Analýza a predikce ekonomické přidané hodnoty podniku zpracovatelského průmyslu

Abstract

The dissertation thesis is devoted to the verification of analysis and prediction of economic value added in terms of a particular company. The analysis is performed through the pyramidal decomposition methodology of indicator economic value added, which is expressed by mutual relations between the partial indicators. Variance analysis for additive and multiplicative connection is used to express the influence of partial indicators on change of top indicator. The logarithmic method is practically applied in the case of multiplicative relations. The starting point of prediction is stochastic random evolution of assets over time and mean-reversion process - Vasicek model. Prediction of selected partial indicators of economic value added decompositon, which is performed by Monte Carlo simulation, is based on the stochastic evelution of assets. Monthly data obtained from company financial statements are the input data for prediction. Final prediction indicator EVA is performed for twelve months.