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Path-dependent Risk Measures - Theory and Applications

dc.contributor.advisorKorn, Olaf Prof. Dr.
dc.contributor.authorMöller, Philipp Maximilian
dc.date.accessioned2021-01-22T12:01:55Z
dc.date.available2021-01-22T12:01:55Z
dc.date.issued2021-01-22
dc.identifier.urihttp://hdl.handle.net/21.11130/00-1735-0000-0005-1559-0
dc.identifier.urihttp://dx.doi.org/10.53846/goediss-8406
dc.language.isoengde
dc.relation.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc330de
dc.titlePath-dependent Risk Measures - Theory and Applicationsde
dc.typedoctoralThesisde
dc.contributor.refereeKorn, Olaf Prof. Dr.
dc.date.examination2021-01-12
dc.description.abstractengThis dissertation addresses various key aspects in risk measurement with path-dependent risk measures. In contrast to most classical risk measures like value-at-risk, (semi-)variance, expected shortfall, or lower partial moments, path-dependent measures like drawdown incorporate the risky object’s path, instead of being functions of the distribution of the risky object at the end of the investment horizon alone. While including this information about the path is beneficial for many reasons – including liquidity, behavioral, and information efficiency reasons –, it adds substantially to the complexity of these measures, which is why little is known about their properties so far. The dissertation addresses this question by analyzing fundamental properties of drawdown measures. Its main findings can be summarized as follows: While changes in lower return moments affect a wide range of drawdown measures similarly, the effect of higher moments varies by drawdown measure. Autocorrelation in the returns does not increase the drawdown as long as the return variance is controlled adequately. A unified framework is devised that comprises almost all current drawdown measures, facilitates the construction of new drawdown measures, simplifies their implementation, and highlights their conceptual differences. All drawdown measures exhibit the capacity to identify stock picking skill in portfolio managers to some degree, and rank their portfolios differently. Moreover, fund drawdown is discovered to exhibit robust relative persistence, which underscores its potential to inform investment decisions. Methodologically, these insights are derived from either simulation studies, portfolio simulations, or the empirical analysis of stock or fund data. They substantially expand the current level of understanding of path-dependent risk measurement, provide a firm basis for further research in this area, and substantiate the application of drawdown measures in practice.de
dc.contributor.coRefereeDierkes, Stefan Prof. Dr.
dc.contributor.thirdRefereeRau, Holger Prof. Dr.
dc.subject.engRisk Measuresde
dc.subject.engRisk Measurementde
dc.subject.engDrawdownde
dc.subject.engDrawdown Risk Measuresde
dc.subject.engAsset Managementde
dc.subject.engPerformance Measurementde
dc.subject.engRegretde
dc.subject.engExponential Lévy Processesde
dc.subject.engRisk Persistencede
dc.identifier.urnurn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-1559-0-4
dc.affiliation.instituteWirtschaftswissenschaftliche Fakultätde
dc.subject.gokfullWirtschaftswissenschaften (PPN621567140)de
dc.identifier.ppn1745522778


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