Template-type: ReDIF-Paper 1.0
Author-Name: Chia-Lin Chang
Author-Email: changchialin@nchu.edu.tw
Author-Person: pch286 
Author-Workplace-Name: Department of Applied Economics, Department of Finance, National Chung Hsing University, Taiwan
Author-Name: Juan-Ángel Jiménez-Martín
Author-Email: juanangel@ccee.ucm.es
Author-Homepage: https://www.ucm.es/fundamentos-analisis-economico2/jajm
Author-Person: pji27 
Author-Workplace-Name: Departamento de Economía Cuantitativa (Department of Quantitative Economics), 
	Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad 
	Complutense de Madrid
Author-Workplace-Homepage: https://www.ucm.es/fundamentos-analisis-economico2
Author-Workplace-Homepage: https://www.ucm.es/icae
Author-Name: Esfandiar Maasoumi
Author-Workplace-Name: Department of Economics, Emory University
Author-Name: Teodosio Pérez Amaral
Author-Workplace-Name: Departamento de Economía Cuantitativa (Department of Quantitative Economics), 
	Facultad de Ciencias Económicas y Empresariales (Faculty of Economics and Business), Universidad 
	Complutense de Madrid
Author-Workplace-Homepage: https://www.ucm.es/fundamentos-analisis-economico2
Author-Workplace-Homepage: https://www.ucm.es/icae
Title: A Stochastic Dominance Approach to Financial Risk Management Strategies 
Abstract: The Basel III Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) 
	communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each 
	trading day, using one of a range of alternative risk models to forecast Value-at-Risk (VaR). The risk 
	estimates from these models are used to determine the daily capital charges (DCC) and associated capital 
	costs of ADIs, depending in part on the number of previous violations, whereby realized losses exceed the 
	estimated VaR. In this paper we define risk management in terms of choosing sensibly from a variety of 
	risk models and discuss the optimal selection of financial risk models. A previous approach to model 
	selection for predicting VaR proposed combining alternative risk models and ranking such models on the 
	basis of average DCC. This method is based only on the first moment of the DCC distribution, supported 
	by a restrictive evaluation function. In this paper, we consider uniform rankings of models over large 
	classes of evaluation functions that may reflect different weights and concerns over different intervals 
	of the distribution of losses and DCC. The uniform rankings are based on recently developed statistical 
	tests of stochastic dominance (SD). The SD tests are illustrated using the prices and returns of VIX 
	futures. The empirical findings show that the tests of SD can rank different pairs of models to a 
	statistical degree of confidence, and that the alternative (recentered) SD tests are in general agreement.
Classification-JEL: G32, G11, G17, C53, C22.
Keywords: Stochastic dominance; Value-at-Risk; daily capital charges; violation penalties; optimizing strategy; 
	Basel III Accord; VIX futures; global financial crisis.
Note: The authors are most grateful to Michael McAleer for many comments and suggestions. For financial support, 
	the first author wishes to thank the National Science Council, Taiwan, and the second and fourth authors 
	acknowledge the Ministerio de Economía y Competitividad and Comunidad de Madrid, Spain.
Length: 33 pages
Creation-Date: 2014 
Revision-Date: 2014-04  
Number: 2014-08 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1408.txt
File-URL: https://eprints.ucm.es/id/eprint/25124/1/1408.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1408