Metodologías de valoración de empresas

La valoración de una empresa como sistema dinámico es bastante compleja, los diferentes modelos o métodos de valoración son una aproximación teórica y por consiguiente simplificadora de la realidad. Dichos modelos, se aproximan mediante supuestos o premisas estadísticas que nos permiten hacer dicha simplificación, ejemplos de estos, son el comportamiento del inversionista o la eficiencia del mercado. Bajo el marco de un mercado emergente, este proceso presenta de indistinta forma retos paracualquier método de valoración, dado a que el mercado no obedece a los paradigmas tradicionales. Lo anterior hace referencia a que la valoración es aún más compleja, dado que los inversionistas se enfrentan a mayores riesgos y obstáculos. Así mismo, a medida que las economías se globalizan y el capital es más móvil, la valoración tomaráaún más importancia en el contexto citado. Este trabajo de gradopretende recopilar y analizar los diferentes métodos de valoración, además de identificar y aplicar aquellos que se reconocen como “buenas prácticas”. Este proceso se llevó a cabo para una de las empresas más importantes de Colombia, donde fundamentalmente se consideró el contexto de mercado emergente y específicamente el sector petrolero, como criterios para la aplicación del tradicional DCF y el práctico R&V.

Lógica en la toma de decisiones de inversión en el sector de extracción de petróleo y gas natural

Este documento se centra en la presentación de información y análisis de la misma a la hora de establecer la manera en que empresas del sector de extracción de gas natural y generación de energía a base de dicho recurso, toman decisiones en cuanto a inversión, centrándose en la lógica que usan a la hora de emprender este proceso. Esto debido a la constante necesidad de establecer procesos que permitan tomar decisiones más acertadas, incluyendo todas las herramientas posibles para tal fin. La lógica es una de estas herramientas, pues permite encadenar factores con el fin de obtener resultados positivos. Por tal razón, se hace importante conocer el uso de esta herramienta, teniendo en cuentas de qué manera y en que contextos es usada. Con el fin de tener una mayor orientación, este estudio estará centrado en un sector específico, el cual es el de la extracción de petróleo y gas natural. Lo anterior entendiendo la necesidad existente de fundamentación teórica que permita establecer de manera clara la forma apropiada de tomar decisiones en un sector tan diverso y complejo como lo es el mencionado. El contexto empresarial actual exige una visión global, no basada en la lógica lineal causal que hoy se tiene como referencia. El sector de extracción de petróleo y gas natural es un ejemplo particular en cuanto a la manera en cuanto se toman decisiones en inversión, puesto que en su mayoría son empresas de capital intensivo, las cuales mantienen un flujo elevado de recursos monetarios.

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.

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.

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.

Commercial real estate and equity market bubbles: are they contagious to REITs?

This paper uses a regime-switching approach to determine whether prices in the US stock, direct real estate and indirect real estate markets are driven by the presence of speculative bubbles. The results show significant evidence of the existence of periodically partially collapsing speculative bubbles in all three markets. A multivariate bubble model is then developed and implemented to evaluate whether the stock and real estate bubbles spill over into REITs. The underlying stock market bubble is found to be a stronger influence on the securitised real estate market bubble than that of the property market. Furthermore, the findings suggest a transmission of speculative bubbles from the direct real estate to the stock market, although this link is not present for the returns themselves.

An alternative approach to investigating lead-lag relationships between stock and stock index futures markets

In the absence of market frictions, the cost-of-carry model of stock index futures pricing predicts that returns on the underlying stock index and the associated stock index futures contract will be perfectly contemporaneously correlated. Evidence suggests, however, that this prediction is violated with clear evidence that the stock index futures market leads the stock market. It is argued that traditional tests, which assume that the underlying data generating process is constant, might be prone to overstate the lead-lag relationship. Using a new test for lead-lag relationships based on cross correlations and cross bicorrelations it is found that, contrary to results from using the traditional methodology, periods where the futures market leads the cash market are few and far between and when any lead-lag relationship is detected, it does not last long. Overall, the results are consistent with the prediction of the standard cost-of-carry model and market efficiency.

Testing for bubbles in indirect property price cycles

Speculative bubbles are generated when investors include the expectation of the future price in their information set. Under these conditions, the actual market price of the security, that is set according to demand and supply, will be a function of the future price and vice versa. In the presence of speculative bubbles, positive expected bubble returns will lead to increased demand and will thus force prices to diverge from their fundamental value. This paper investigates whether the prices of UK equity-traded property stocks over the past 15 years contain evidence of a speculative bubble. The analysis draws upon the methodologies adopted in various studies examining price bubbles in the general stock market. Fundamental values are generated using two models: the dividend discount and the Gordon growth. Variance bounds tests are then applied to test for bubbles in the UK property asset prices. Finally, cointegration analysis is conducted to provide further evidence on the presence of bubbles. Evidence of the existence of bubbles is found, although these appear to be transitory and concentrated in the mid-to-late 1990s.

