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El presente trabajo de investigación tiene como propósito analizar una propuesta de indicadores macroeconómicos y financieros para un sistema de alerta temprana en la tasa de morosidad de las Cajas Municipales de Ahorro y Crédito del sistema financiero peruano, durante el periodo 2006-2017. El objetivo principal de este estudio es demostrar la influencia de las variables seleccionadas con respecto a la tasa de morosidad y determinar el efecto producido por cada una sobre la variable dependiente como un sistema de alerta o prevención. Las variables escogidas para el análisis son PBI sector comercio, tasa de desempleo, ratio de solvencia, ratio de liquidez, número de agencias, créditos directos y créditos directos por empleado. Para este caso, la información estadística se analizará a través del modelo econométrico vector autorregresivo (VAR) para determinar los efectos que presentan las variables sobre la tasa de morosidad y el modelo vector autorregresivo estructural (VARS) para analizarlo de forma estructural de largo plazo. Así mismo, se determina los efectos dinámicos de las variables macroeconómicas y financieras con respecto a la tasa de morosidad. Dentro de los resultados obtenidos tenemos que las variables macroeconómicas y financieras estudiadas sí influyen en la tasa de morosidad, lo cual corroboran nuestras hipótesis y funcionan como un sistema de alerta temprana para las Cajas Municipales. Con respecto al efecto de las variables, se observa que el efecto de cada una varía o se mantiene en la fase corta y en la fase permanente. / The purpose of this research is to analyze a proposal of macroeconomic and financial factors for an early warning system for the default rate of Municipal Savings and Credit of the Peruvian financial system, during the period 2006-2017. The objective of this study is to demonstrate the influence of selected variables on the default rate and also, as a complement, know the effect produced by each one as a prevention system. The variables chosen for the analysis are GDP trade sector, unemployment rate, solvency rate, liquidity, number of agencies, direct credits and direct credits per employee. For this, the statistical information will be analyzed through the autoregressive vector (VAR), an econometric model that determine the effects of the variables on the default rate and the structural autoregressive vector model (VARS) to analyze it in a long-term structural manner. Additionally, the dynamic effects of the macroeconomic and financial variables are determined in relation to the default rate. The results of this study are that macroeconomic and financial factors have an influence in the default rate, which are in order with our hypotheses and it works as an early warning for Municipal Savings. About the effect of each variable, there are cases that it changes or remains in the short term and long term. / Tesis

The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This thesis follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy in the first part of this thesis. Time series of bankruptcy and firm's numbers were used. Aggregate data for whole economy as well as industry specific data were available. First, linear vector autoregressive models was used in case of dynamic empirical model. We examined how significant macroeconomic indicators determined the default rate in the whole economy and in the industry specific sector. However these models cannot provide microeconomic foundation as latent factor models. We employed a one- factor model in our estimation although, multi-factor models were also considered. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Obtained results were used in the second part of this...

Stress testing is a macro-prudential analytical method of assessing the financial system's resilience to adverse events. This thesis describes the methodology of the stress tests and illustrates the stress testing for credit and market risks on the real bank-by-bank data in the two Balkan countries: Croatia and Serbia. Credit risk is captured by the macroeconomic credit risk models that estimate the default rates of the corporate and the household sectors. Setting-up the framework for the countries that were not much covered in former studies and that face the limited availability of data has been the main challenge of the thesis. The outcome can help to reveal possible risks to financial stability. The methods described in the thesis can be further developed and applied to the emerging markets that suffer from the similar data limitations. JEL Classification: E37, G21, G28 Keywords: banking, credit risk, default rate, macro stress testing, market risk

A main goal of the diploma thesis is to perform a strategic analysis of a selected enterprise with the purpose of examining a current situation and trends in external and internal environment of the enterprise, and, based on the analysis, to suggest recommendations concerning a future strategy of the company.

