El riesgo de interés estructural es la potencial alteración que se produce en el margen financiero y/o en el valor económico (valor patrimonial) de una institución financiera debido a la variación de los tipos de interés. La exposición a movimientos adversos en los tipos de interés constituye un riesgo inherente al desarrollo de la actividad bancaria que, al mismo tiempo, se convierte en una oportunidad que suele ser bien aprovechada para la creación de valor económico. Por ello, el riesgo de interés debe ser medido y gestionado de manera que no sea excesivo con relación al patrimonio de la institución financiera, y que guarde una relación razonable con el resultado económico estimado por la gerencia y los accionistas. El presente artículo considera una serie de métricas con las que se calculan indicadores del riesgo de interés estructural: GAP contable, Margen en Riesgo (MeR), Ganancia en Riesgo (GeR), Sensibilidad de Margen Financiero (SMF), Duration GAP, Valor Patrimonial en Riesgo (VPR) y la Sensibilidad de Valor Económico (SVE)

nÃo hà / A dissertaÃÃo trata da gestÃo de investimentos das entidades fechadas de previdÃncia complementar (EFPC) no Brasil. O tema à abordado em cinco capÃtulos. No primeiro, à apresentado uma visÃo atuarial dessas entidades, atravÃs de um breve histÃrico sobre o setor, e dos conceitos envolvidos no seu estudo. No segundo, a abordagem à financeira, destacando os segmentos do mercado financeiro brasileiro, onde as entidades aplicam seus recursos e discorrendo sobre as modernas tÃcnicas de geraÃÃo de cenÃrios econÃmicos. No terceiro capÃtulo mostramos as modelagens mais utilizadas em se tratando de dimensionamento de ativos financeiros. No quarto à realizada uma explanaÃÃo sobre modelagem de passivos atuariais em fundos de pensÃo. No Ãltimo capÃtulo à mostrado um estudo de caso com sua implementaÃÃo e anÃlise. O resultado deste trabalho foi a definiÃÃo e implementaÃÃo de um modelo de ALM simplificado para ser utilizado em um Fundo de PensÃo com Plano de BenefÃcio do Tipo BenefÃcio Definido. / This study broachs the management of the investments of a Brazilian pension fund - EFPC. The theme is described in five chapters. In the first one is presented a actuarial vision of a EFPC, through a short historic about the sector and about the concepts involved especially concerning to the segments of the Brazilian financial Market. In the second, where the EFPC invests his resources and talking about the modern techniques of generation of economics scenario. In the third chapter we show the most used modeling in dimension of financial actives. The fourth shows a explanation about Modeling of Actuaries passives in pension funds. In the last one is showed a study of case including their implementation and analysis. The result of this work was definitions and implementation of a model of simplified ALM to be used in a pension fund with a defined benefit plans.

This thesis focuses on the stability of ALM models formulated as problems of multistage stochastic programming, with respect to reductions in scenario tree. In the first chapter, we introduce multistage stochastic programming problem and the chosen approach of the master scenario tree generation. The second chapter describes models of asset price evolution in time and clustering algo- rithm used for generation of the master tree. In the third chapter, we describe three random and three deterministic scenario tree reduction algorithms. In the fourth chapter, we formulate two pension fund ALM problems - the first one is four-stage problem, the second one is seven-stage problem. The fifth chap- ter is dedicated to the description of the practical part of the thesis, in which we study and compare the stability of the objective function and the solutions in individual stages with respect to scenario tree reductions obtained from the algorithms described in the third chapter. 1

Práce porovnává základní přístupy a možnosti v řízení portfolií aktiv institucionálními investory, přičemž se zaměřuje zejména na penzijní fondy a pojišťovny. V jednotlivých kapitolách se nejprve věnuje omezením, na něž portfolio manažeři naráží při umisťování prostředků uvedených finančních institucí. Dále přibližuje třídy aktiv, tradiční i alternativní, do nichž je možné investovat volné prostředky, s nimi spojená rizika a nástroje pro jejich měření. Podrobně rozebrány jsou základní přístupy pro správu portfolia: Benchmarking, ALM a Risk budgeting. V závěru jsou uvedeny nejpoužívanější investiční strategie pro řízení části portfolia s dodatečnými požadavky na riziko nebo výnos.

Thesis (M.Com. (Risk Management))--North-West University, Potchefstroom Campus, 2009.

In the last decade, the financial service industry has become increasingly aware of the dangers posed by operational risk. Profound changes in the economic and financial environment have made it necessary for banks in general to adapt their long term strategies as well as their approaches to the management of their assets and liabilities. Regardless of this heightened awareness, banks continue to fail at effective management of these risks. The Asset and Liability Management Committee (ALCO) is responsible for managing a bank's assets and liabilities to balance its many risk exposures and thereby help it achieve its operating objectives e.g. maximising Net Interest Income (Nil). Thus the ALCO process is the crux of the strategic management process performed within a bank. The ALCO process is driven by people, processes and technology which, in essence, is a broad definition of operational risk. Failure in any one of these areas will lead to failure of the ALCO, ALCO processes and, therefore, the strategic Asset and Liability Management (ALM). The focus of this study is, therefore, how to measure and manage operational risk in a bank's ALCO process. A case study was conducted, with the aid of ALCO experts in a specialised niche bank in South Africa, to identify operational risks within this bank's ALCO process. The various risk indicators of operational risk were classified into 5 broad categories. Each category was weighted according to its representative risk indicator and converted into percentages for the interpretation of the overall results. Category 2 (authority levels) has the highest negative impact, while the remaining 4 categories (employee, model, system and other indicators) have a medium negative impact, on the efficiency of the ALCO process. / Thesis (M.Com. (Risk Management))--North-West University, Potchefstroom Campus, 2009.

