On using fuzzy clustering for detecting the number of states in Markov switching models

Edoardo Otranto () and Luca Scaffidi Domianello ()
Additional contact information
Edoardo Otranto: Sapienza University of Rome, and CRENoS
Luca Scaffidi Domianello: University of Catania

Annals of Operations Research, 2025, vol. 349, issue 3, No 13, 1855-1890

Abstract: Abstract An open problem of Markov switching models is identifying the number of states, generally fixed a priori; it is impossible to apply classical tests due to the issue of the nuisance parameters present only under the alternative hypothesis. In this work, we show, by Monte Carlo simulations, that fuzzy clustering is able to reproduce the parametric state inference derived from the Hamilton filter and that the typical indices used in clustering to determine the number of groups can be used to identify the number of states in this framework. The procedure is very simple to apply, considering that it is performed independently of the data generating process and that the indicators we use are available in most statistical packages. Furthermore, the proposed approach appears to be sufficiently robust to perturbations in the data generating processes. A final application of real data completes the analysis.

Keywords: Nuisance parameters; Groups identification; Monte Carlo simulations; Markov chains (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-025-06585-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:annopr:v:349:y:2025:i:3:d:10.1007_s10479-025-06585-w

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-025-06585-w

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().