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dc.contributor.authorFrahm, Gabrielen_US
dc.description.abstractSuppose that we are searching for the maximum of many unknown and analytically untractable quantities or, say, the 'best alternative' among several candidates. If our decision is based on historical or simulated data there is some sort of selection bias and it is not evident if our choice is significantly better than any other. In the present work a large sample test for the best alternative is derived in a rather general setting. The test is demonstrated by an application to financial data and compared with the Jobson-Korkie test for the Sharpe ratios of two asset portfolios. We find that ignoring conditional heteroscedasticity and non-normality of asset returns can lead to misleading decisions. In contrast, the presented test for the best alternative accounts for these kinds of phenomena.en_US
dc.publisherUniv., Seminar für Wirtschafts- und Sozialstatistik Kölnen_US
dc.relation.ispartofseriesDiscussion papers in statistics and econometrics 7/07en_US
dc.subject.keywordGordin's conditionen_US
dc.subject.keywordJobson-Korkie testen_US
dc.subject.keywordMonte Carlo simulationen_US
dc.subject.keywordperformance measurementen_US
dc.subject.keywordSharpe ratioen_US
dc.titleTesting for the best alternative with an application to performance measurementen_US
dc.typeWorking Paperen_US
Appears in Collections:Discussion Papers in Econometrics and Statistics, Institut für Ökonometrie und Statistik, Universität Köln

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