The market rank indicator to detect financial distress

Figini, Silvia; Maggi, Mario; Uberti, Pierpaolo

doi:10.1016/j.ecosta.2017.12.001

Cited by 10 publications

(10 citation statements)

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“…In this section, we review some of the most used connectedness indicators and investigate whether these measures verify the minimal properties required by the PMCs definition. We focus our attention on the following most commonly used measures: the Total Connectedness (see Diebold and Yilmaz 2009), the Cumulative Risk Fraction (see Billio et al 2012), the Market Rank Indicator (see Figini et al 2018), the Average Correlation, the Variance Inflation Factor (see Belsey et al 1980), the Mahalanobis distance (see Mahalanobis 1936).…”

Section: Some Measures Of Connectedness Proposed In the Literaturementioning

confidence: 99%

“…The notion of Market Rank Indicator (see Figini et al 2018) is defined as a ratio of some of the eigenvalues of a given matrix and it is useful to detect the collinearity between the columns of the input matrix.…”

Section: The Market Rank Indicatormentioning

confidence: 99%

“…Definition 8 (Market rank indicator) (see Figini et al 2018) The market rank indicator s k , k = 1, . .…”

Section: The Market Rank Indicatormentioning

confidence: 99%

“…In this paper we focus on the concept of connectedness and its possible application to systemic risk detection. Various measures of connectedness have been proposed and studied for market risk (return connectedness and market diversification), see among others Belsey et al (1980), credit risk (default connectedness), see for example Merton (2014), and in general systemic risk (for system wide connectedness), see Billio et al (2012), Figini et al (2018), Acemoglu et al (2015), Acharya et al (2012). In particular, financial interconnectedness is well-known as a potential source of systemic risk.…”

Section: Introductionmentioning

confidence: 99%

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Proper measures of connectedness

2020

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The concept of connectedness has been widely used in financial applications, in particular for systemic risk detection. Despite its popularity, at the state of the art, a rigorous definition of connectedness is still missing. In this paper we propose a general definition of connectedness introducing the notion of Proper Measures of Connectedness (PMCs). Based on the classical concept of mean introduced by Chisini, we define a family of PMCs and prove some useful properties. Further, we investigate whether the most popular measures of connectedness available in the literature are consistent with the proposed theoretical framework. We also compare different measures in terms of forecasting performances on real financial data. The empirical evidence shows the forecasting superiority of the PMCs compared to the measures that do not satisfy the theoretical properties. Moreover, the empirical results support the evidence that the PMCs can be useful to detect in advance financial bubbles, crises, and, in general, for systemic risk detection.

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Section: Some Measures Of Connectedness Proposed In the Literaturementioning

confidence: 99%

Section: The Market Rank Indicatormentioning

confidence: 99%

“…Definition 8 (Market rank indicator) (see Figini et al 2018) The market rank indicator s k , k = 1, . .…”

Section: The Market Rank Indicatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Proper measures of connectedness

2020

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“…Dar respuesta a estos interrogantes constituye en esta investigación un aporte para el sector empresarial y para al contexto económico que se analiza, toda vez que se precisan criterios para definir variables y rubros, que permitan establecer indicadores de resultados financieros, con lo que se pueda definir clúster empresariales, sus niveles de resultados y estructura estadística que permita predecir la pertenecía a un clúster de una empresa independiente. De igual manera, se seleccionaron como objeto de estudio de esta investigación los tres indicadores financieros de resultados, considerando que los rubros utilidad bruta, utilidad operacional, utilidad neta y ventas netas, las cuales definen, establecen y miden los resultados empresariales financieros de las organizaciones objeto de estudio (Figini et al, 2018;Sean y Chang, 2016). O cualquier otro grupo empresarial a nivel nacional o internacional.…”

Section: Introductionunclassified

Diseño de Perfiles Financieros Empresariales del Sector Químico en Colombia mediante Cálculo Multivariado

2018

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Se presenta un método para el diseño de perfiles empresariales en el sector químico de Colombia. Se utilizaron los conceptos estadísticos de cálculo multivariado mediante Análisis de Conglomerado y Análisis Discriminante Multivariado (ADM). Se tomó como muestra un conjunto de 80 empresas que presentaron sus estados financieros al Sistema de Información y Reporte Empresarial para el año 2015. Con los rubros de los estados financieros, se calcularon los indicadores financieros Margen Bruto, Margen Operacional y Margen Neto y mediante un análisis cuantitativo racional en el que se aplicaron técnicas de análisis multivariado, se identificaron tres grupos empresariales, a partir de los cuales se definieron perfiles financieros. El ADM generó capacidad discriminante del 98,03% para clasificar a futuro nuevas empresas en los perfiles identificados. Se concluye que los indicadores Margen Bruto, Margen Operacional y Margen Neto son consistentes y confiables para discriminar, valorar y proyectar perfiles financieros empresariales en el sector analizado.

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Connectedness versus diversification: two sides of the same coin

Torrente

Uberti

2021

Math Finan Econ

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In the financial framework, the concepts of connectedness and diversification have been introduced and developed respectively in the context of systemic risk and portfolio theory. In this paper we propose a theoretical approach to bring to light the relation between connectedness and diversification. Starting from the respective axiomatic definitions, we prove that a class of proper measures of connectedness verifies, after a suitable functional transformation, the axiomatic requirements for a measure of diversification. The core idea of the paper is that connectedness and diversification are so deeply related that it is possible to pass from one concept to the other. In order to exploit such correspondence, we introduce a function, depending on the classical notion of rank of a matrix, that transforms a suitable proper measure of connectedness in a measure of diversification. We point out general properties of the proposed transformation function and apply it to a selection of measures of connectedness, such as the well-known Variance Inflation Factor.

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The market rank indicator to detect financial distress

Cited by 10 publications

References 30 publications

Proper measures of connectedness

Proper measures of connectedness

Diseño de Perfiles Financieros Empresariales del Sector Químico en Colombia mediante Cálculo Multivariado

Connectedness versus diversification: two sides of the same coin

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