Clustering and Testing Financial Asset Returns Using the Spatial Dynamic Panel Data Model

Giuseppe Feo (), Francesco Giordano (), Sara Milito (), Marcella Niglio () and Maria Lucia Parrella ()
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Giuseppe Feo: University of Salerno
Francesco Giordano: University of Salerno
Sara Milito: University of Salerno
Marcella Niglio: University of Salerno
Maria Lucia Parrella: University of Salerno

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2024, pp 160-166 from Springer

Abstract: Abstract In this work, we consider a spatio-temporal financial dataset, with $$p=84$$ p = 84 units (a sample of asset returns from the “G7” countries) and $$T=666$$ T = 666 daily observations, from May 2021 to December 2023. Assuming that the p units can be grouped into clusters, we apply a clusterized spatial dynamic panel data model and a multiple testing procedure, to investigate the best partition of clusters for the dataset. We show that, among the three candidate partitions considered in our analysis, the best partition is the one based on the asset’s economic sector.

Keywords: Clustering; spatio-temporal models; financial returns (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-64273-9_27

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DOI: 10.1007/978-3-031-64273-9_27

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