Financial performance and distress profiles. From classification according to financial ratios to compositional classification

Linares‐Mustarós, Salvador; Coenders, Germà; Vives‐Mestres, Marina

doi:10.1016/j.adiac.2017.10.003

Cited by 43 publications

(51 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For example, Tsai and Cheng in [14] studied bankruptcy prediction performance achieved after removal of different outlier volumes from datasets. Linares-Mustaros et al in [15] dealt with problems of the occurrence of outliers in using cluster analysis to classify firms according to their financial structures. Alrawashdeh et al in [16] tried to eliminate the problem of high sensitivity of linear discriminant analysis to the occurrence of outliers in data and to improve the classification ability of created models also in bankruptcy prediction.…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of Data structure on classification ability of financial failure prediction model

Švábová

Michalkova

2020

SHS Web Conf.

View full text Add to dashboard Cite

The creation of prediction models to reveal the threat of financial difficulties of the companies is realized by the application of various multivariate statistical methods. From a global perspective, prediction models serve to classify a company into a group of prosperous or non-prosperous companies, or to quantify the probability of financial difficulties in the company. In many countries around the world, real financial data about the companies are used in developing these prediction models. In Slovakia, standard data from the financial statements and annual reports of Slovak companies are used for the creation of the company’s failure model. Since in this case there are generally large data files, it is necessary to pre-process the data by the selected methods before the prediction model is constructed. A database of the companies needs to be prepared for the subsequent application of statistical methods, and it is also highly appropriate to focus globally on the detection of potential extreme and remote observations. Therefore, the article will focus on quantifying the impact of the data structure detected, for example, the occurrence of extreme and remote observations in the data set, on the resulting overall classification of the prediction ability of the models created.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

The impact of Data structure on classification ability of financial failure prediction model

Švábová

Michalkova

2020

SHS Web Conf.

View full text Add to dashboard Cite

show abstract

“…The scientific hypotheses formulated by the author are proved and justified by the corresponding logical and analytical conclusions. The theoretical and methodological foundation of the research is the studies of the multivariate analysis carried out by Hidalgo and Goodman (2013), Anderson (2003), Kumar, et al, (1986), Schervish (1987), euclidean distance (Linares-Mustarósa, Coendersb, & Vives-Mestres, 2018) and cluster analysis (Capece, Cricellib, & Pillo, 2010, Gupta & Huefner, 1972, Salmi, Dahlstedt, Luoma, & Laakkonen, 1986, Boillat, Skowronski, & Tuchschimid, 2002. Financial performance and distress profiles are from classification according to financial ratios relatively compositional classification.…”

Section: Research Questionsmentioning

confidence: 99%

Rating Of Agricultural Enterprises Of Irkutsk Region Based On Multivariate Analysis

Tyapkina¹

2018

The European Proceedings of Social and Behavioural Sciences

View full text Add to dashboard Cite

show abstract

“…La tradición CoDa comenzó con el trabajo seminal de Aitchison (1982Aitchison ( , 1986) sobre composiciones químicas y geológicas, en el que sólo interesa la proporción de cada parte o componente, ya que las cantidades absolutas son irrelevantes y sólo revelan el tamaño de la muestra química o de suelo (por ejemplo, Buccianti et al, 2006). En la actualidad, el análisis CoDa abarca casi todas las ciencias exactas y ha comenzado a utilizarse en varios campos de las ciencias sociales, como la educación (Batista-Foguet et al, 2015), la economía (Fry, 2011), el marketing (Vives-Mestres et al, 2016), la contabilidad (Linares et al, 2018), el turismo (Ferrer Rosell y Coenders, 2016), los valores (van Eijnatten et al, 2015), las redes sociales (Kogovšek et al, 2013), el uso del tiempo (Martín-Fernández et al, 2015a), y estudios electorales (Egozcue y Pawlowsky-Glahn, 2011;Liscano Fierro y Ortiz Rico, 2017 Buccianti, 2011;Pawlowsky-Glahn et al, 2015). A continuación, ofrecemos un breve resumen del método.…”

Section: Análisis Composicionalunclassified

Representación composicional de la intermedia agenda-setting de los principales grupos de medios y partidos políticos en las elecciones generales españolas de 2015

Duatis

Coenders

Sáez

2018

RLCS

View full text Add to dashboard Cite

Cómo citar este artículo / Referencia normalizadaM Blasco-Duatis, G Coenders Gallart, M Sáez (2018): "Representación composicional de la intermedia agenda-setting de los principales grupos de medios y partidos políticos en las elecciones generales españolas de 2015". Revista Latina de Comunicación Social, 73, pp Abstracts [ES]Este artículo presenta el biplot composicional como un enfoque metodológico innovador para representar de manera intuitiva la intermedia agenda-setting en el estudio de las agendas mediática y política. Como ilustración, empleamos un análisis de contenido de los principales grupos de medios españoles (RTVE, Prisa, Vocento, Unidad Editorial, COPE, Atresmedia, Planeta, Godó, Mediaset España y Libertad Digital) y principales partidos políticos con circunscripción única (Partido Popular, Partido Socialista Obrero Español, Podemos, Ciudadanos e Izquierda Unida), en el marco del período de las Elecciones Generales españolas de 2015. En oposición a los enfoques tradicionales, el análisis composicional en general y el biplot en particular enfatizan la relevancia relativa de los contenidos dentro de la agenda. La representación confirma la solidez metodológica del enfoque, al tiempo que proporciona una visión novedosa del caso en estudio y visualiza la representación de la intermedia agenda-setting.[EN] This article presents the compositional biplot as an innovative methodological approach to visualize intermedia agenda-setting in the study of the media and political agendas. As an illustration, we use a content analysis of the main Spanish media groups (RTVE, Prisa, Vocento, Unidad Editorial, COPE, Atresmedia, Planeta, Godó, Mediaset España and Libertad Digital) and main Spanish political parties (Partido Popular, Partido Socialista Obrero Español, Podemos, Ciudadanos e Izquierda Unida), within the framework of the Spanish General Election period of 2015. In opposition to traditional approaches, compositional analysis in general and the biplot in particular, emphasize the relative relevance of the contents within the agenda. The representation confirms the methodological RLCS, Revista Latina de Comunicación Social, 73 -Páginas 264 a 292 [Investigación] [Financiada] DOI: 10.4185/RLCS-2018-1255| ISSN 1138-5820 | Año 2018 http://www.revistalatinacs.org/073paper/1255/14es.html Página 265soundness of the approach, while providing a novel view of the case under study and visualizing the representation of the intermedia agenda-setting.

show abstract

Financial performance and distress profiles. From classification according to financial ratios to compositional classification

Cited by 43 publications

References 57 publications

The impact of Data structure on classification ability of financial failure prediction model

The impact of Data structure on classification ability of financial failure prediction model

Rating Of Agricultural Enterprises Of Irkutsk Region Based On Multivariate Analysis

Representación composicional de la intermedia agenda-setting de los principales grupos de medios y partidos políticos en las elecciones generales españolas de 2015

Contact Info

Product

Resources

About