Grado de predicción del valor de las acciones ante nuevas emisiones en el sector de extracción de petróleo crudo y gas natural en Colombia, mediante modelos de caos y análisis recurrente
Thesis
The present document study Ecopetrol´s shares in a period of time to may 22th, 2012 to august 30th, 2013. Ecopetrol is one of the most representatives companies in the market to production of oil and gas natural in Colombia (SP&G). For this period of time the Ecopetrol´s shares presented changes in the price, this changes were related with a new emission of debt (share), that the company made. According with the changes in the price, arise a different questions about (i) the reaction in the market, in front of, different success occurred inside the company (ii) the capability of the financial models to predict and understand the possible reactions in the assets (understand as debt). During the development of this paper we will study the relevance, according with the objectives and developments to the Administration College in the Rosario University. Specifically, in topics of perdurability and management where debt is an actual and important part of the organizations, and is understand as determinant variable for the future in the organizations. Once we explicate the relation between the university and the document, we development different concepts and theories that allow study the market in a more specific way, trying to reduce the risk associated to the investment. The mentioned analysis is development in two parts (i) models of discrete time and (ii) models in continuous time. Therefore, we analyze the data through models of Chaos and recurrent analysis. This model permit understand that the shares has a behavior chaotic and permit understand some relations between the current prices and the historic ones. In the otherwise, we will make a description to the oil market y we study Ecopetrol in Colombia as a Company and important participant in the market. To finish, we present the results of the paper, and some recommendations from the observation.
