The Case for Macro Risk Budgeting and Portfolio Tranching in Reserves Management

The set of objectives in reserves management are normally predifined and include: Protecting the economy against potential external shocks on the current account or on capital flows; invest the reserves minimizing the potential of a loss and ensuring the availability of international liquidity when necessary. Whereas the adoption of a floating exchange rate in theory reduces the need for reserves to protect against external shocks, in the context of free capital movements it will be a function of the efficiency of international markets.

The Factor-Portfolios Approach to Asset Management using Genetic Algorithms

We present an investment process that: (i) decomposes securities into risk factors; (ii) allows for the construction of portfolios of assets that would selectively expose the manager to desired risk factors; (iii) perform a risk allocation between these portfolios, allowing for tracking error restrictions in the optimization process and (iv) give the flexibility to manage dinamically the transfer coeffficient (TC). The contribution of this article is to present an investment process that allows the asset manager to limit risk exposure to macro-factors - including expectations on correlation dynamics - whilst allowing for selective exposure to risk factors using mimicking portfolios that emulate the behaviour of given specific. An Artificial Intelligence (AI) optimisation technique is used for risk-budget allocation to factor-portfolios.Active Management, Portfolio Optimization, Genetic Algorithms, Propensities. Classification JEL: G11; G14; G32.

Portfolio Optimization and Long-Term Dependence

Whilst emphasis has been given to short-term dependence of financial returns, long-term dependence remains overlooked. Despite financial literature provides evidence of long-term’s memory existence, serial-independence assumption prevails. This document’s long-term dependence assessment relies on rescaled range analysis (R/S), a popular and robust methodology designed for Geophysics but extensively used in financial literature. Results correspond to most of the previous evidence of significant long-term dependence, particularly for small and illiquid markets, where persistence is its most common kind. Persistence conveys that the range of possible future values of the variable will be wider than the range of purely random and independent variables. Ahead of R/S financial literature, authors estimate an adjusted Hurst exponent in order to properly estimate the covariance matrix at higher investment horizons, avoiding the traditional -independence reliant- square-root-of-time rule. Ignoring long-term dependence within the mean-variance portfolio optimization results in concealed risk taking; conversely, by adjusting for long-term dependence the weight of high (low) persistence risk factors decreases (increases) as the investment horizon widens. This alleviates some well-known shortcomings of conventional portfolio optimization for long-term investors (e.g. central banks, pension funds and sovereign wealth managers), such as excessive risk taking in long-term portfolios, extreme weights, home bias, and reluctance to hold foreign currency-denominated assets.Portfolio optimization, Hurst exponent, long-term dependence, biased random walk, rescaled range analysis. Classification JEL: G11, G32, G20, C14.

Montecarlo simulation of long-term dependent processes: a primer

As a natural extension to León and Vivas (2010) and León and Reveiz (2010) this paper briefly describes the Cholesky method for simulating Geometric Brownian Motion processes with long-term dependence, also referred as Fractional Geometric Brownian Motion (FBM). Results show that this method generates random numbers capable of replicating independent, persistent or antipersistent time-series depending on the value of the chosen Hurst exponent. Simulating FBM via the Cholesky method is (i) convenient since it grants the ability to replicate intense and enduring returns, which allows for reproducing well-documented financial returns’ slow convergence in distribution to a Gaussian law, and (ii) straightforward since it takes advantage of the Gaussian distribution ability to express a broad type of stochastic processes by changing how volatility behaves with respect to the time horizon. However, Cholesky method is computationally demanding, which may be its main drawback. Potential applications of FBM simulation include market, credit and liquidity risk models, option valuation techniques, portfolio optimization models and payments systems dynamics. All can benefit from the availability of a stochastic process that provides the ability to explicitly model how volatility behaves with respect to the time horizon in order to simulate severe and sustained price and quantity changes. These applications are more pertinent than ever because of the consensus regarding the limitations of customary models for valuation, risk and asset allocation after the most recent episode of global financial crisis.Montecarlo simulation, Fractional Brownian Motion, Hurst exponent, Long-term Dependence, Biased Random Walk. Classification JEL: C15, C53, C63, G17, G14.