The financial and environmental performance of firms exposed to the EU Emissions Trading Scheme

This thesis is an empirical-based study of the European Union’s Emissions Trading Scheme (EU ETS) and its implications in terms of corporate environmental and financial performance. The novelty of this study includes the extended scope of the data coverage, as most previous studies have examined only the power sector. The use of verified emissions data of ETS-regulated firms as the environmental compliance measure and as the potential differentiating criteria that concern the valuation of EU ETS-exposed firms in the stock market is also an original aspect of this study. The study begins in Chapter 2 by introducing the background information on the emission trading system (ETS), which focuses on (i) the adoption of ETS as an environmental management instrument and (ii) the adoption of ETS by the European Union as one of its central climate policies. Chapter 3 surveys four databases that provide carbon emissions data in order to determine the most suitable source of the data to be used in the later empirical chapters. The first empirical chapter, which is also Chapter 4 of this thesis, investigates the determinants of the emissions compliance performance of the EU ETS-exposed firms through constructing the best possible performance ratio from verified emissions data and self-configuring models for a panel regression analysis. Chapter 5 examines the impacts on the EU ETS-exposed firms in terms of their equity valuation with customised portfolios and multi-factor market models. The research design takes into account the emissions allowance (EUA) price as an additional factor, as it has the most direct association with the EU ETS to control for the exposure. The final empirical Chapter 6 takes the investigation one step further, by specifically testing the degree of ETS exposure facing different sectors with sector-based portfolios and an extended multi-factor market model. The findings from the emissions performance ratio analysis show that the business model of firms significantly influences emissions compliance, as the capital intensity has a positive association with the increasing emissions-to-emissions cap ratio. Furthermore, different sectors show different degrees of sensitivity towards the determining factors. The production factor influences the performance ratio of the Utilities sector, but not the Energy or Materials sectors. The results show that the capital intensity has a more profound influence on the utilities sector than on the materials sector. With regard to the financial performance impact, ETS-exposed firms as aggregate portfolios experienced a substantial underperformance during the 2001–2004 period, but not in the operating period of 2005–2011. The results of the sector-based portfolios show again the differentiating effect of the EU ETS on sectors, as one sector is priced indifferently against its benchmark, three sectors see a constant underperformance, and three sectors have altered outcomes.

Echoes of 1992: the NAFTA negotiations and North America now

Two decades ago, Canada, Mexico, and the United States created a continental economy. The road to integration from the signing of the North American Free Trade Agreement has not been a smooth one. Along the way, Mexico lived through a currency crisis, a democratic transition, and the rising challenge of Asian manufacturing. Canada stayed united despite surging Quebecois nationalism during the 1990s; since then, it has seen dramatic economic changes with the explosion of hydrocarbon production and a much stronger currency. The United States saw a stock-market bust, the shock of 9/11, and the near-collapse of its financial system. All of these events have transformed the relationships that emerged after NAFTA entered into force in 1994. Given the tremendous changes, one might be skeptical that the circumstances and details of the negotiation and ratification of NAFTA hold lessons for the future of North America. However, the road to NAFTA had its own difficulties, and many of the issues involved in the negotiations underpin today's challenges. NAFTA was conceived at a time of profound change in the international system. When Mexican leaders surveyed the world two decades ago, they saw emerging regional groupings in Europe, Asia, and South America. Faced with a lack of interest or compatibility, they instead doubled down on North America. How did Mexican leaders reconsider their national interests and redefine Mexico's role in the world in light of those transformations? Unpublished Mexican documents from SECOFI, the secretariate most involved in negotiating NAFTA, help illustrate Mexican thinking about its interests and role at that time. Combining those insights with analysis of newly available evidence from U.S. presidential archives, this paper sheds light on the negotiations that concluded two decades ago.

Institutional investors: arbitrageurs or rational trend chasers?

This paper studies the relationship between institutional investor holdings and stock misvaluation in the U.S. between 1980 and 2010. I find that institutional investors overweigh overvalued and underweigh undervalued stocks in their portfolio, taking the market portfolio as a benchmark. Cross-sectionally, institutional investors hold more overvalued stocks than undervalued stocks. The time-series studies also show that institutional ownership of overvalued portfolios increases as the portfolios' degree of overvaluation. As an investment strategy, institutional investors' ride of stock misvaluation is neither driven by the fund flows from individual investors into institutions, nor industry-specific. Consistent with the agency problem explanation, investment companies and independent investment advisors have a higher tendency to ride stock misvaluation than other institutions. There is weak evidence that institutional investors make positive profit by riding stock misvaluation. My findings challenge the models that view individual investors as noise traders and disregard the role of institutional investors in stock market misvaluation.