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The use of mutual information to improve value-at-risk forecasts for exchange rates

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dc.contributor.author Antwi, Albert
dc.contributor.author Kyei, Kwabena
dc.contributor.author Gill, Ryan
dc.date.accessioned 2021-08-30T09:35:18Z
dc.date.available 2021-08-30T09:35:18Z
dc.date.issued 2020
dc.identifier.issn 2169-3536
dc.identifier.uri http://10.1109/ACCESS.2020.3027631
dc.description.abstract In this paper, we show a simple but novel approach in an attempt to improve value-at-risk forecasts. We use mutually dependent covariate returns to create exogenous break variables and jointly use the variables to augment GARCH models to account for time-variations and breaks in the unconditional volatilityprocessessimultaneously.Astudyofhypotheticalmutualdependenciesbetweenvolatilityandthe covariates is first carried out to investigate the levels of the shared mutual information among the variables before using the augmented models to forecast 1% and 5% value-at-risks. The results provide evidence of some substantial exchange of information between volatility and the lagged exogenous covariates. Inaddition,theresultsshowthattheestimatedaugmentedmodelshavelowervolatilitypersistence,reduced information leakages, and improved explanatory powers. Furthermore, there is evidence that our approach leads to fewer violations, improved 1% value-at-risk forecasts, and optimal daily capital requirements for all the models. There is, however evidence of relative superiority of the majority of the models for the 5% value-at-risksforecastsfromourapproach,althoughtheyhaverelativelyhigherfailurerates.Basedonthese results,werecommendtheincorporationofourapproachtoexistingriskmodelingframeworks.Itisbelieved that such models may lead to fewer bank failures, expose banks to optimal market risks, and assist them in computing optimal regulatory capital requirements and minimize penalties from regulators. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries volume 8;
dc.subject Exogenous break en_US
dc.subject mutual information en_US
dc.subject value-at-risk en_US
dc.subject volatility en_US
dc.title The use of mutual information to improve value-at-risk forecasts for exchange rates en_US
dc.type Article en_US


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