Predikce finanční výkonnosti podniku v plastikářském průmyslu

Abstract

The aim of diploma thesis is prediction of the company financial performance by the Economic Value Added measure. The prediction based on real seasonal decomposed data is performed for four following quarters by using Monte Carlo simulation. In theoretical part of the paper is described a methology and decomposition of EVA measure according to the narrowed value spread. There is also described typology of stochastic process, simulation due to Cholesky algorithm and seasonal decomposition is presented as well. Practical part of the paper is focused on the company financial performance measured by tradional measures and modern measures such as EVA measure. Next part of the paper is devoted to the prediction of the company financial performance. First of all, there were calculated costs of equity by using methology which use Ministry of Industry and Trade of the Czech Republic. Consequently were calculated financial measures that make up the pyramid decomposition of EVA measure and the indicator EVA. In the time series of financial measures were very noticeable seasonal factors thus there was neccessary to do a seasonal decomposition. The seasonally decomposed time series were base for regression analysis which is used for obtaining model parameters. Those parameters were consequently stastically verified and were used for prediction of each financial measure. Generated were 5 000 scenarios of financial measure development in order to find out probability distribution of EVA measure in each quarter. In each predicted quarter were calculated the mean of EVA measure, standard deviation, Value at Risk (VaR) at 5 % and VaR at 10 %. The results shows that company is creating added value for shareholders in each quarter.