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金融尾部风险预测评价：等预测能力检验AI 解读

This paper provides comprehensive simulation results on the finite sample properties of the Diebold-Mariano (DM) test by Diebold and Mariano (1995) and the model confidence set (MCS) testing procedure by Hansen et al. (2011) applied to the asymmetric loss functions specific to financial tail risk forecasts, such as Value-at-Risk (VaR) and Expected Shortfall (ES). We focus on statistical loss functions that are strictly consistent in the sense of Gneiting (2011a). We find…

条件预测方法置信集AI 解读

This paper proposes a Conditional Method Confidence Set (CMCS) which allows to select the best subset of forecasting methods with equal predictive ability conditional on a specific economic regime. The test resembles the Model Confidence Set by Hansen et al. (2011) and is adapted for conditional forecast evaluation. We show the asymptotic validity of the proposed test and illustrate its properties in a simulation study. The proposed testing procedure is particularly suitable…