Implementación de cópulas para la estimación del valor en riesgo

La dependencia entre las series financieras, es un parámetro fundamental para la estimación de modelos de Riesgo. El Valor en Riesgo (VaR) es una de las medidas más importantes utilizadas para la administración y gestión de Riesgos Financieros, en la actualidad existen diferentes métodos para su estimación, como el método por simulación histórica, el cual no asume ninguna distribución sobre los retornos de los factores de riesgo o activos, o los métodos paramétricos que asumen normalidad sobre las distribuciones. En este documento se introduce la teoría de cópulas, como medida de dependencia entre las series, se estima un modelo ARMA-GARCH-Cópula para el cálculo del Valor en Riesgo de un portafolio compuesto por dos series financiera, la tasa de cambio Dólar-Peso y Euro-Peso. Los resultados obtenidos muestran que la estimación del VaR por medio de copulas es más preciso en relación a los métodos tradicionales.

Poor people and risky business

We try to explain why economic conflicts and illegal business often take place in poor countries. We use the concept of subsistence level of consumption (d) and assume a regular concave utility function for consumption levels higher than d. For consumption levels lower than d utility is constant and equal to zero. Under this framework poor agents are risk-lovers. This result helps to explain why economic conflicts are more likely to appear in poor economies and why poor agents are more willing to undertake illegal business.

An Empirical Examination of the Determinants of Foreign Direct Investment: A Firm-Level Analysis for the Colombian Economy

We use a large firm level data set to investigate the determinants of foreign direct investment(FDI) in Colombia. We estimate econometric models for the determinants of the probabilitythat a firm receives FDI, as well as for the factors that help to explain the foreign share in afirm’s capital. The results show that firms listed on the stock market, involved in foreign tradeactivities, and operating in sectors with greater capital intensity are more likely to be recipientsof FDI. Also, the probability of a firm receiving FDI is directly related to its size.

Ciencias de la complejidad: estado actual

Los aportes teóricos y aplicados de la complejidad en economía han tomado tantas direcciones y han sido tan frenéticos en las últimas décadas, que no existe un trabajo reciente, hasta donde conocemos, que los compile y los analice de forma integrada. El objetivo de este proyecto, por tanto, es desarrollar un estado situacional de las diferentes aplicaciones conceptuales, teóricas, metodológicas y tecnológicas de las ciencias de la complejidad en la economía. Asimismo, se pretende analizar las tendencias recientes en el estudio de la complejidad de los sistemas económicos y los horizontes que las ciencias de la complejidad ofrecen de cara al abordaje de los fenómenos económicos del mundo globalizado contemporáneo.

La disonancia cognitiva y trampa de la memoria en decisiones de Inversión: caso colombiano

Este documento es el resultado de una investigación bajo el enfoque de Finanzas Corporativas del Comportamiento, disciplina relevante en el mundo financiero desde el 2002 y que hasta el momento poco se ha investigado en Colombia. Esta difiere del supuesto tradicional de la racionalidad de los individuos en la toma de decisiones financieras, ya que pueden ser influenciadas por sesgos cognitivos y emocionales que la teoría ortodoxa no tiene en cuenta en sus supuestos. Esta investigación busca indagar, desde el punto de vista conceptual y mediante el análisis de resultados de estudio de campo con operadores del mercado bursátil colombiano, sobre la posible presencia de elementos comportamentales en las decisiones de inversión. Los sesgos que se evaluaron fueron: disonancia cognitiva, heurístico de disponibilidad y sesgo de confirmación. Para la recolección de fuentes primarias, una encuesta fue enviada a los operadores Colombianos, categorizados en operadores con experiencia y operadores jóvenes. Después del filtro, 142 encuestas fueron seleccionadas para el análisis. Los principales hallazgos fueron que los jóvenes son más propensos a experimentar disonancia cognitiva y heurístico de disponibilidad y en ambas categorías, los sesgos analizados influencian medianamente la toma de decisiones de inversión.

Las implicaciones geopolíticas de la construcción del Canal de Nicaragua para el vecindario del Caribe Occidental (2006-2014)

El presente estudio de caso, busca explicar cuáles son las posibles implicaciones e influencia de la construcción del Proyecto del Canal de Nicaragua en la geografía, la economía y la política exterior del Caribe Occidental. Esta investigación defiende que la construcción de este canal influirá en el largo plazo en la geopolítica de esta región, debido a la posibilidad de una competencia hasta hoy inexistente en la región entre dos canales interoceánicos, que puede llegar a afectar la disponibilidad de recursos naturales de la subregión, y asimismo, fortalecer la presencia asiática en América Latina; sin embargo, las consecuencias de este canal no pueden determinarse de manera específica. Para sustentar lo anterior, se realizará una revisión del proceso de construcción del canal de Panamá y del proyecto del de Nicaragua, para establecer un estudio de prospectiva de los escenarios posibles para la región del Caribe Occidental.

