The Model Confidence Set Package for R

23 Pages Posted: 20 Nov 2015

See all articles by Mauro Bernardi

Mauro Bernardi

University of Padua

Leopoldo Catania

Aarhus University - School of Business and Social Sciences; Aarhus University - CREATES

Date Written: November 17, 2015


This paper presents the R package MCS which implements the Model Confidence Set (MCS) procedure recently developed by Hansen, Lunde, and Nason (2011). The Hansen's procedure consists on a sequence of tests which permits to construct a set of "superior" models, where the null hypothesis of Equal Predictive Ability (EPA) is not rejected at a certain confidence level. The EPA statistic tests is calculated for an arbitrary loss function, meaning that we could test models on various aspects, for example punctual forecasts. The relevance of the package is shown using an example which aims at illustrating in details the use of the functions provided by the package. The example compares the ability of different models belonging to the ARCH family to predict large financial losses. We also discuss the implementation of the ARCH-type models and their maximum likelihood estimation using the popular R package rugarch developed by Ghalanos (2014).

Keywords: Hypothesis testing, Model Confidence Set, Value-at-Risk, VaR combination, ARCH-Models, R-CRAN

Suggested Citation

Bernardi, Mauro and Catania, Leopoldo, The Model Confidence Set Package for R (November 17, 2015). CEIS Working Paper No. 362, Available at SSRN: or

Mauro Bernardi (Contact Author)

University of Padua ( email )

Via 8 Febbraio
Padova, Vicenza 2-35122

Leopoldo Catania

Aarhus University - School of Business and Social Sciences ( email )

Fuglesangs Allé 4
Aarhus V, DK-8210
+4587165536 (Phone)


Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C

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