No abstract

The traditional methods of risk quantification include a sensitivity analysis, a scenario analysis and a historical simulation. The true nature of risk factors changes is ignored in the traditional 'ceteris paribus' approach to a sensitivity analysis, hence it can be reflected in a scenario analysis and a historical simulation. The most significant disadvantage of a scenario analysis is the limited number of scenarios, whereas a historical simulation depends on historical data availability and adequacy. The Monte Carlo simulation is a clear answer to the limitations of traditional methods. The changes of risk factors reflected in the Monte Carlo simulation are simultaneous, non-linear and interdependent. The most important aspect of this method is the stage of taking up the assumptions. The purpose of the paper is to indicate that considering several reasonable sets of assumptions for the Monte Carlo simulation simultaneously can bring even more comprehensive information about enterprise risk.

A significant element of managing corporate finance is forecasting the financial situation of an enterprise. Forecasting means drawing up simplified financial statements (pro--forma). One of the basic components of a financial situation forecast is estimating both: fixed asset levels, as well as their depreciation. In a volatile environment, the natural assumption is volatile demand for production capabilities, as a consequence of volatile economic conditions. Furthermore, eventual changes of the production capabilities being the consequence of purchasing and selling fixed assets are not smooth. Taking the above into account, the authors propose the concept of a financial model for forecasting fixed assets and their depreciation. The implementation of the model is also presented using a case study.Streszczenie: Istotnym elementem procesu zarządzania finansami przedsiębiorstwa jest prognozowanie jego sytuacji finansowej. Polega ono na sporządzeniu sprawozdania pro-forma. Jednym z podstawowych ogniw prognozy sytuacji finansowej jest określenie poziomu aktywów trwałych i ich ekonomicznego zużycia. W zmiennym otoczeniu naturalnym jest założenie o zmiennym zapotrzebowaniu na zdolności produkcyjne jako konsekwencji zmiennej koniunktury gospodarczej. Ponadto ewentualne zmiany zdolności produkcyjnych na skutek nabywania i zbywania aktywów trwałych w celu ich dostosowania do zapotrzebowania mają w rzeczywistości skokowy -a nie płynny -charakter. W konsekwencji w opracowaniu zaproponowano koncepcję modelu finansowego służącego do prognozowania aktywów trwałych i ich ekonomicznego zużycia, które uwzględnia wskazane założenia. Funkcjonowanie modelu finansowego zostało zaprezentowane na przykładzie studium przypadku.Słowa kluczowe: modelowanie finansowe, prognozowanie, finanse przedsiębiorstwa, ryzyko, metoda Monte Carlo.

Environmental taxes, including energy taxes, are applied in all EU Member States. They are considered important instruments in the implementation of the EU energy and climate policies. The main purpose of the research presented in this article is to identify trends in the EU Member States in shaping environmental tax revenues, with particular emphasis on their most important group, i.e., energy taxes. The researchers sought answers to the research question regarding the existence of converging trends in this respect. The “letter values” method was used in the research procedure, which is an extension of the box-plots method. The analysis covered 27 EU Member States. The data used in the research came from the Eurostat database (2009–2020). As a result of the research, it was found that in the EU as a whole, there is a slight downward trend in the share of environmental tax revenues in GDP and the share of environmental tax revenues in total tax revenues, while the share of energy tax revenues in total environmental tax revenues shows a slight upward trend. The decomposition of the research and the conducted comparative analysis, including the determination of specific rankings, showed that both the level and trends in the shaping of the studied variables vary considerably in the individual EU Member States.

A non-financial enterprise with receivables or liabilities denominated in a foreign currency is exposed to currency risk. Wanting to calculate a financial reserve in order to secure its receivables or liabilities, an enterprise can introduce the concept of the value at risk. To determine value at risk, an enterprise has to know the probability distribution of the future value of the receivable or the liability for a specific moment in future. Using a geometric Brownian motion to reflect exchange rate changes is among the possible solutions. The aim of the paper is to indicate that using the Monte Carlo simulation for forecasting the currency risk of an enterprise is a clear, easy-to-implement and flexible in terms of the assumptions approach. The flexibility of the Monte Carlo approach relies on the possibility to take up the assumption that the currency position changes caused by currency fluctuations have an other than normal probability distribution.