EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk

Abstracts

EN

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.

Keywords

EN

value-at-risk; state of turbulence; GARCH; tail distributions; market risk

• Publisher: Uniwersytet Warszawski. Wydział Nauk Ekonomicznych
• Journal: Central European Economic Journal
• Year: 2017
• Volume: 3
• Issue: 50

Dates

published

2018-12-18

Contributors

other

Marcin Chlebus

• Faculty of Economic Science, University of Warsaw Warsaw, Poland

Identifiers

DOI

10.1515/ceej-2017-0014