Operational Risk Management using a Fuzzy Logic Inference System

Operational Risk (OR) results from endogenous and exogenous risk factors, as diverse and complex to assess as human resources and technology, which may not be properly measured using traditional quantitative approaches. Engineering has faced the same challenges when designing practical solutions to complex multifactor and non-linear systems where human reasoning, expert knowledge or imprecise information are valuable inputs. One of the solutions provided by engineering is a Fuzzy Logic Inference System (FLIS). Despite the goal of the FLIS model for OR is its assessment, it is not an end in itself. The choice of a FLIS results in a convenient and sound use of qualitative and quantitative inputs, capable of effectively articulating risk management's identification, assessment, monitoring and mitigation stages. Different from traditional approaches, the proposed model allows evaluating mitigation efforts ex-ante, thus avoiding concealed OR sources from system complexity build-up and optimizing risk management resources. Furthermore, because the model contrasts effective with expected OR data, it is able to constantly validate its outcome, recognize environment shifts and issue warning signals.Operational Risk, Fuzzy Logic, Risk Management Classification JEL:G32, C63, D80

Efficient Portfolio Optimization in the Wealth Creation and Maximum Drawdown Space

First developed by Markowitz (1952), the mean-variance framework is the most widespread theoretical approximation to the portfolio problem. Nevertheless, successful application in the investment community has been limited. Assumptions such as normality of returns and a static correlation matrix could partially account for this. To overcome some of the limitations of the mean-variance framework, mainly the choice of the risk metric and the inconvenience of using an estimated correlation matrix typical of tranquil or euphoria periods, this paper proposes an alternative risk measure: the maximum drawdown (MDD), and combines it with a wealth creation measure to define a new portfolio optimization space. Like other market practitioners’ measures, MDD lacks of a complete and solid theoretical foundation. In an effort to contribute to its theoretical foundation, this paper uses common sense and financial intuition to introduce such measure, followed by a review of its technical advantages and coherence for risk management. Finally, an application of a MDD risk metric based portfolio optimization model is presented. The main findings indicate this proposal may effectively help overcome some of the traditional mean-variance shortcomings and provide some useful tools for portfolio optimization in practice. For long-term performance driven portfolios, such as pension funds, this approach may yield interesting results because it focuses on wealth creation over the long run.Portfolio Optimization, Asset Allocation, Downside Risk, Maximum Drawdown, mean-variance Criteria, Diversification. Classification JEL: G11; G23; G32; D81.

Artificial Markets under a Complexity Perspective

The focus of this study is to build, from the ‘bottom-up’, a market with artificially intelligent adaptive agents based on the institutional arrangement of the Colombian Foreign Exchange Market (1994-1999) in order to determine simple agents’ design, rules and interactions that are sufficient to create interesting behaviours at the macroscopic level - emerging patterns that replicate the properties of the time series from the case study. Tools from artificial intelligence research, such as genetic algorithms and fuzzy logic, are the basis of the agents’ mental models, which in turn are used for forecasting, quoting and learning purposes in a double auction market. Sets of fuzzy logic rules yield adequate, approximately continuous risk and utility preferences without the need to fix their mathematical form ex-ante. Statistical properties of financial time series are generated by the artificial market, as well as some additional non-linearity linked to the existence of a crawling band. Moreover, the behaviour of the simulated exchange rate is consistent with currency band theory. Agent’s learning favours forecasting rules based on regulatory signals against rules based on fundamental information. Also, intra-day volatility is strongly linked to the rate of arrival and size of real sector trades. Intra-day volatility is also a function of the frequency of learning and search specialisation. It is found that when a moderately low frequency of learning is used, volatility increases.Adaptive agents, artificial markets, constrained generating procedures, fuzzy logic and genetic algorithms. Classification JEL: G1; G12; G39.

