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Producción + Limpia

Print version ISSN 1909-0455

Abstract

BOADA, Antonio  and  CASTANO, Diego. Techniques of financial multiples to value shares of companies in the electricity sector in Colombia. Rev. P+L [online]. 2019, vol.14, n.2, pp.61-92.  Epub Oct 30, 2020. ISSN 1909-0455.  https://doi.org/10.22507/pml.v14n2a6.

Introduction:

Through this article, a new procedure for the valuation of shares is documented, through business financial multiples, but with the support of statistical techniques for the future proj ection of scenarios, tools for simulation, and even Bayesian models of continuous valuation of relative indicators in time.

Objective:

Develop a financial statistical technique to assess share price in the secondary market in the medium term.

Materials and Methods:

This methodology introduces a new concept of valuation, combining the traditional technique of financial multiples with the probabilistic simulation of future scenarios through the use of Risk Simulator and finally the creation of a percentage indicator to estímate the share price in the secondary market, by means of a Bayesian dynamic linear model of these previous simulations.

Results:

In this work five phases were documented, which begin with an analysis of the information provided by Bloomberg in the Colombian electricity sector companies (ISAGEN, CELSIA and ISA), and then generate a structure through the use of multiples financial policies defined and documented for its application. Based on this structural information, the variables used in the valuation for the future five years (until 2020) were projected, with the purpose of calculating the financial multiples of the theoretical results and being able to perform Monte Carlo simulations based on established probability distributions for each causal variable, according to their historical behavior.

Conclusions:

Finally, with these values of the financial multiples determined through the simulation, and the real price of the share in the market, the Relative Comparison Indicator (IRC) is calculated, which will present historical values, offering support for making projections through a Bayesian Dynamic Linear Model, in order to forecast in the medium term the average annual share value for each company in the electricity sector in Colombia (ISAGEN, CELSIA and ISA) during the years 2016 to 2020.

Keywords : Securities market; Trading desk; Financial Prospective; Bayesian Models; Financial Statistics.

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