Automatic portmanteau tests with applications to market risk management
Guangwei Zhu (),
Zaichao Du and
Juan Carlos Escanciano
Additional contact information
Guangwei Zhu: Southwestern University of Finance and Economics
Stata Journal, 2017, vol. 17, issue 4, 901-915
Abstract:
In this article, we review some recent advances in testing for serial correlation, provide code for implementation, and illustrate this code’s application to market risk forecast evaluation. We focus on the classic and widely used portman- teau tests and their data-driven versions. These tests are simple to implement for two reasons: First, the researcher does not need to specify the order of the tested autocorrelations, because the test automatically chooses this number. Second, its asymptotic null distribution is chi-squared with one degree of freedom, so there is no need to use a bootstrap procedure to estimate the critical values. We illustrate the wide applicability of this methodology with applications to forecast evaluation for market risk measures such as value-at-risk and expected shortfall. Copyright 2017 by StataCorp LP.
Keywords: dbptest; rtau; autocorrelation; consistency; power; Akaike’s information criterion; Schwarz’s Bayesian information criterion; market risk (search for similar items in EconPapers)
Date: 2017
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj17-4/st0504/
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0504 link to article purchase
Related works:
Working Paper: Automatic Portmanteau Tests with Applications to Market Risk Management (2017) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:17:y:2017:i:4:p:901-915
Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html
Access Statistics for this article
Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins
More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().