Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary [Previous title:
2019
We propose forecast encompassing tests for the Expected Shortfall (ES) jointly
with the Value at Risk (VaR) based on flexible link (or combination) functions.
Our setup allows testing encompassing for convex forecast combinations and for
link functions which preclude crossings of the combined VaR and ES forecasts. As
the tests based on these link functions involve parameters which are on the boundary
of the parameter space under the null hypothesis, we derive and base our tests on
nonstandard asymptotic theory on the boundary. Our simulation study shows that
the encompassing tests based on our new link functions outperform tests based on
unrestricted linear link functions for one-step and multi-step forecasts. We further
illustrate the potential of the proposed tests in a real data analysis for forecasting
VaR and ES of the S&P 500 index.
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