa redatta dal suo legale, sullo stato di predisposizione della proposta definitiva nonché sulla gestione corrente, anche finanziaria, allegandovi l’elenco delle più rilevanti operazioni compiute, sia di carattere negoziale, che gestionale, industriale, finanziario o solutorio, con l’indicazione della giacenza di cassa e delle più rilevanti variazioni di magazzino.

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The comparison was carried out on a sample of 90 companies operating in the Slovak Republic over a period of 3 years (2016, 2017, and 2018) with a narrower focus on three sectors: construction, retail, and tourism, using alternative default prediction models, such as CH-index, G-index, Binkert’s Model, HGN2 Model, M-model, Gulka’s Model, Hurtošová’s Model, Model of Delina and Packová, and Binkert’s Model. To verify the reliability of these models, tests of the significance of statistical hypotheses were used, such as type I and type II error. According to research results, the highest reliability and accuracy was achieved by an alternative local Model of Delina and Packová. The least r...

Development in science has enabled the improvement of bankruptcy prediction models through several data-driven and artificial intelligence based methods. One of such promising methods might be the Case-Based Reasoning (CBR) method. The aim of this article is to consider the applicability of CBR on a sample of Hungarian micro enterprises, within the framework of classic bankruptcy prediction, by comparing the classification power of CBR to the three most frequently applied bankruptcy prediction techniques (decision tree, logistic regression, neural networks). The empirical research examined the occurrence of bankruptcy events (initiating bankruptcy, liquidation or forced deregistration procedure) for 1.828 Hungarian micro enterprises in 2017 using financial ratios calculated from 2015 and 2016 annual reports. On the whole it can be concluded that it is worthwhile to consider CBR methodology in solving classification problems similar to bankruptcy prediction. However, on the basis of the empirical research, the predictive power of the developed CBR model underperformed the accuracy of neural networks and logistic regression on observations in the testing sample.

For some time, it was an open secret to all that Jet Airways is a debt ridden company and unable to even service the debt both in short term as well as long term. Being a full-fledged airline, it has very high operational costs in comparison to many other airlines operating in India. Apart from this, at present there are no pilots or any crew members who could help to fly its planes back in the air because the firm has failed even to pay the salaries to its staff for long. On the other hand, the lenders have already declined to provide any relief by lending with the emergency fund of Rs 1,200 crores even after giving assurance for the same. Also there are thick rumours in the air that employees are planning to go to the court to recover their dues. These circumstances altogether make it even more difficult for Jet Airways to hit back in the air.

En este estudio se formulan y estiman modelos logit de predicción de insolvencia combinando ratios contables de una muestra de empresas fracasadas y no fracasadas. La finalidad es contribuir a la formulación de una teoría sobre el fracaso empresarial incorporando, además de aquellos indicadores financieros que han funcionado bien en estudios empíricos previos, los ratios procedentes del modelo económico-financiero de solvencia empresarial Modelo contrastado en numerosos trabajos de investigación con empresas individuales. Los resultados obtenidos indican que los modelos estimados clasifican y predicen correctamente la insolvencia y que algunos de los indicadores propuestos por el modelo teórico contribuyen a la significación estadística y aumentan la capacidad predictiva de dichos modelos.

Banking historiography often does not sufficiently take into account bankers’ deliberations of their decision making, but rather limits investigation to considerations of profit maximisation. This book shows that the decision-making processes of nineteenth-century bankers contemplating high-risk financial markets like Greece are just as complex as present-day investment decisions.

The book, now published in English after a first German edition, offers in-depth studies of decision making in concrete historical situations, considering political and economic circumstances and also the individual background of the actors concerned, including a reflection on the influence of cultural movements such as Philhellenism. Employing methodological inspirations from the field of behavioural finance, the book analyses a broad range of published and unpublished English, French, Greek, German and Swiss sources on European investment in Greece between 1821 and the Balkan wars. Additionally, rich insights into Greek economic history, the economic integration of the country into Europe and long-lasting European stereotypes of Southern Europe and Greece are provided; this furthers understanding of the historical background of the Greek financial crisis after 2009.

In combining the perspectives of financial, economic, political and cultural history, this book is primarily significant for students of various fields of historiography. Due to its strong awareness of methodological questions, it is also of great interest to academic historians. In addition, the strong public interest in the Greek financial crisis after 2009 and its consequences for Europe will, thirdly, attract the interest of a broader public.

The study aims to examine the impact of liquidity and solvency management on the financial performance of Jordanian manufacturing companies listed on the Amman Stock Exchange, for a period of 10 years from 2010 to 2019. The size of the company was used as a control variable. The study employs Return on Assets (ROA) and Earnings Per Share (EPS) to measure financial performance. Current ratio (CR) and total debts to total assets were used as proxies for liquidity and solvency management, while logarithm of total assets was used to measure the size. Correlation and multi regression analyses have been applied to analyze the data. The results show a statistically significant impact of independent and control variables (liquidity and solvency management and the size of the company) on financial performance, while the detailed results of the hypotheses indicate that liquidity has an insignificant reverse impact on financial performance. With respect to other variables, there is a significant positive impact of size on performance and a significant negative impact of solvency on performance. The study suggests in light of results, increasing investments in companies' assets by focusing on internal financing, such that large-sized companies with low leverage will have a good performance.

A Covid 19 vai deixar atrás de si uma crise inédita diferente da Grande Depressão da bolha das dotcom ou da Grande Recessão É cedo para perceber quais e quantas empresas irá condenar mas já há sinais. Os enormes apoios estatais vão salvar muitas mas as companhias aéreas e retalhistas tradicionais estão entre as mais expostas e que já caem.