Efectos en los mercados financieros internacionales de la derogatoria en 1999 de la Ley Glass Steagall de los EE.UU. (Tema Central)

Actualmente la profunda crisis del sistema financiero internacional, similar a la que vivió Estados Unidos en los años treinta, es el punto más importante de discusión en todo el mundo. Por ello, se consideró importante realizar un análisis de la Ley Glass Steagall Act, promulgada en el año 1933, justamente como una salida a la crisis financiera estadounidense, de aquella época, precisando cuáles son sus principales características, y sobre todo los efectos que su derogatoria (en 1999) trajo consigo en el sistema financiero mundial, pues como veremos, para muchos la actual crisis es producto de la inadecuada mezcla de regulación y libertad que se produjo con la promulgación de la Ley Gramm Leach Bliley Act, mediante la cual los bancos comerciales empezaron a incursionar en operaciones bursátiles, actividades que anteriormente estaban vetadas, y por tanto existían garantías suficientes para los depositantes.

Drivers of fund performance: a panel data analysis

The principle aim of this research is to elucidate the factors driving the total rate of return of non-listed funds using a panel data analytical framework. In line with previous results, we find that core funds exhibit lower yet more stable returns than value-added and, in particular, opportunistic funds, both cross-sectionally and over time. After taking into account overall market exposure, as measured by weighted market returns, the excess returns of value-added and opportunity funds are likely to stem from: high leverage, high exposure to development, active asset management and investment in specialized property sectors. A random effects estimation of the panel data model largely confirms the findings obtained from the fixed effects model. Again, the country and sector property effect shows the strongest significance in explaining total returns. The stock market variable is negative which hints at switching effects between competing asset classes. For opportunity funds, on average, the returns attributable to gearing are three times higher than those for value added funds and over five times higher than for core funds. Overall, there is relatively strong evidence indicating that country and sector allocation, style, gearing and fund size combinations impact on the performance of unlisted real estate funds.

The impact of 9/11 on US REIT returns: fundamental or financial?

Following the attack on the World Trade Center on 9/11 volatility of daily returns of the US stock market rose sharply. This increase in volatility may reflect fundamental changes in the economic determinants of prices such as expected earnings, interest rates, real growth and inflation. Alternatively, the increase in volatility may simply reflect the effects of increased uncertainty in the financial markets. This study therefore sets out to determine if the effects of the attack on the World Trade Center on 9/11 had a fundamental or purely financial impact on US real estate returns. In order to do this we compare pre- and post-9/11 crisis returns for a number of US REIT indexes using an approach suggested by French and Roll (1986), as extended by Tuluca et al (2003). In general we find no evidence that the effects of 9/11 had a fundamental effect on REIT returns. In other words, we find that the effect of the attack on the World Trade Center on 9/11 had only a financial effect on REIT returns and therefore was transitory.

The case for REITs in the mixed-asset portfolio in the short and long run

The poor performance of the Stock Market in the US up to the middle of 2003 has meant that REITs are increasingly been seen as an attractive addition to the mixed-asset portfolio. However, there is little evidence to indicate the consistency of the role REITs should play a role in the mixed-asset portfolio over different investment horizons. The results highlight that REITs do play a significant role over both different time horizons and holding periods. The findings show that REITs attractiveness as a diversification asset increase as the holding period increases. In addition, their diversification qualities span the entire efficient frontier, providing return enhancement properties at the lower end, switching to risk reduction qualities at the top end of the frontier.

Analyzing the performance of non-listed real estate funds: an panel data analysis

The rapid growth of non-listed real estate funds over the last several years has contributed towards establishing this sector as a major investment vehicle for gaining exposure to commercial real estate. Academic research has not kept up with this development, however, as there are still only a few published studies on non-listed real estate funds. This paper aims to identify the factors driving the total return over a seven-year period. Influential factors tested in our analysis include the weighted underlying direct property returns in each country and sector as well as fund size, investment style gearing and the distribution yield. Furthermore, we analyze the interaction of non-listed real estate funds with the performance of the overall economy and that of competing asset classes and found that lagged GDP growth and stock market returns as well as contemporaneous government bond rates are significant and positive predictors of annual fund performance.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

The interaction of volatility, volume and skewness: empirical evidence from REITs

This paper considers how trading volume impacts upon the first three moments of REIT returns. Consistent with previous studies of the broader stock market, we find that volume is a significant factor with respect to both returns and volatility. We also find evidence supportive of the Hong & Stein’s (2003) Investor Heterogeneity Theory with respect to the finding that skewness in REIT index returns is significantly related to volume. Furthermore, we also report findings that show the influence of the variability of volume with skewness.

Macro-economic and financial determinants of comovement across global real estate security markets

This paper models the determinants of integration in the context of global real estate security markets. Using both local and U.S. Dollar denominated returns, we model conditional correlations across listed real estate sectors and also with the global stock market. The empirical results find that financial factors, such as the relationship with the respective equity market, volatility, the relative size of the real estate sector and trading turnover all play an important role in the degree of integration present. Furthermore, the results highlight the importance of macro-economic variables in the degree of integration present. All four of the macro-economic variables modeled provide at least one significant result across the specifications estimated. Factors such as financial and trade openness, monetary independence and the stability of a country’s currency all contribute to the degree of integration reported.