Loan sales under asymmetric information

Loans are illiquid assets that can be sold in a secondary market even that buyers have no certainty about their quality. I study a model in which a lender has access to new investment opportunities when all her assets are illiquid. To raise funds, the lender may either borrow using her assets as collateral, or she can sell them in a secondary market. Given asymmetric information about assets quality, the lender cannot recover the total value of her assets. There is then a role for the government to correct the information problem using fiscal tools.

Measuring and testing for the systemically important financial institutions

This paper analyzes the measure of systemic importance ∆CoV aR proposed by Adrian and Brunnermeier (2009, 2010) within the context of a similar class of risk measures used in the risk management literature. In addition, we develop a series of testing procedures, based on ∆CoV aR, to identify and rank the systemically important institutions. We stress the importance of statistical testing in interpreting the measure of systemic importance. An empirical application illustrates the testing procedures, using equity data for three European banks.

The cyclical behavior of bank capital buffers in an emerging economy: size do matters

Using a panel of Colombian banks and quarterly data between 1996:1 and 2010:3, we study the relationship between short-run adjustemnts in bank capital buffers and the business cycle. We follow a partial adjustment framework and control for several variables that have been identified as important determinants of bank capital buffers in previous studies, and find that bank capital buffers vary over the business cycle. We are able to identify a negative co-movement of capital buffers and and the business cycle. However, we also find that capital buffers of small and large banks behave asymmetrically during the business cycle. While the former appear to be constant over time, once the appropriate set of control variables is used, the latter present a countercyclical behavior. Our results suggest the possible need of the implementation of regulatory policy measures in developing countries

Invprest

Invprest es la primera plataforma de préstamos entre personas en Colombia y Latinoamérica dirigida exclusivamente para Millenials; es decir conectamos a personas que necesitan financiamiento con personas que están dispuestas a prestar a una tasa justa, equitativa y más rentable que la del mercado financiero. Se tiene en cuenta un estudio de crédito diferente al tradicional donde se revisan factores de la personalidad y comportamentales del solicitante de crédito para conocer su riesgo. Actualmente una gran parte de los usuarios financieros se sienten insatisfechos con los servicios que prestan las entidades bancarias. La tecnología y nuevos modelos de economía colaborativa han abierto el espacio a nuevas formas de consumo, entre ellos la innovación en los servicios bancarios que han funcionado por mucho tiempo de la misma forma. La falta de un excelente servicio, unas tasas de interés que no reflejan las condiciones del mercado, la falta de un servicio que incluya las necesidades de los clientes en una economía digital son problemas que se resuelven con este emprendimiento. Se busca llegar a un mercado potencial de 170.000 personas en Bogotá y en Colombia de 638.000 aproximadamente. El mercado en Colombia es nuevo, naciente y con potencial de crecimiento. Actualmente hay más de 70 países que cuentan con plataformas de este estilo y se espera que las inversiones en estos modelos de negocio sean mayores a $14.000 Millones de dólares en el 2.015. Así mismo en Colombia cada vez se conoce más sobre los cambios de la industria financiera mundial. Invprest se diferencia en otros aspectos relacionados con el seguimiento de la cartera, los requerimientos relacionados a la posesión de activos fijos que en este modelo no son necesarios si la persona tiene buenos ingresos y la utilización de firmas electrónicas para que todos los procesos se puedan hacer electrónicamente. Yohan Florez es un apasionado por el tema de finanzas que ha logrado contactar e incluir a personas de Fiduciarias, Brigard & Urrutia, Certicamara y otros expertos financieros en la creación de las soluciones que se le pueden dar a los problemas de este proceso y que ayudan con su conocimiento y experiencia para el desarrollo del proyecto. 3 En el corto plazo la empresa se va a consolidar en Colombia y en el mediano- largo plazo se van a realizar las acciones para expandir el modelo a otros países de Latinoamérica. Se espera que en el tercer año se cuente con ingresos superiores a los $1.700 millones de pesos con una ganancia de $98 millones, el punto de equilibrio se alcanza en el mes 11. El medio para llegar a los clientes es usando redes sociales con publicidad dirigida, así mismo el Ceo será el principal vendedor de la compañía al inicio de la operación. La inversión inicial requerida para el proyecto empresarial es de $201.000.000.

Network externalities across financial institutions

We propose and estimate a financial distress model that explicitly accounts for the interactions or spill-over effects between financial institutions, through the use of a spatial continuity matrix that is build from financial network data of inter bank transactions. Such setup of the financial distress model allows for the empirical validation of the importance of network externalities in determining financial distress, in addition to institution specific and macroeconomic covariates. The relevance of such specification is that it incorporates simultaneously micro-prudential factors (Basel 2) as well as macro-prudential and systemic factors (Basel 3) as determinants of financial distress. Results indicate network externalities are an important determinant of financial health of a financial institutions. The parameter that measures the effect of network externalities is both economically and statistical significant and its inclusion as a risk factor reduces the importance of the firm specific variables such as the size or degree of leverage of the financial institution. In addition we analyze the policy implications of the network factor model for capital requirements and deposit insurance pricing.

