Publicación: Patrón de comportamiento explicativo de las ofertas públicas de adquisición de acciones en el sector inmobiliario. El caso de España
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2017-02-07
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info:eu-repo/semantics/openAccess
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Elsevier
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La tendencia alcista del sector inmobiliario espa˜nol (2000-2007) provocó el crecimiento excesivo de muchas empresas, principalmente mediante adquisiciones. Esta investigación pretende identificar patrones de comportamiento para la realización de OPAs en el sector inmobiliario espa˜ nol, particularmente castigado por la crisis financiera. Para ello, se ha analizado un conjunto de 20 variables económico-financieras y su relación con la participación de las compa˜nías cotizadas del sector en este tipo de operaciones, para un total de 354 casos para el periodo 2000-2012, como adquirentes y adquiridas. Para ello, se ha empleado una metodología en dos etapas. En primer lugar, se ha aplicado el Método de Componentes Principales para acotar las variables de estudio consideradas con mayor capacidad explicativa. En segundo lugar, se ha construido un modelo predictivo basado en árboles de decisión, concretamente de tipo CHAID, que permite categorizar el conjunto de empresas analizadas y discriminar patrones de comportamiento. Los cinco factores principales con mayor capacidad explicativa son: a) liquidez, solvencia y capacidad de endeudamiento; b) tama˜no; c) resultado económico; d) capacidad operativa, y e) resultado financiero. De hecho, los dos primeros explican conjuntamente en torno al 70% de la variable dependiente, considerando principalmente a empresas adquirentes. El modelo propuesto cuenta con un nivel de explicación global cercano al 80%. El porcentaje restante que no explica el modelo responde fundamentalmente a cuestiones de tipo estratégico, de especulación financiera e intereses particulares, entre otros factores que concurren en la toma de decisiones.
The upward of the Spanish real estate sector (2000–2007) caused the excessive growth of many companies mainly through acquisitions. This study aimed to identify behaviour patterns for takeover bids in the Spanish real estate industry, which was particularly hard hit by the last financial crisis. Considering that in bubble growing/burst periods, economic and financial variables are considered the most useful measures (market variables can have reliability problems), a set of 20 economic and financial variables was analysed, along with their relationship with listed companies’ participation in this type of operations over the period 2000–2012. Both acquiring and target companies were included in the 354 cases studied here. A two-stage methodology was used. Firstly, the principal component method was applied to identify the variables with greatest explanatory capacity. That was followed by the construction of a decision treebased predictive model, more specifically a CHAID, which categorised the set of companies analysed to establish behaviour patterns. The findings of this study show that the five principal components found to afford the greatest explanatory capacity were: (a) liquidity, solvency and borrowing capacity; (b) size; (c) economic performance; (d) operating capacity; and (e) financial performance. Taken together, the first two components explained 70% of dependent variable behaviour, primarily relative to buyers. Overall, the model proposed explained on the order of 80% of dependent variable behaviour. The percentage not explained by the model was attributed essentially to strategic issues, financial speculation and private interests, among other factors present in decision-making.
The upward of the Spanish real estate sector (2000–2007) caused the excessive growth of many companies mainly through acquisitions. This study aimed to identify behaviour patterns for takeover bids in the Spanish real estate industry, which was particularly hard hit by the last financial crisis. Considering that in bubble growing/burst periods, economic and financial variables are considered the most useful measures (market variables can have reliability problems), a set of 20 economic and financial variables was analysed, along with their relationship with listed companies’ participation in this type of operations over the period 2000–2012. Both acquiring and target companies were included in the 354 cases studied here. A two-stage methodology was used. Firstly, the principal component method was applied to identify the variables with greatest explanatory capacity. That was followed by the construction of a decision treebased predictive model, more specifically a CHAID, which categorised the set of companies analysed to establish behaviour patterns. The findings of this study show that the five principal components found to afford the greatest explanatory capacity were: (a) liquidity, solvency and borrowing capacity; (b) size; (c) economic performance; (d) operating capacity; and (e) financial performance. Taken together, the first two components explained 70% of dependent variable behaviour, primarily relative to buyers. Overall, the model proposed explained on the order of 80% of dependent variable behaviour. The percentage not explained by the model was attributed essentially to strategic issues, financial speculation and private interests, among other factors present in decision-making.
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Categorías UNESCO
Palabras clave
Real estate industry, Takeover bids, Economic-financial variables, Principal components analysis, Chi-square Automatic Interaction Detector (CHAID), Sector inmobiliario, Ofertas públicas de adquisición de acciones, Variables económico-financieras, Método de componentes principales
Citación
Centro
Facultad de Ciencias Económicas y Empresariales
Departamento
Economía de la Empresa y Contabilidad