On the classification of financial data with domain agnostic features

João Bastos and Jorge Caiado

No 2021/0185, Working Papers REM from ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa

Abstract: We compare a data-driven domain agnostic set of canonical features with a smaller collection of features that capture well-known stylized facts about financial asset returns. We show that these facts discriminate better different asset types than general-purpose features. Therefore, financial time series analysis is a domain where well-informed expert knowledge may not be disregarded in favor of agnosticrepresentations of the data.

Keywords: Financial economics; Time series; Clustering; Classification; Machine learning (search for similar items in EconPapers)
Date: 2021-07
New Economics Papers: this item is included in nep-cmp and nep-ets
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ise:remwps:wp01852021

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