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Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology

Indranil Ghosh, Amith Vikram Megaravalli, Mohammad Abedin Orcid Logo, Kazim Topuz

Annals of Operations Research, Volume: 346, Issue: 3, Pages: 2423 - 2459

Swansea University Author: Mohammad Abedin Orcid Logo

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DOI (Published version): 10.1007/s10479-025-06491-1

Abstract

The growing media buzz and industry focus on the emergence and rapid development of Metaverse technology have paved the way for the escalation of multifaceted research. Specific Metaverse coins have come into existence, but they have barely seen any traction among practitioners despite their tremend...

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Published in: Annals of Operations Research
ISSN: 0254-5330 1572-9338
Published: Springer Nature 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa68745
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last_indexed 2025-03-28T06:15:18Z
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spelling 2025-03-27T11:42:10.3843236 v2 68745 2025-01-27 Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology 4ed8c020eae0c9bec4f5d9495d86d415 0000-0002-4688-0619 Mohammad Abedin Mohammad Abedin true false 2025-01-27 CBAE The growing media buzz and industry focus on the emergence and rapid development of Metaverse technology have paved the way for the escalation of multifaceted research. Specific Metaverse coins have come into existence, but they have barely seen any traction among practitioners despite their tremendous potential. The current work endeavors to deeply analyze the temporal characteristics of 6 Metaverse coins through the lens of predictive analytics and explain the forecasting process. The dearth of research imposes serious challenges in building the forecasting model. We resort to a granular prediction setup incorporating the Maximal Overlap Discrete Wavelet Transformation (MODWT) technique to disentangle the original series into subseries. Facebook's Prophet and TBATS algorithms are utilized to individually draw predictions on granular components. Aggregating components-wise forecasted figures achieve the final forecast. Facebook's Prophet is deployed in a multivariate setting, applying a set of explanatory features covering macroeconomic, technical, and social media indicators. Rigorous performance checks justify the efficiency of the integrated forecasting framework. Additionally, to interpret the black box typed prediction framework, two explainable artificial intelligence (XAI) frameworks, SHAP and LIME, are used to gauge the nature of the influence of the predictor variables, which serve several practical insights. Journal Article Annals of Operations Research 346 3 2423 2459 Springer Nature 0254-5330 1572-9338 Metaverse coin; Maximal overlap discrete wavelet transformation (MODWT); Facebook’s prophet; TBATS; Explainable artificial intelligence (XAI) 1 3 2025 2025-03-01 10.1007/s10479-025-06491-1 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2025-03-27T11:42:10.3843236 2025-01-27T11:31:30.1786216 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Indranil Ghosh 1 Amith Vikram Megaravalli 2 Mohammad Abedin 0000-0002-4688-0619 3 Kazim Topuz 4 68745__33504__92ad2e22c1b34e8ba9cf3eabe4c789c1.pdf 68745.VOR.pdf 2025-02-05T13:16:00.0541866 Output 4616426 application/pdf Version of Record true Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License (CC-BY 4.0). true eng http://creativecommons.org/licenses/by/4.0/
title Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
spellingShingle Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
Mohammad Abedin
title_short Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
title_full Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
title_fullStr Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
title_full_unstemmed Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
title_sort Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Mohammad Abedin
author Mohammad Abedin
author2 Indranil Ghosh
Amith Vikram Megaravalli
Mohammad Abedin
Kazim Topuz
format Journal article
container_title Annals of Operations Research
container_volume 346
container_issue 3
container_start_page 2423
publishDate 2025
institution Swansea University
issn 0254-5330
1572-9338
doi_str_mv 10.1007/s10479-025-06491-1
publisher Springer Nature
college_str Faculty of Humanities and Social Sciences
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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
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description The growing media buzz and industry focus on the emergence and rapid development of Metaverse technology have paved the way for the escalation of multifaceted research. Specific Metaverse coins have come into existence, but they have barely seen any traction among practitioners despite their tremendous potential. The current work endeavors to deeply analyze the temporal characteristics of 6 Metaverse coins through the lens of predictive analytics and explain the forecasting process. The dearth of research imposes serious challenges in building the forecasting model. We resort to a granular prediction setup incorporating the Maximal Overlap Discrete Wavelet Transformation (MODWT) technique to disentangle the original series into subseries. Facebook's Prophet and TBATS algorithms are utilized to individually draw predictions on granular components. Aggregating components-wise forecasted figures achieve the final forecast. Facebook's Prophet is deployed in a multivariate setting, applying a set of explanatory features covering macroeconomic, technical, and social media indicators. Rigorous performance checks justify the efficiency of the integrated forecasting framework. Additionally, to interpret the black box typed prediction framework, two explainable artificial intelligence (XAI) frameworks, SHAP and LIME, are used to gauge the nature of the influence of the predictor variables, which serve several practical insights.
published_date 2025-03-01T07:31:02Z
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