Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann
September 2011
Research Paper
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Patton and Timmermann (2011, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', Journal of Business & Economic Statistics, forthcoming) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a regression that only involves (long-horizon and short-horizon) forecasts and no observations on the target variable. We propose an extension, a simulation-based procedure that takes into account the presence of errors in parameter estimates. This procedure can also be applied in the field of 'backtesting' models for Value-at-Risk. Applications to simple AR and ARCH time series models show that its power in detecting certain misspecifications is larger than the power of well-known tests for correct Unconditional Coverage and Conditional Coverage.
- G32 : Financing Policy; Capital and Ownership Structure
- C52 : Model Evaluation and Testing
- C53 : Forecasting and Other Model Applications
- C12 : Hypothesis Testing
- model
- forecast
- revision
- error
- parameter
- regression
- revision regression test
- value
- v art |t
- power
- value-at-risk
- revision test
- cc tests
- rationality
- institute
- revision regression
- parameter estimates
- coverage
- timmermann
- patton
