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Value at Risk backtesting techniques: Intuitionistic fuzzy approach and InterCriteria Analysis

机译:风险价值回测技术:直觉模糊方法和标准间分析

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摘要

There are various approaches for development of Value at Risk (VaR) forecasting models but the final steps of a building procedure usually incorporate different validations of the models like adequacy tests and backtesting. These validations provide solid reasons to reject those models which do not pass the tests. However there are situations when several models are deemed to provide good forecasts and for a practical application only one of them should be selected. We suggest a methodology to select the VaR forecasting model which approximates the actual market risk the most closely in cases when there is more than one candidate for a best model. We have used also InterCriteria Analysis to do an additional stability test on the best model.
机译:有多种开发风险价值(VaR)预测模型的方法,但是构建过程的最后步骤通常包含对模型的不同验证,例如充足性测试和回测。这些验证提供了可靠的理由来拒绝那些未通过测试的模型。但是,在某些情况下,有几种模型被认为可以提供良好的预测,而在实际应用中,仅应选择其中一种。我们建议一种方法来选择VaR预测模型,以在有多个最佳模型候选人的情况下最接近实际市场风险。我们还使用InterCriteria分析对最佳模型进行了额外的稳定性测试。

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