The impact of energy performance certificates on the rental and capital values of commercial property assets: some preliminary evidence from the UK

This paper focuses on the effect of energy performance ratings on the capital values, rental values and equivalent yields of UK commercial property assets. Of which a small number are also BREEAM rated, the study is based upon 708 commercial property assets held in the IPD UK Universe drawn from across all PAS segments. Incorporating a range of controls such as unexpired lease term, vacancy rate and tenant credit risk, hedonic regression procedures are used to estimate the effect of EPC rating. The study finds no evidence of a strong relationship between environmental and/or energy performance and rental and capital value. Bearing in mind the small number of BREEAM rated assets, there was a small but statistically significant effect on equivalent yield only. Similarly, there was no evidence that the EPC rating had any effect on Market Rent or Market Value with only minor effects of EPC ratings on equivalent yields. The preliminary conclusion is that energy labelling is not yet having the effects on Market Values and Market Rents that provide incentives for market participants to improve the energy efficiency of their commercial real estate assets.

Residential property loans and bank performance during property price booms: evidence from Europe

Understanding the performance of banks is of the utmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of their performance. Using a dynamic panel model, we analyse the impact of residential mortgage loans on bank profitability and risk, based on a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that an increase in residential mortgage loans seems to improve bank’s performance in terms of both profitability and credit risk in good market, pre-financial crisis, conditions. These findings may aid in explaining why banks rush to lend to property during booms because of the positive effect it has on performance. The results also show that credit risk and profitability are lower during the upturn in the residential property cycle.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

The economic significance of CDS price discovery

© 2015 Springer Science+Business Media New York Between 2005 and 2009, we document evident time-varying credit risk price discovery between the equity and credit default swap (CDS) markets for 174 US non-financial investment-grade firms. We test the economic significance of a simple portfolio strategy that utilizes fluctuation in CDS spreads as a trading signal to set stock positions, conditional on the CDS price discovery status of the reference entities. We show that a conditional portfolio strategy which updates the list of CDS-influenced firms over time, yields a substantively larger realized return net of transaction cost over the unconditional strategy. Furthermore, the conditional strategy’s Sharpe ratio outperforms a series of benchmark portfolios over the same trading period, including buy-and-hold, momentum and dividend yield strategies.

Desenvolvimento de metodologia de rating baseada no modelo ordered probit

Nos últimos anos o mercado de crédito brasileiro apresentou grande crescimento em termos de volume e modalidade de operações de crédito. Além disso, observou-se também o aumento da participação dos bancos nesse setor, principais intermediários financeiros da economia. Com isso, em um mercado em desenvolvimento, torna-se cada vez mais importante a correta avaliação e administração do risco financeiro envolvido nas operações: o risco de crédito. Nesse contexto, a classificação de rating surge como referência para investidores. No entanto, como o mercado bancário brasileiro ainda é pouco desenvolvido, apenas instituições de grande porte são classificados pelas agências de rating em funcionamento no país. Este trabalho tem como objetivo o desenvolvimento de uma metodologia de rating baseada no modelo ordered probit, que seja capaz de replicar o nível de rating de uma determinada agência, e assim conseguir estimar o nível de rating para aqueles bancos que não têm a referida classificação de rating

Basiléia II e exigência de capital para risco de crédito dos bancos no Brasil

Com a implementação do Acordo de Basiléia II no Brasil, os grandes conglomerados bancários poderão utilizar o chamado modelo IRB (Internal Ratings Based) para cômputo da parcela de risco de crédito da exigência de capital. O objetivo deste trabalho é mensurar a diferença entre o capital mínimo exigido (e, conseqüentemente, do Índice de Basiléia) calculado pela abordagem IRB em relação à regulamentação atual. Para isso, foram estimadas probabilidades de inadimplência (PD) utilizando matrizes de transição construídas a partir dos dados da Central de Risco de Crédito (SCR) do Banco Central do Brasil. Os resultados indicam aumento da exigência de capital, ao contrário do ocorrido nos países do G-10

Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico

Credit risk management has assumed increasing importance for the managers and directors of enterprises. Thus, different approaches aimed to measure the probability of default are under discussion nowadays. This paper evaluates models that have become more popular over the last 30 years in order forecast defaults or to provide information regarding to financial difficulties of enterprises. This paper will focus on the KMV model in order to estimate the probability of default, its methodology based on market value of the asset and its volatility and finally estimate the probability of default. Finally, to test the KMV model will be used a sample of global steel companies that have credit in Companhia Vale do Rio Doce (CVRD), which will allow us to make comparisons with the models presented in this work.

A influência dos ativos intangíveis na análise de risco de crédito de empresas de base tecnológica

Evolution is present in world dynamics. And it is just in such transformational environment where companies have been encapsulated. In an economy of knowledge, physical assets alone are unable to provide profits to meet shareholders' demands. Now there comes an invisible component with the purpose of defining strategies and impelling results: Intangible Assets. Banking financing systems, however, have not kept pace with this knowledge revolution and its resulting new income generation techniques. Credit analysis methods for most financing agents would not employ any intangible parameters in their methodology of study as yet. This paper seeks to discuss the importance of intangible assets by focusing their role of influencial factor in decisions to finance technology-based companies. By studying the credit risk classification system employed by FINEP, Brazil's Federal Agency for innovation development, we wished to suggest indicators for intangibles which might be put to use in the Financiadora.