Institute of Economic Research
Topic
Quantile risk measures and their applications in financial investment.
PhD. program
Year of admission
2025
Name of the supervisor
doc. Ing. Tomáš Výrost, PhD.
Contact:
Receiving school
Fakulta matematiky, fyziky a informatiky UK
Annotation
The proposed dissertation is to deal with the modeling of quantile risk measures and their application. While classical risk measures such as volatility tend to be symmetrical, which can be perceived as a shortcoming, quantile-based measures take into account the asymmetric nature of risk while at the same time allowing attention to be focused on the left tail of the probability distribution of asset returns, i.e., on the area where risk management is most needed. In recent years, there has been a significant shift in the use of quantile risk measures. For example, the Basel Commission on Banking Supervision prefers using the Expected Shortfall quantile measure in its version of the Basel III standards. From a theoretical point of view, several mathematically interesting results have been published in recent years, which allow the estimation of spectral risk measures that are non-elicitable (Fissler – Ziegel, 2016; Patton et al., 2019; Dimitriadis – Bayer, 2019; Jiang et al., 2020). The dissertation should examine different quantile risk measures, as well as their properties and applications in financial investing.