Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/334113 
Year of Publication: 
2024
Citation: 
[Journal:] Asian Journal of Economics and Banking (AJEB) [ISSN:] 2633-7991 [Volume:] 8 [Issue:] 1 [Year:] 2024 [Pages:] 54-66
Publisher: 
Emerald, Leeds
Abstract: 
Purpose - This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory. Design/methodology/approach - The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability measures. Findings - In elaborating the new statistical analysis of non-Euclidean data sets, the paper illustrates the generalization of traditional aspects of statistical inference following Frechet's program. Originality/value - Besides the elaboration of research methodology for a new data analysis, the paper discusses the applications of Wasserstein metrics to the robustness of financial risk measures.
Subjects: 
Frechet mean sets
Histogram data sets
Optimal transport
Random probability measures
Robustness of financial risk measures
Wasserstein metrics
Wasserstein sampling spaces
WGAN
JEL: 
C10
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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