Aplikace simulací Monte Carlo v bankovnictví

Currently, banking is exposed to huge market risks. One of those risks is occurrence of negative interest rates in the EU. Nowadays, it is important to use sophisticated and modern measurement tools and approaches to measure and manage banking risks. One of those methods is Monte Carlo simulation. This bachelor thesis is aimed at analysis and prediction of 3-month maturity Prague Interest Offer Rate (PRIBOR) for 3, 6 and 12 months with using Monte Carlo simulations. It was found that this method is suitable for prediction market variables with low volatility. If anybody uses this method, it is necessity to have in mind all pitfalls and assumptions, that this method includes, as an adequate random generated number of scenarios, approximation of correct probability distribution, independence of dataset and not least, as far as possible, to focus on factors generating randomness of market variable and not the prices, that express rather consequences of randomness than its cause. Further, the Monte Carlo prediction was compared with prognosis of the Czech Nation Bank and it was found that Monte Carlo prediction is more accurate for short term predictions. 12-month prediction of Monte Carlo simulation discovered also possible occurrence of negative interest rate at 0,05% level of probability in compare to the Czech National Bank prognosis, where was no negative interest rate predicted.