Underpricing and Long-Term Performance of Ipos: Evidence From European Intermediary-Oriented Markets

Gandolfi, Gino; Regalli, Massimo; Soana, Maria Gaia; Arcuri, Maria Cristina

doi:10.22381/emfm13320181

Cited by 8 publications

(2 citation statements)

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“…According to their classification, cluster 1 presents the countries which belong to former parts of the Soviet Union, cluster 3 stands for the Soviet-controlled Eastern bloc countries and cluster 2 is a mixture of the previous two groups of countries. All the countries experienced a dramatic change within the communist bloc, which influence their political, economic and social life (Sion, 2018;Gandolfi et al, 2018). After the revolution, the countries started the process of transition to a market economy, presenting growing and developing markets nowadays.…”

Section: Resultsmentioning

confidence: 99%

Remaining Financially Healthy and Competitive: The Role of Financial Predictors

Klieštik¹,

Valášková²,

Lăzăroiu³

et al. 2020

JOC

124

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Financial ratios play an important role in revealing corporate financial soundness, a role which helps to maintain the competitive position of an enterprise, with the achievement of stable development contributing to the elimination of potential financial risks. This paper aims to analyse and compare financial ratios used in the models of transition countries. The analysis focuses on the prediction of the future financial development of a particular enterprise as well as the determination of potential dependencies among the nation in consideration of financial ratios and country of origin. More than 400 prediction models of the Slovak Republic,

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Section: Resultsmentioning

confidence: 99%

Remaining Financially Healthy and Competitive: The Role of Financial Predictors

Klieštik¹,

Valášková²,

Lăzăroiu³

et al. 2020

JOC

124

View full text Add to dashboard Cite

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“…For the situations resulting in the problems of continuity of the company operations, terms such as bankruptcy, failure, insolvency, and default are usually used. (Gandolfi et al, 2018) According to the Altman definition of failure (1993), failure is a situation where "the realized rate of return on invested capital, with allowances for risk consideration, is significantly and continually lower than prevailing rates of similar investments".…”

Section: Literature Reviewmentioning

confidence: 99%

Financial distress prediction in Slovakia: An application of the CART algorithm

Ďurica¹,

Frnda²,

Švábová³

2021

Journal of International Studies

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Innovation Management of the Bankruptcy: Case Study of Visegrad Group Countries

Kováčová

Valášková

Ďurana

et al. 2019

MMI

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Since the first bankruptcy prediction models developed in the 60th of 20th century numerous different models have been constructed through the world. These individual models for bankruptcy prediction have been created in different time and space using different methods and variables. During this period various statistical methods have been used starting with the most popular univariate, linear and multivariate discriminant analysis, logistic regression, probit regression, decision trees, neural networks, rough sets, linear programming, principal component analysis, data envelopment analysis, survival analysis and so on. Therefore, we aim to provide deep insight and analyse the bankruptcy prediction models developed in countries of Visegrad four, with the emphasis on methods applied and explanatory variables used in these models, and evaluate them through appropriate statistical methods. Specifically, cluster analysis to explore the differences between basic groups of financial indicators and designed clusters of explanatory variables. Based on the analysis of more than one hundred bankruptcy prediction models we can conclude the most used variables, which serves as a basis for further research and development of prediction models in Visegrad group countries. Three clusters were developed which representing various explanatory variables while these clusters differ from basic groups of financial indicators. According to detected clusters we recommend to choose the most frequently used variables from each created cluster. From the cluster one revenues from sales/total assets ratio; from the cluster two the construction of models should contain current ratio, and from the cluster three we recommend to use ROE. Also if we take into consideration the total frequency together with the constructed clusters we advise to use more variables from clusters two and three. Results of the provided study may be used not only by researchers and enterprises but also by investors during the construction of bankruptcy prediction models in conditions of an individual country. Keywords: bankruptcy, bankruptcy prediction, variables, countries of Visegrad four.

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Underpricing and Long-Term Performance of Ipos: Evidence From European Intermediary-Oriented Markets

Cited by 8 publications

References 0 publications

Remaining Financially Healthy and Competitive: The Role of Financial Predictors

Remaining Financially Healthy and Competitive: The Role of Financial Predictors

Financial distress prediction in Slovakia: An application of the CART algorithm

Innovation Management of the Bankruptcy: Case Study of Visegrad Group Countries

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