Riesgo de crédito y solidez financiera en el sector bancario: Un enfoque macroprudencial

[ES]La estabilidad del sector bancario ha recibido una creciente atención en los últimos años. Básicamente distinguimos dos enfoques en el análisis del riesgo bancario: microprudencial y macroprudencial. El primero se centra en entidades individuales, mientras el segundo analiza el sistema financiero en su conjunto. Las recientes dificultades financieras han mostrado las limitaciones de la regulación microprudencial, provocando un movimiento hacia el análisis macroprudencial. En esta línea, el Fondo Monetario Internacional ha desempeñado una labor decisiva, desarrollando y recopilando los Indicadores de Solidez Financiera (ISF). Nuestra investigación adopta el enfoque macroprudencial, haciendo uso de los ISF. Las conclusiones de los dos estudios realizados a nivel de los países de la Unión Europea son relevantes para establecer un diagnóstico de la solidez del sistema bancario, la influencia que en la misma ha ejercido el nivel de desarrollo financiero, y el impacto de cada aspecto de la solidez bancaria en el riesgo soberano.[EN]Banking sector stability has received increased attention in recent years. Basically, two main approaches exist in the research related to bank risk assessment: the microprudential and macroprudential approaches. The microprudential approach examines individual financial institutions whereas the macroprudential approach aims to monitor stability of the financial system as a whole. Global financial difficulties have shown the limitation of microprudential regulations. Consequently, there has been a shift towards the macroprudential approach. In this sense, the International Monetary Fund has made important efforts to develop and compile the Financial Soundness Indicators (FSIs). Our research focuses on the macroprudential approach by using the FSIs. The conclusions of the two studies that we develop in this thesis are relevant to assess the financial soundness of the EU banking system, the influence of the financial development on the banking soundness of countries, and the impact of each aspect of banking soundness on the sovereign risk.Tesis Univ. Jaén. Departamento de Economía Financiera y Contabilidad, Leída el 6 de febrero de 201

Using the Z-score to analyze the financial soundness of insurance firms

Purpose - Despite the sophisticated regulatory regime established in Solvency II, analysts should be able to consider other less complex indicators of the soundness of insurers. The Z-score measure, which has traditionally been used as a proxy of individual risk in the banking sector, may be a useful tool when applied in the insurance sector. However, different methods for calculating this indicator have been proposed in the literature. This paper compares six different Z-score approaches to examine which one best fits insurance companies. The authors use a final dataset of 183 firms (1,382 observations) operating in the Spanish insurance sector during the period 2010-2017. Design/methodology/approach - In the first stage, the authors opt for a root mean squared error (RMSE) criterion to evaluate which of the various mean and SD estimates that are used to compute the Z-score best fits the data. In the second stage, the authors estimate and compare the explanatory power of the six Z-score measures that are considered by using an ordinary least squares (OLS) regression model. Finally, the authors report the results of the baseline equation using the system-GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998) for dynamic panel data models. Findings - The authors find that the best formula for calculating the Z-score of insurance firms is the one that combines the current value of the return on assets (ROA) and capitalization with the SD of the returns calculated over the full sample period. Research limitations/implications - The main limitation of the research is that it addresses only the Spanish insurance sector, and consequently, the implications of the findings must be framed in this institutional context. However, the authors think that the results could be extrapolated to other countries. Future research should consider including different countries and analyzing the usefulness of aggregated insurer-level Z-scores for macroprudential monitoring. Practical implications - The Z-score may be a useful early warning indicator for microprudential supervision. In addition to being an indicator of the soundness of insurers simpler than those established in the current regulation, the information provided by this accounting-based measure may help analysts and investors obtain a better understanding of insurance firms' risk factors. Originality/value - To the best of the authors' knowledge, this study is the first to examine and compare different approaches to calculating Z-scores in the insurance sector. The few available results on the predictive power of the Z-score are mixed and focus on the banking sector