Commercial mortgage underwriters have traditionally relied upon a standard set of criteria for approving and pricing loans. The increased level of commercial mortgage loan defaults from 1% at the start of 2009 to 9.32% by the end of 2011 provides motivation for questioning underwriting standards which previously served the lending industry well. This dissertation investigates factors that affect the probability of Non-performance among commercial mortgage-backed security (CMBS) loans, proposes conditions under which the standard ratios may not apply, and tests additional criteria which may prove useful during economic periods previously not experienced by commercial mortgage underwriters. In this dissertation, Cap Rate Spread, the difference between the cap rate of a property and the Coupon Rate of the associated loan, is introduced to test whether the probability of Non-performance can be better predicted than by relying on traditional commercial mortgage underwriting criteria such as Loan to Value (LTV) and Debt Service Coverage Ratio (DSCR). Testing the research hypotheses with a probit model using a database of 47,883 U.S. CMBS loans from 1993 to 2011, Cap Rate Spread is found to have a significantly negative relationship with loan Non-performance. That is, as the Cap Rate Spread falls, the probability of Non-performance rises appreciably. A numerical model suggests that among loans which would have passed the standard ratio tests requiring loans to have values of LTV less than .8 and DSCR greater than 1.25, a Cap Rate Spread criteria requiring loans to have a value greater than 1% would have prevented the origination of an additional 1,798 CMBS loans reducing the rate of Non-performance from 14.9% with only the LTV and DSCR criteria to just 11.6% by adding the Cap Rate Spread criteria. Of course, adding additional criteria will also lead to errors of rejecting loans which would have performed well. Back testing with the same sample of CMBS loans, this Type I error rate rises from 19% with only the LTV and DSCR criteria to 34% with the addition of the Cap Rate Spread. Ultimately, CMBS loan underwriters must individually determine an acceptable level of Non-performance appropriate to their business model and tolerance for risk. Using intuition, experience, tools, and rules, each underwriter must choose a balance between the competing risks of rejecting potentially profitable loans and accepting loans which will fail. This research result is important because it helps deepen our understanding of the relationships between property income and loan performance and provides an additional tool that underwriters may employ in assessing CMBS loan risk.

La Universidad Peruana de Ciencias Aplicadas (UPC) fue sede de la segunda edición del “University Premium Training” organizada por Bloomberg, empresa líder en información financiera y económica a nivel mundial. / El evento, que fue realizado los días 5, 6 y 7 de noviembre en el campus San Isidro, tuvo como objetivo poder reforzar las competencias de los docentes de diversas universidades de Lima que emplean Bloomberg como una herramienta didáctica para la educación y planificación financiera. Esta compañía brinda herramientas de software financiero, como análisis, plataformas de comercio capital y servicios de datos para las empresas quienes deseen consultar información bursátil y financiera en tiempo real. / Además, se contó con la participación de expertos que emplean la herramienta como apoyo para la toma de decisión financiero: Lizzette Lara; especialista en riesgos y derivados, André Lapponi; especialista Senior en Portafolio y Análisis técnico, Pedro Cortejo, CEO-Founder de Decision Capital, entre otros. / Se explica cómo mejorar el flujo de aprendizaje de la terminal en las universidades, los flujos de información en los equipos de trabajo, y las bases de datos de índices. Finalmente, se presentan ejemplos y casos y se interpretaron algunos gráficos. Ponente: Javier Rojas, responsable por las operaciones de Bloomberg en Perú.

La Universidad Peruana de Ciencias Aplicadas (UPC) fue sede de la segunda edición del “University Premium Training” organizada por Bloomberg, empresa líder en información financiera y económica a nivel mundial. / El evento, que fue realizado los días 5, 6 y 7 de noviembre en el campus San Isidro, tuvo como objetivo poder reforzar las competencias de los docentes de diversas universidades de Lima que emplean Bloomberg como una herramienta didáctica para la educación y planificación financiera. Esta compañía brinda herramientas de software financiero, como análisis, plataformas de comercio capital y servicios de datos para las empresas quienes deseen consultar información bursátil y financiera en tiempo real. / Además, se contó con la participación de expertos que emplean la herramienta como apoyo para la toma de decisión financiero: Lizzette Lara; especialista en riesgos y derivados, André Lapponi; especialista Senior en Portafolio y Análisis técnico, Pedro Cortejo, CEO-Founder de Decision Capital, entre otros. / Se explican los conceptos de pre trade y post trade, su análisis, dónde se encuentran las cotizaciones, y su ejecución (post trade). Finalmente, se explica el análisis de renta fija. Ponente: Lizette Lara, especialista de riesgo y derivados – Bloomberg.

yes / This paper evaluates the use of specialist software within university trading rooms in order to enable students to experience a simulated environment which allows them to gain an appreciation of “real life” decision-making within the nance and banking industry and become familiar with real-time data. An important additional aim of trading room-based instruction is to encourage responsible nancial decision-making. Our analysis focuses on business schools within the United Kingdom and provides a detailed illustration of use of such resources, in particular, as deployed at the Bradford University School of Management. We provide a critical overview of the main challenges involved in making e ective use of a trading room. We also offer recommendations to other academics to enable productive and appropriate use of resources such as Bloomberg Professional in order to enhance the student learning experience and to facilitate the development of valuable skills.

The aim of the work is to analyze the theoretical basis of determination of the market risk premium in conditions of the national market in the Czech Republic with CAPM and practical procedures of its determination using the market data provided by Bloomberg. The work addresses some open problems of practical determination of market risk premium as a choice between historical and implied risk premium, determination of credit spread as a representative of country risk and accurate determination of the equity and bond market volatility ratio. The thesis also contains research on the cost of equity and single-factor sensitivity analysis demonstrating the significant influence of a small change in one parameter entering the calculation of the discount rate on the resulting value.