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The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China

Shusheng Ding Orcid Logo, Tianxiang Cui Orcid Logo, Anthony Graham Bellotti, Abedin Abedin, Brian Lucey

International Review of Financial Analysis, Volume: 90, Start page: 102851

Swansea University Author: Abedin Abedin

  • Accepted Manuscript under embargo until: 5th August 2025

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DOI (Published version): 10.1016/j.irfa.2023.102851

Abstract

The prediction of firm financial distress during the COVID-19 crisis episode attracted massive academic attention since economic uncertainty was exacerbated. In this paper, we propose a firm financial distress prediction model based on the Extreme Gradient Boosting-Genetic Programming (XGB-GP) frame...

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Published in: International Review of Financial Analysis
ISSN: 1057-5219 1873-8079
Published: Elsevier BV 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa64218
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spelling v2 64218 2023-08-31 The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China 4ed8c020eae0c9bec4f5d9495d86d415 Abedin Abedin Abedin Abedin true false 2023-08-31 BAF The prediction of firm financial distress during the COVID-19 crisis episode attracted massive academic attention since economic uncertainty was exacerbated. In this paper, we propose a firm financial distress prediction model based on the Extreme Gradient Boosting-Genetic Programming (XGB-GP) framework by investigating subsamples of pre-COVID and post-COVID periods. The key contribution of our paper is that we explore time-varying prediction features for pre-COVID and post-COVID periods. We illuminate that the earning financial indicator is the dominant feature for financial distress prediction during the pre-COVID period, whereas total financial leverage is the most important factor during the post-COVID period. On this basis, our XGB-GP financial distress prediction model exhibits higher prediction accuracy than the traditional models. As a result, managers can modify the financial leverage level to improve the financial situation of the firm by reducing the debt burden and increasing profitability during the post-COVID period. Journal Article International Review of Financial Analysis 90 102851 Elsevier BV 1057-5219 1873-8079 Financial distress prediction, Time-varying feature selection, Extreme gradient boosting, Genetic programming, COVID-19 crisis 30 11 2023 2023-11-30 10.1016/j.irfa.2023.102851 http://dx.doi.org/10.1016/j.irfa.2023.102851 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2023-10-16T10:24:06.9161973 2023-08-31T17:15:33.4475312 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Shusheng Ding 0000-0001-5745-7552 1 Tianxiang Cui 0000-0002-0102-2581 2 Anthony Graham Bellotti 3 Abedin Abedin 4 Brian Lucey 5 Under embargo Under embargo 2023-10-16T10:22:07.9652345 Output 296123 application/pdf Accepted Manuscript true 2025-08-05T00:00:00.0000000 Distributed under the terms of a Creative Commons CC-BY-NC-ND licence. true eng https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
title The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
spellingShingle The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
Abedin Abedin
title_short The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
title_full The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
title_fullStr The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
title_full_unstemmed The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
title_sort The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Abedin Abedin
author Abedin Abedin
author2 Shusheng Ding
Tianxiang Cui
Anthony Graham Bellotti
Abedin Abedin
Brian Lucey
format Journal article
container_title International Review of Financial Analysis
container_volume 90
container_start_page 102851
publishDate 2023
institution Swansea University
issn 1057-5219
1873-8079
doi_str_mv 10.1016/j.irfa.2023.102851
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
url http://dx.doi.org/10.1016/j.irfa.2023.102851
document_store_str 0
active_str 0
description The prediction of firm financial distress during the COVID-19 crisis episode attracted massive academic attention since economic uncertainty was exacerbated. In this paper, we propose a firm financial distress prediction model based on the Extreme Gradient Boosting-Genetic Programming (XGB-GP) framework by investigating subsamples of pre-COVID and post-COVID periods. The key contribution of our paper is that we explore time-varying prediction features for pre-COVID and post-COVID periods. We illuminate that the earning financial indicator is the dominant feature for financial distress prediction during the pre-COVID period, whereas total financial leverage is the most important factor during the post-COVID period. On this basis, our XGB-GP financial distress prediction model exhibits higher prediction accuracy than the traditional models. As a result, managers can modify the financial leverage level to improve the financial situation of the firm by reducing the debt burden and increasing profitability during the post-COVID period.
published_date 2023-11-30T10:24:08Z
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score 11.012924

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