In the last decade, the financial service industry has become increasingly aware of the dangers posed by operational risk. Profound changes in the economic and financial environment have made it necessary for banks in general to adapt their long term strategies as well as their approaches to the management of their assets and liabilities. Regardless of this heightened awareness, banks continue to fail at effective management of these risks. The Asset and Liability Management Committee (ALCO) is responsible for managing a bank's assets and liabilities to balance its many risk exposures and thereby help it achieve its operating objectives e.g. maximising Net Interest Income (Nil). Thus the ALCO process is the crux of the strategic management process performed within a bank. The ALCO process is driven by people, processes and technology which, in essence, is a broad definition of operational risk. Failure in any one of these areas will lead to failure of the ALCO, ALCO processes and, therefore, the strategic Asset and Liability Management (ALM). The focus of this study is, therefore, how to measure and manage operational risk in a bank's ALCO process. A case study was conducted, with the aid of ALCO experts in a specialised niche bank in South Africa, to identify operational risks within this bank's ALCO process. The various risk indicators of operational risk were classified into 5 broad categories. Each category was weighted according to its representative risk indicator and converted into percentages for the interpretation of the overall results. Category 2 (authority levels) has the highest negative impact, while the remaining 4 categories (employee, model, system and other indicators) have a medium negative impact, on the efficiency of the ALCO process. / Thesis (M.Com. (Risk Management))--North-West University, Potchefstroom Campus, 2009.

Structural interest risk rate is the potential change that occurs in a financial institution’s financial margin and/or the economic value (market value) due to a variation in the types of interest. The exposure to adverse movement in the types of interest is an inherent risk in banking activity that, at the same time, becomes an opportunity that can be used to create economic value. As such, interest rate risk should be measured and managed such that it isn’t too high in relation to the financial institution’s assets and that it is reasonable in relation to the economic performance that management and stockholders estimate. This article considers a series of metrics that calculate structural interest rate risk indicators: accounting GAP, margin at risk, earnings at risk, financial margin sensitivity, duration GAP, asset value at risk and economic value sensitivity. / Revisión por pares

Este trabalho trata de uma aplicação de programação estocástica para administração de passivos e ativos. Inicialmente, um modelo de administração de ativos e passivos utilizando valores de retorno de ativos determinísticos é formalizado, constatando-se as suas limitações, justificando-se a necessidade de abranger formalmente a incerteza inerente aos mercados financeiros. Para isso, um modelo para administração de ativos e passivos que utiliza otimização e programação estocástica baseado em uma árvore de cenários multiestágio balanceada é apresentado, descrito, e implementado. Os seus resultados determinam uma política de investimento de ativos para o instante inicial do período considerado, definindo-se também uma regra que possibilita, a partir do equilíbrio entre o patrimônio inicial e total de passivo a ser pago ao final do período considerado, estimar a probabilidade de insolvência do fundo de pensão. Além disso, realiza-se o estudo do impacto da redução de uma proxy da taxa de juros básico na composição do portfólio administrado por essas empresas. / This work discusses an application of stochastic programming for asset-liability management. Initially, a deterministic asset-liability model is formalized. Its limitations become clear which justify the need to include uncertainty in the model. Then, a stochastic programming model based on a balanced multistage scenario tree is presented, described and implemented for an asset-liability environment. The main results are: (i) an investment policy for the fund, and, (ii) the pension’s fund insolvency probability considering an initial relation between the current assets and the present value of the future liabilities. The impact of a possible reduction in interested rate on the pension’s fund optimal portfolio is also presented.

Este trabalho trata de uma aplicação de programação estocástica para administração de passivos e ativos. Inicialmente, um modelo de administração de ativos e passivos utilizando valores de retorno de ativos determinísticos é formalizado, constatando-se as suas limitações, justificando-se a necessidade de abranger formalmente a incerteza inerente aos mercados financeiros. Para isso, um modelo para administração de ativos e passivos que utiliza otimização e programação estocástica baseado em uma árvore de cenários multiestágio balanceada é apresentado, descrito, e implementado. Os seus resultados determinam uma política de investimento de ativos para o instante inicial do período considerado, definindo-se também uma regra que possibilita, a partir do equilíbrio entre o patrimônio inicial e total de passivo a ser pago ao final do período considerado, estimar a probabilidade de insolvência do fundo de pensão. Além disso, realiza-se o estudo do impacto da redução de uma proxy da taxa de juros básico na composição do portfólio administrado por essas empresas. / This work discusses an application of stochastic programming for asset-liability management. Initially, a deterministic asset-liability model is formalized. Its limitations become clear which justify the need to include uncertainty in the model. Then, a stochastic programming model based on a balanced multistage scenario tree is presented, described and implemented for an asset-liability environment. The main results are: (i) an investment policy for the fund, and, (ii) the pension’s fund insolvency probability considering an initial relation between the current assets and the present value of the future liabilities. The impact of a possible reduction in interested rate on the pension’s fund optimal portfolio is also presented.