Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis

Sven Serneels

Papers from arXiv.org

Abstract: Betas are possibly the most frequently applied tool to analyze how securities relate to the market. While in very widespread use, betas only express dynamics derived from second moment statistics. Financial returns data often deviate from normal assumptions in the sense that they have significant third and fourth order moments and contain outliers. This paper targets to introduce a way to calculate generalized betas that also account for higher order moment effects, while maintaining the conceptual simplicity and interpretability of betas. Thereunto, the co-moment analysis projection index (CAPI) is introduced. When applied as a projection index in the projection pursuit (PP) framework, generalized betas are obtained as the directions optimizing the CAPI objective. A version of CAPI based on trimmed means is introduced as well, which is more stable in the presence of outliers. Simulation results underpin the statistical properties of all projections and a small, yet highly illustrative example is presented.

Date: 2019-07
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in In: JSM Proceedings, Business and Economic Statistics Section, 2019. Alexandria, VA: American Statistical Association. 3009-3035

Downloads: (external link)
http://arxiv.org/pdf/1908.00141 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1908.00141

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().