Sökning: "Generalized Pareto Distribution"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden Generalized Pareto Distribution.
1. The Performance of Market Risk Models for Value at Risk and Expected Shortfall Backtesting : In the Light of the Fundamental Review of the Trading BookMaster-uppsats, KTH/Matematisk statistik
Sammanfattning : The global financial crisis that took off in 2007 gave rise to several adjustments of the risk regulation for banks. An extensive adjustment, that is to be implemented in 2019, is the Fundamental Review of the Trading Book (FRTB). LÄS MER
- Master-uppsats, KTH/Matematisk statistik; KTH/Matematisk statistik
Sammanfattning : This thesis aims to discern what factors and assumptions are the most important in market risk modeling through examining a broad range of models, for different risk measures (VaR0.01, S0:01 and ES0:025) and using hierarchical clustering to identify similarities and dissimilarities between the models. LÄS MER
- Master-uppsats, KTH/Matematisk statistik
Sammanfattning : This thesis project studies robust portfolio optimization with Expected Short-fall applied to a reference portfolio consisting of Swedish linear assets with stocks and a bond index. Specifically, the classical robust optimization definition, focusing on uncertainties in parameters, is extended to also include uncertainties in log-return distribution. LÄS MER
4. An empirical comparison of extreme value modelling procedures for the estimation of high quantilesMaster-uppsats, Uppsala universitet/Statistiska institutionen
Sammanfattning : The peaks over threshold (POT) method provides an attractive framework for estimating the risk of extreme events such as severe storms or large insurance claims. However, the conventional POT procedure, where the threshold excesses are modelled by a generalized Pareto distribution, suffers from small samples and subjective threshold selection. LÄS MER
- Kandidat-uppsats, Uppsala universitet/Statistiska institutionen
Sammanfattning : The volatility model approach to forecasting Value at Risk is complemented with modelling of Expected Shortfalls using an extreme value approach. Using three models from the GARCH family (GARCH, EGARCH and GJR-GARCH) and assuming two conditional distributions, normal Gaussian and Student t’s distribution, to make predictions of VaR, the forecasts are used as a threshold for assigning losses to the distribution tail. LÄS MER
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