Predikce finanční výkonnosti společnosti v potravinářském průmyslu

Abstract

The aim of this thesis is to verify the possibility of prediction of economic value added, based on the real data of a company operating in the food industry. Prediction of financial performance is derived from the estimated mean-reversion stochastic processes of partial financial indicators using Monte Carlo simulation in term of four quarters. The work is divided, plus an introduction and conclusion, into three main chapters. The second chapter presents the theoretical part of the work, it consists of two main parts and it is the basis for the third and the fourth, practical chapters. The first part of the theoretical chapter is devoted to the characterization of economic value added, determination the cost of equity and to the issue of decomposition of synthetic indicators. In the second part of theoretical chapter the method of prediction of economic value added is described and there is also explained the procedure of simulation of partial financial indicators using stochastic processes. Furthermore a methodology of aplication the Monte Carlo simulation technique is presented here for generating random experiments, including Cholesky algorithm. In the third, practical chapter, the company is introduced and there is analysed the financial performance of the company using ratio indicators. There is also included the analysis of the financial performance of the company aimed to measure the economic performance of the company. There are costs of equity calculated using the modular method and the economic value added is quantified based on narrowed range of values. There is also made a pyramid decomposition of economic value added using functional method and comparation of the company and the industry in which it operates. The fourth, also practical chapter is focused on the verification of the possibility of prediction of EVA, which is derived from from the estimated stochastic processes of partial financial indicators using Monte Carlo simulation in term of four quarters.