Model confidence set;
Model selection;
Market risk models;
D O I:
10.1016/j.frl.2017.02.005
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
Two alternative approaches to identifying a model confidence set (MCS) are contrasted. Together with a specification of the established MCS test, we present a new version of a test that identifies a model set satisfying the MCS requirements and is characterised by an alternative model ranking p-value. We also contrast the two MCS approaches empirically, constructing a market risk model selection exercise for the Dow Jones Industrial Average. Our adapted MCS method is shown to lead to a smaller MCS, nested within the MCS determined by the popular MCS method, and allows greater distinction between models. (C) 2017 Elsevier Inc. All rights reserved.
机构:
Univ Paris Est Marne La Vallee, Lab Anal & Math Appl, UFR Math, F-77454 Marne La Vallee 2, FranceUniv Paris Est Marne La Vallee, Lab Anal & Math Appl, UFR Math, F-77454 Marne La Vallee 2, France
Denis, Christophe
Hebiri, Mohamed
论文数: 0引用数: 0
h-index: 0
机构:
Univ Paris Est Marne La Vallee, Lab Anal & Math Appl, UFR Math, F-77454 Marne La Vallee 2, FranceUniv Paris Est Marne La Vallee, Lab Anal & Math Appl, UFR Math, F-77454 Marne La Vallee 2, France
Hebiri, Mohamed
STATISTICAL LEARNING AND DATA SCIENCES,
2015,
9047
: 301
-
312