Kvantifikace tržního rizika portfolia akcií pomocí metody Value at Risk

Abstract

This diploma thesis focuses on the quantification of market risk using the Value at Risk (VaR) methodology within the context of increased global financial market volatility between 2020 and 2025. The goal of the submitted diploma thesis was the application of Value at Risk calculation methods to a selected stock portfolio in the current market environment. The analysis was performed on a model equity portfolio with a total exposure of USD 100,000, consisting of Apple, Booking, Netflix, PepsiCo, and Thermo Fisher Scientific. The theoretical section defines the mathematical foundations of the variance-covariance method, historical simulation, and bootstrapping. The practical section analyzes the statistical properties of returns based on real market data, identifying non-normality and the presence of fat tails. The results demonstrate that at the 95% confidence level, the chosen methods yield consistent estimates with minimal deviations. However, significant divergence occurs at extreme confidence levels (above 98%), where non-parametric models, particularly bootstrapping, better reflect historical market shocks. The thesis concludes by formulating specific recommendations for various types of investors based on their risk aversion and proposes portfolio hedging strategies using derivative instruments, stop-loss limits, and sector diversification.