Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification

By Valentina Corradi, Norman R. Swanson. 2006

105 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/20714c80af7e226d31fc95861ec441f787a421f2

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Citations in the corpus

Testing for Structural Stability of Factor Augmented Forecasting Models (2014, background): “As shown in the (unnumbered) Proposition in Han and Inoue (2012), the criterion of Bai and Ng (2002), applied to the full sample, will detect 2 factors.”
Alternative tests for correct specification of conditional predictive densities (2019, methodology): “We are interested in the test statistics: κP = sup r∈[0,1] |ΨP (r) |, (4) CP = ∫ 1 0 ΨP (r) 2 dr. (5) The κP test statistic is the same as the V1T test statistic considered by Corradi and Swanson (2006a) when applied to predictive densities.”
Nonparametric tests for conditional symmetry in dynamic models (2007, methodology): “In a related but different problem, Corradi and Swanson (2006) use the block bootstrap for Kolmogorov-type conditional distribution tests under dynamic misspecification and parameter estimation error.”
Quantile aggregation of density forecasts (2014, unknown): “…has been progressively extended to density forecasts in order to gauge the relative performance of different prediction models in terms of their distributions; see, inter alia, Diebold et al. (1998), Corradi and Swanson (2003, 2006), Mitchell and Hall (2005), Amisano and Giacomini (2007).”
Likelihood-based scoring rules for comparing density forecasts in tails (2011, methodology): “This problem of relative predictive accuracy has been considered by Sarno and Valente (2004); Mitchell and Hall (2005); Corradi and Swanson (2005, 2006b); Amisano and Giacomini (2007) and Bao et al. (2004, 2007).”
The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series (2014, unknown): “This contribution fits into a long literature of testing predictability using signs or rank statistics, including the papers of Cowles and Jones (1937), Dufour et al. (1998), and Christoffersen and Diebold (2002).”
Combining inflation density forecasts (2010, methodology): “These tests require the assumption of correct specification of the density forecast under the null hypothesis using all the relevant information (e.g. Diebold, Gunther & Tay 1998, Bai 2003) or conditional on a given information set (Corradi & Swanson 2003a).”
Advances in Forecasting Under Instability (2012, unknown): “48Diebold, Gunther and Tay (1998) and Corradi and Swanson (2006a) propose methodologies for evaluating the correct speci cation of density forecasts in stable environments see Corradi and Swanson (2006b) for an excellent review.”