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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Prediction of the future condition of the company by indicators of financial health
 RANDUS, Petr
The aim of this master thesis is to verify the classification methods of current models. The basis for the research part of the thesis is the definition of the financial situation in a company, which is created on the grounds of relevant literature and assumptions related to the negative financial situation of a company. According to this definition, an enterprise with no financial difficulties must achieve positive profits for a five-year period related to the value of the assets at the end of the reporting period, and during the reporting period the entity must not achieve a negative or zero cash-flow. Afterwards, the current classification models, which determine the financial situation of the company, were examined. The application of the models took place on data from companies belonging to different sectors to avoid distorted results. Selected sectors are not similar on purpose. The total reliability of classification was examined on selected classification models on the classification matrices basis for each of the analyzed sectors. The results of the current classification methods were unsatisfactory in terms of the number of correct classifications. The main benefit of this thesis was to create a predictive state model of the dependent variable. The model indicates whether the analyzed enterprise achieves a five-year return ratio and the asset size reaches values higher or lower than the value selected. This value may be the industry average of the mentioned indicator. The suggested linear model has been tested on a test(control) enterprise database.
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Magazine sales prediction
 Rajčan, Šimon ; Pokorný, Jaroslav (advisor) ; Mrázová, Iveta (referee)
Today, many magazine publishing houses faces the problem of future predictions of their products. In many cases, these predictions are made by employees based on their personal experiences and guesses. The problems of this attitude are high expanses on making the predictions and increased expanses when those predictions are wrong. The aim of this work is to study existing regression methods of automatic prediction and create a solution for predicting the magazine sales in Russian publishing house Burda.
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