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Wyszukujesz frazę "value at risk" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions
Autorzy:
Szubzda, Filip
Chlebus, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/1356736.pdf
Data publikacji:
2020-03-20
Wydawca:
Uniwersytet Warszawski. Wydział Nauk Ekonomicznych
Tematy:
Value-at-Risk
extreme value theory
forecasting
market risk
Opis:
The aim of the presented study was to assess the quality of VaR forecasts in various states of the economic situation. Two approaches based on the extreme value theory were compared: Block Maxima and the Peaks Over Threshold. Forecasts were made on the daily closing prices of 10 major indices in European countries, divided into two groups: emerging countries (Bulgaria, Czech Republic, Lithuania, Latvia, Poland, Slovakia and Hungary) and developed countries (England, France and Germany). Three states of economic situation were analysed: the pre-crisis (2007), the crisis (2008) and the post-crisis (2009) period as out-of-sample. The main conclusion obtained is the too slow process of adapting static EVT-based forecasts to market movements. While in the pre-crisis period the results were satisfactory, in the period of crisis VaR forecasts were too often exceeded.
Źródło:
Central European Economic Journal; 2019, 6, 53; 70 - 85
2543-6821
Pojawia się w:
Central European Economic Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk
Autorzy:
Chlebus, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/1357422.pdf
Data publikacji:
2018-12-18
Wydawca:
Uniwersytet Warszawski. Wydział Nauk Ekonomicznych
Tematy:
value-at-risk
state of turbulence
GARCH
tail distributions
market risk
Opis:
In the study, the two-step EWS-GARCH models to forecast Value-at-Risk is presented. The EWS-GARCH allows different distributions of returns or Value-at-Risk forecasting models to be used in Value-at-Risk forecasting depending on a forecasted state of the financial time series. In the study EWS-GARCH with GARCH(1,1) and GARCH(1,1), with the amendment to the empirical distribution of random errors as a Value-at-Risk model in a state of tranquillity and empirical tail, exponential or Pareto distributions used to forecast Value-at-Risk in a state of turbulence were considered. The evaluation of Value-at-Risk forecasts was based on the Value-at-Risk forecasts and the analysis of loss functions. Obtained results indicate that EWS-GARCH models may improve the quality of Value-at-Risk forecasts generated using the benchmark models. However, the choice of best assumptions for the EWS-GARCH model should depend on the goals of the Value-at-Risk forecasting model. The final selection may depend on an expected level of adequacy, conservatism and costs of the model.
Źródło:
Central European Economic Journal; 2017, 3, 50; 1 - 25
2543-6821
Pojawia się w:
Central European Economic Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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