Weighted score-driven fuzzy clustering of time series with a financial application
Journal article
Cerqueti, R., D’Urso, P., De Giovanni, L., Giacalone, M. and Mattera, R. (2022). Weighted score-driven fuzzy clustering of time series with a financial application. Expert Systems with Applications. 198, p. 116752. https://doi.org/10.1016/j.eswa.2022.116752
Authors | Cerqueti, R., D’Urso, P., De Giovanni, L., Giacalone, M. and Mattera, R. |
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Abstract | Time series data are commonly clustered based on their distributional characteristics. The moments play a central role among such characteristics because of their relevant informative content. This paper aims to develop a novel approach that faces still open issues in moment-based clustering. First of all, we deal with a very general framework of time-varying moments rather than static quantities. Second, we include in the clustering model high-order moments. Third, we avoid implicit equal weighting of the considered moments by developing a clustering procedure that objectively computes the optimal weight for each moment. As a result, following a fuzzy approach, two weighted clustering models based on both unconditional and conditional moments are proposed. Since the Dynamic Conditional Score model is used to estimate both conditional and unconditional moments, the resulting framework is called weighted score-driven clustering. We apply the proposed method to financial time series as an empirical experiment. |
Year | 2022 |
Journal | Expert Systems with Applications |
Journal citation | 198, p. 116752 |
Publisher | Elsevier |
ISSN | 09574174 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eswa.2022.116752 |
Publication dates | |
05 Mar 2022 | |
Publication process dates | |
Accepted | 23 Feb 2022 |
Deposited | 30 Mar 2022 |
Accepted author manuscript | License File Access Level Open |
Page range | 116752 |
Permalink -
https://openresearch.lsbu.ac.uk/item/8z746
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Accepted author manuscript
Weighted_score_driven_fuzzy_clustering_of_financial_time_series - LSBU.pdf | ||
License: CC BY-NC-ND 4.0 | ||
File access level: Open |
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