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The Model Confidence Set package for R

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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).

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  • Mauro Bernardi & Leopoldo Catania, 2015. "The Model Confidence Set package for R," CEIS Research Paper 362, Tor Vergata University, CEIS, revised 17 Nov 2015.
    • Handle: RePEc:rtv:ceisrp:362
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    Keywords

    Hypothesis testing; Model Confidence Set; Value{at{Risk; VaR combination; ARCH-Models; R-CRAN;
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