Administración de fondos de pensiones y multifondos en Colombia

Este documento evalúa la regulación vigente relacionada con la inversión de los recursos de los Fondos de Pensiones Obligatorios (FPO), para lo cual se analiza el perfil de eficiencia del sistema dadas sus actuales restricciones. De acuerdo con los resultados obtenidos, se observa que el marco regulatorio de las inversiones de los FPO restringen el retorno esperado y hace que los administradores de portafolios no accedan a niveles superiores de retorno por unidad de riesgo con mayores beneficios de diversificación. Las propuestas apuntan hacia la flexibilización de las restricciones a las inversiones y a su adecuación al perfil de riesgo de los cotizantes, utilizando para ello el esquema de multifondos implementado en otros países de la región.Regulación de los Fondos de Pensiones Obligatorios, Fronteras Eficientes, Multifondos, Portafolio de Referencia. Classification JEL: G18; G11; G23.

La dolarización financiera: Experiencia internacional y perspectivas para Colombia

Las monedas locales de los países en vías de desarrollo, además de no ser libremente convertibles a nivel internacional, suelen experimentar niveles de inflación superiores y más volátiles, al tiempo que tienden a sufrir periodos de fuerte apreciación y depreciación. Estas bien conocidas características no solo implican un reto para las autoridades económicas de estos países, sino que también llaman la atención sobre la capacidad de las monedas locales para cumplir cabalmente con sus funciones. Colombia, a pesar de ser reconocida por su historial de manejo monetario disciplinado, no ha escapado a ocasionales cuestionamientos sobre la conveniencia de mantener el peso para cumplir con las funciones de la moneda. Estos esporádicos cuestionamientos coinciden con periodos de fuerte apreciación o depreciación de la moneda, en los cuales se han escuchado interrogantes sobre la conveniencia de llevar a cabo una dolarización total o parcial de la economía. Al respecto, son pocos los países que han optado por reemplazar totalmente la moneda local por una extranjera para que esta última cumpla con todas las funciones de la moneda, pero sí son muchos los países que han permitido la dolarización parcial de la economía. Basado en la experiencia internacional, y en especial por las características de la economía colombiana, este documento concluye que la dolarización financiera conllevaría costos elevados, en especial si se comparan con unos beneficios limitados y apenas potenciales.Dolarización; dolarización financiera; dolarización parcial; indexación; fear of floating; riesgo cambiario. Classification JEL: F31; F33; F36.

Recomendaciones para la modificación del régimen de pensiones obligatorias de Colombia

Este documento evalúa la regulación vigente relacionada con la administración de los portafolios de los Fondos de Pensiones Obligatorios (FPO), para esto revisa la literatura relacionada con la eficiencia del Sistema dadas sus actuales restricciones. Se concluye que el marco regulatorio de las inversiones de los FPO restringen el retorno esperado y hace que los administradores de portafolios no accedan a niveles superiores de retorno por unidad de riesgo con mayores beneficios de diversificación. Así mismo se limita la capacidad del administrador de construir portafolios que reflejen el perfil de riesgo del afiliado. Se muestra que la fórmula de rentabilidad mínima genera incentivos perversos para que las AFP´s no incurran en riesgo llevando a los Administradores a estrategias que sincronicen los retornos de los portafolios para minimizar el impacto de la incertidumbre generado por la fórmula de rentabilidad mínima. Las propuestas van en el sentido de flexibilizar las inversiones y adecuarlas de acuerdo al perfil de riesgo de los cotizantes utilizando el esquema de Multifondos implementando en otros países de la región.Regulación de los Fondos de Pensiones Obligatorios, Fronteras eficientes, Multifondos, Portafolio de referencia. Classification JEL: G18; G11; G23.