Made available in DSpace on 2010-04-20T20:48:08Z (GMT). No. of bitstreams: 3 68479.pdf.jpg: 16047 bytes, checksum: e55a63085f1340eeed16cabe46f731aa (MD5) 68479.pdf: 840158 bytes, checksum: d13c12beedbf2f62a71d5574af83dfad (MD5) 68479.pdf.txt: 270876 bytes, checksum: 0af13fce10af7db2c36dcb34a90e0b79 (MD5) Previous issue date: 2004-04-07T00:00:00Z / Credit risk comes from the possibility of the debtor not paying its debt at the maturity date, and the promised amount. When the debtor doesn’t pay in full its debt, we say he or she is in default. In this case, the creditor gets a loss. However, the loss could be reduced if the debtor pays part of his or her debt. The measurement of a debtor’s probability of default has been the subject of studies for decades. However, the measurement of how much one can receive from a defaulted credit – the recovery rate – has been given attention only recently. And, most of the time, this measure has been calculated for huge companies in United States financial markets, only. We have defined recovery rate based on financial reports of Brazilian commercial banks, and tracked the path of this variable pari passu to default rate, defined from the same reports also. We established a theoretical framework, and made hypothesis on how such variables as default rates and other credit quality indicators, economic level indicators, nominal and real interest rates, and capital markets indicators could explain variations on the recovery rates we have defined. We gathered information from 46 Brazilian private commercial banks, semiannually, bracing the period between June of 1994 and December 2002. These institutions were segmented by their share on the amount of credit of the private banking industry in Brazil and by the origin of its capital. Statistical models were run on explanatory variables based on original data and on variables obtained from principal components analysis. The models were able to explain most of the variation observed on the recovery rate we have defined, for the segments we have studied. The best models have shown that variations on the recovery rate could be explained by default rates and other indicators of credit quality, economic activity indicators and capital markets indicators. / O risco de crédito decorre da possibilidade de o devedor não honrar sua dívida no montante e na data aprazada. Quando o devedor não liquida sua dívida nas condições contratadas, diz-se que se torna inadimplente. Neste caso, o credor incorre em prejuízo. A perda, entretanto, pode ser reduzida se o cliente pagar parcialmente o que deve. A mensuração da probabilidade de um devedor inadimplir tem sido objeto de estudos há décadas. Entretanto, a quantificação do quanto o credor recebe em caso de inadimplência – a taxa de recuperação –só recentemente tem recebido atenção da academia. E, na maioria das vezes, esta quantificação tem-se limitado aos títulos de grandes empresas, negociados no mercado de capitais dos Estados Unidos da América. Neste trabalho, definiu-se uma taxa de recuperação baseada em informações contábeis de instituições bancárias brasileiras e analisou-se o comportamento desta variável pari passu à taxa de inadimplência, também definida a partir de dados contábeis. Estabeleceu-se um arcabouço teórico capaz de explicar de que forma variáveis como a taxa de inadimplência e outros indicadores de qualidade das carteiras de crédito, indicadores da atividade econômica, níveis de juros nominais e reais e indicadores do mercado de capitais, poderiam explicar as variações na taxa de recuperação das carteiras de crédito. Foram obtidas informações de um conjunto de 46 instituições bancárias privadas brasileiras, semestralmente, para o período compreendido entre junho de 1994 e dezembro de 2002. Essas instituições foram segmentadas pela representatividade de suas carteiras de crédito no volume total de créditos das instituições comerciais brasileiras e por origem de seu capital acionário. Elaboraram-se modelos estatísticos baseados em regressões multivariadas tanto de variáveis originais como de variáveis obtidas através de análise de componentes principais, que se mostraram capazes de explicar parte considerável das variações observadas na taxa de recuperação no conceito contábil, para os vários segmentos de instituições estudados. Mostraram-se como variáveis explicativas relevantes, nos melhores modelos, indicadores de inadimplência, indicadores da atividade econômica e indicadores do mercado de capitais.