Ποσοτικά μέτρα κινδύνου με εφαρμογές στα χρηματοοικονομικά και στον αναλογισμό
Quantitative measures of risk with applications in finance and actuarial science
In this thesis, quantitative risk measures which consist a timeless, topical and crucial subject of financial and actuarial science, are studied. The theory that has been developed around risk measures, their categorization into several classes, their importance at mapping the risk, as well as, their connection with the regulating-supervisory framework that define financial organizations, are presented. In addition, the most prominent quantitative risk measures, “Value-at-Risk” (VaR) and “Expected Shortfall” (ES), are analyzed and compared. In the framework of this work, the estimation methods of “Value-at-Risk” and “Expected Shortfall” are mentioned, giving emphasis on the parametric method and the time series analysis that defines it. Finally, this thesis ends with an empirical application, using numerous conditional heteroscedasticity models for the risk estimation of two stock indexes and giving some conclusions.